FS&P Ph.D. Thesis no. 8/1995 ISSN no.
at The University of Roskilde, Denmark.
Den overordnede målsetning med avhandlingen er å teste hypotesen: fra et stort oljetankskips perspektiv (skip > 200.000 dwt) kan aggregert etterspørsel bli formulert som en funksjon av Midt-Østen produsentene i "Organization of Petroleum Exporting Countries" (OPEC) sin eksport av råolje og raffinerte produkter. Dette aggregerte etterspørselsforholdet vil bli behandlet som en produksjonsfunksjon for tankmarkedet, som igjen vil bli samordnet i et nytt konsept for kapasitetsutnyttelse anvendt mot shipping. Dette konseptet for kapasitetsutnyttelse vil bli integrert i en ny managementmodell for tankmarkedet.
Basert på en sekvensiell teoretisk og empirisk analyse, er en studie av oljestrømmen fra OPEC Midt-Østen blitt utført.
Filosofien bak oljetilførselen ble undersøkt i form av teoretiske og empiriske analyser relatert til OPECs oljetilførsel og prisadferd. En kartelladferd ble identifisert. En ny studier, ble utført under forutsetning av antatt kartelladferd. En del av denne oljeproduksjonen, OPECs Midt-Østen eksport av råolje og raffinerte produkter, ble relatert til tankmarkedet gjennom en produktfunksjon.
Denne produktfunksjonen er en del av et nytt konsept for kapasitetsutnyttelse for tankmarkedet, som også er blitt utviklet.
Politiske hendelser i Midt-Østen kan influere aggregert tanketterspørsel via oljeproduksjonsadferden direkte, eller indirekte ved at oljestrømmene kan forskyves ved direkte forhindrelse av eksport eller at gjennomstrømningsmønsteret i oljerørledningene i regionen blir forandret slik at utskipningspunktene får ny vektlegging. Konsekvensene av mulige politiske hendelser i regionen har blitt vurdert i konteksten av individuelle OPEC-lands nåværende og sannsynlige fremtidige produksjonskapasitet, samt eksisterende og planlagte — oljerørledninger (eksportkapasitet).
Det nye kapasitetsutnyttelsesbegrepet som er blitt utviklet er blitt formulert i en management sammenheng ved at det er etablert en enkel analytisk modell for beslutningstagere innen tankskipsfart. Modellen kan bli integrert i en foreslått generell analytisk heuristisk scenario prosedyre for analyse av tankmarkedet, hvor konsekvensene av slike politiske hendelser blir inkorporert.
A Thesis Submitted in Partial Satisfaction Towards the Degree of Ph. D.
at The University of Roskilde, Department of Social Sciences, Denmark.
(Submitted September 1994)
The overall objective of the dissertation is to test the hypothesis: From a large tanker perspective (vessels > 200.000 dwt), aggregate demand can be stated as a function of the Organization of Petroleum Exporting Countries (OPEC) Middle East oil supply.
integrated into a management model for the tanker market.
Based on a sequential theoretical and empirical analysis, a study of the flow of crude oil from the OPEC Middle East oil producers is performed.
variable within the planning process of a tanker company.
The philosophy behind the oil supply was investigated in the form of theoretical and empirical analyses related to the OPEC oil supply and oil pricing behaviour. A cartel behaviour was subsequently identified. A different empirical test of the aggregate OPEC (oil pricing) behaviour, to previously published empirical studies, was conducted by assuming a cartel.
the tanker market through a production function.
tanker market, which has been developed.
Political events in the Middle East may influence the oil supply behaviour directly or indirectly through the alteration of the oil flow by redistribution within the pipeline grid in the region, and may ultimately cause variations in tanker demand. Such events have been undertaken in the context of individual OPEC member countries'
existing and planned oil pipelines.
The new capacity utilization concept has been brought into a managerial context by establishing a simple analytical model for decision making by managers in tanker shipping.
analytical heuristic scenario procedure for the analysis of the tanker market.
II. LIST OF TABLES III.
1.3 Structure of the Dissertation 1.
2. BACKGROUND 2.1 General Remarks Related to Crude Oil Tankers and the Oil Market 2.
4. OIL SUPPLY BEHAVIOUR 4.
59 59 4.2.
4.2.3.1 Distribution of Production Within a Cartel (Acting as a Monopolist)
5.3.4 A Production and Output to Capital Based Capacity Utilization Term 5.
166 166 8.3 A Simple Analytical Model 172 8.3.1 Alternative Analyses 175 8.3.
9. POSSIBLE ADJUSTMENTS OF THE PRODUCTION FUNCTION(S)
IN THE MIDDLE EAST 185 9.1 General 185 9.2 OPEC Reserves and Production Levels 186 9.2.1 Development of Capacity and Production 186 9.2.2 The Capacity Situation at Year-end 1994 to the Late 1990s 193 9.3 Pipeline Projects in the Middle East 201 9.3.1 Operational and Inoperational Pipelines 201 9.3.2 Closed Pipelines 216 9.3.3 Proposed Pipelines 208 9.
with respect to Tanker Demand 212 10. DISCUSSION AND CONCLUSIONS 216 11. REFERENCES 229 11.1 Sources for Numerical Data 240 11.
ANALYSIS 244 APPENDIX B:
APPENDIX C: PUBLISHED PAPERS 309 Table 2.1 Historical development of maximum tanker size. Table 2.2 OECD oil product consumption mix for the years 1979, 1983 and 1988.
over the percentage change in end user consumer prices unless specified otherwise.
Table 2.4 Sensitivity of OPEC total oil demand to a change in the price of crude oil.
Table 2.5 Global crude oil reserves.
Table 4.1 Comparison of alternative hypotheses tests for OPEC countries under rising and falling oil prices.
Table 4.2 and 4.3 Estimated regression parameters.
Table 1, App. ch. 4 OPEC Middle East exports, Middle East exports and international trade with crude oil and refined petroleum products.
Table 6.1 and 6.2 Estimated regression parameters.
Table 1, App. ch. 6 Consumption data for world outside communist countries, and total non-OPEC supply. Actual and desired OECD company stocks data.
Table 2, App. ch. 6 Official selling price for Arabian Lt., spot price-official price ratio and OPEC adj. demand/supply ratio.
Tables 7.1 to 7.6 Estimated regression parameters.
Tables 7.7 to 7.16 VLCC employment data and representative fleet data for the years 1980, 1985, 1987, 1988, 1989.
Table 7.17 A comparison of yearly tanker employment data.
149 159 oil and NGL production, OPEC Middle East crude oil production, OPEC Middle East exports, total OPEC exports, Middle East exports, aggregate tanker tonne-miles.
Table 2 App. ch. 7 Distance matrix in nautical miles.
Table 3 to 7 App. ch. 7 Tonne-miles matrix for OBOs (trading with oil) and tankers above 200.
1985, 1987, 1988, 1989.
Tables 8.1 to 8.5 Estimated regression parameters.
Table 8.6 A comparison of the various models.
Tables 1 to 3 App. ch. 8 Some quarterly time series.
Table 4 App. ch. 8 Spot freight rates data.
Table 9.1 Installed OPEC crude oil capacity and proved oil reserves.
Table 9.2 OPEC crude oil production levels.
Table 9.3 (Representative) OPEC sustainable crude oil capacities.
Table 9.4 1990 and 1994 sustainable and available capacities.
Table 9.5 Late 1990s OPEC crude oil sustainable capacity projections.
Table 9.6 Operational and inoperational pipelines in the Middle East.
Table 9.7 Closed pipelines in the Middle East.
Table 9.8 Proposed pipelines in the Middle East.
Table 9.9 Difference in tonne-miles when exporting 1.0 mbd from Ceyhan (Turkey) instead of from AG.
Table 9.10 Difference in tonne-miles when exporting 1.0 mbd from AG (Ras Tanura) via Cape of the Good Hope vs. via Suez and from Yanbu via Suez.
Table 9.11 Tonne-miles consequences per 1.
some possible pipelines in the Middle East.
214 Figure 1.1 Structure of the dissertation.
Figure 1.2 A different way of viewing the structure of the thesis.
Figure 2.1 Yearly average spot freight rates and nominal secondhand values for a 1975/76 built 280.000 dwt turbine tanker VLCC.
Figure 2.2 Total world primary energy consumption in mtoe.
Figure 3.1 Schematic overview of different scenario techniques.
Figure 3.2 A conceptual framework for a new worldview.
Figure 3.3 Strategic decision method involving the use of scenarios.
Figure 3.4 Scenario/payoff matrix.
Figure 4.1 OPEC as a multiplant monopolist.
Figure 4.2 A cartel acting as a monopolist.
Figure 4.3 World supply and demand with a backward bending supply curve.
Figure 4.4 OPEC as an oligopolistic dominant firm.
Figure 4.5 Pareto optimal frontier for a two group cartel.
Figure 4.6 International trade with crude oil and refined petroleum products vs. Middle East exports of crude oil and refined petroleum products and OPEC Middle East exports of crude oil and refined petroleum products.
Figure S.1 A generalized scheme for the analysis of the market for large tankers.
Figure 6.1 The schematics of a model of the world oil market.
Figure 6.2 Actual company stocks data and model fit.
Figure 6.3 Graph of the spot price for Arabian Lt. (or Iranian Lt.)
actual data and model fit.
127 to q4 1989 period. Figures 8.2 to 8.4 Actual spot freight rates and model fit.
Figure 9.1 OPEC Middle East and OPEC non-Middle East oil production.
Figure 9.2 Map of the Middle East.
168 174 191 205 Shipping can be divided into four different sectors;
- Industry shipping (cruise operations, liner services)
- Contract shipping (bulk pools, chemical tanker pools)
- Special shipping (Liquefied Natural/Petroleum Gas (LNG/LPG) - Commodity shipping (tanker, dry bulk, Ore-Bulk-Oil (OBO)).
For all these sectors two studies: McKinsey (1985) and McKinsey (1989), list four success factors; (1) superior analytical skills, (2) operational expertise, (3) wide strategic flexibility and financial freedom, and (4) a strong bias for action and aggressiveness. One of these success factors, superior analytical skills, can be said to be the philosophical basis or justification for this dissertation.
managing large tankers.
The overall objective of the dissertation is to test the hypothesis:
large tanker perspectivel)
1) vessels > 200.000 dwt, exemplified by tankers in the 200.000 dwt to 300.000 dwt range, the Very Large Crude Carriers or VLCCs.
be treated as a production function for the tanker market, which again is to be integrated into a new concept of capacity utilization applied to shipping. This represents what is called the top-down approach (see later section for definition) to tanker demand. The bottom-up approach (see later section for definition) of testing the above stated hypothesis, is to verify by actual tanker movements that the Middle East region is of paramount importance with respect to large tanker (VLCC) demand.
In order to relate this new capacity utilization term into a managerial context, it is to be expanded into an aggregate analytical model of the world tanker market. This scheme is to be applied as a conceptual framework for analyzing and understanding the market for large tankers (VLCCs) by the majority of the individuals within the managerial echelon within a tanker company.
available production capacity.
2) Organization of Petroleum Exporting Countries (OPEC) was founded in 1960. The members are, with the year they joined in parenthesis: Saudi Arabia (1960), Kuwait (1969), Iran (1960), Iraq (1960), Venezuela (1960), Qatar (1961), Libya (1962), Indonesia (1962), Abu Dhabi (1967), Algeria (1969), Nigeria (1971), Ecuador (1973, withdrew from the organization January 1, 1993), Dubai and Sharjah (1974). Gabon (1973 associated member, 1975 full member). OPEC Middle East: UAE (Abu Dhabi, Dubai, Sharjah), Iran, Iraq, Kuwait, Saudi Arabia, Neutral Zone, Qatar.
The Norwegian Shipowners' Association requested McKinsey & Co [McKinsey (1989)] to assist in the development of perspectives on the understanding of what is required, at the strategic level, to be successful in the highly dynamic shipping markets. A point to be addressed was how shipping companies could take advantage of opportunities that follow changes in the market place and how they could understand and avoid being exposed to potentially fatal risks.
required in the following areas:
- An In-depth understanding of international economics including a close monitoring of macroeconomic developments.
- Interpretation of OPEC strategies in order to identify important trends in the freight markets.
product strategies.
On this basis the theme of this thesis has emerged.
As stated, the overall objective of the dissertation is to test the hypothesis that from a large tanker perspective, aggregate demand for tankers can be treated as a function of the OPEC Middle East oil supply.
determined and are as such beyond the scope of this dissertation.
scenario procedure for the tanker market (ch. 3)
Behavioural aspects of Development of a new the (OPEC) Middle East capacity utilization Theoretical oil supply (ch. 4) concept (ch. 5)
Empirical test of Production supply sided function (top- model (ch. 5) behaviour (ch. 6) | [down analysis)
cha Empirical testof a Empirical Tanker movement simple analytical analysis analysis in support of model (ch. 8)
: production function due to å | | perspective (bottom-up the use of Middle East | analysis) (ch. 7) pipelines (ch. 3) | Es Managerial | Decisions (buy or sell yv.yv. considerations | |vessels, chartering | policy)
Structure of the dissertation.
Figure 1.1 visualizes the structure of the dissertation, and provides an overview of how the different parts fit together.
been investigated.
petroleum products, was related to the tanker market through a production function. This production function is part of a new concept of capacity utilization for the tanker market, which has been developed. A tanker movement analysis has been performed in support of the production function from a VLCC perspective. Political events in the Middle East may influence the oil supply behaviour directly or indirectly through the alteration of the oil flow and may ultimately cause variations in tanker demand. The new capacity utilization concept has been brought into a managerial context by establishing a simple analytical model for decision making by managers in tanker shipping.
procedure for the analysis of the tanker market.
Middle East - from a large tanker management perspective.
they fit together.
The main body of the dissertation starts with chapter 3; A General Analytical Heuristic Scenario Procedure for the Tanker Market.
knowledge and experience concern the past, while we have to make decisions procedure may promote options planning and closer understanding of interacting factors. It may further help to anticipate and understand the complex issue of risk.
The primary objective of the chapter is to suggest a generalized scenario scheme or analytical procedure for the analysis of the tanker market.
the Middle East.
the tanker market, with emphasis on the OPEC Middle East supply situation:
1. Define the scope of the analysis.
2. Based on various assumptions oil demand projections are made.
3. Forecast(s) of the non-OPEC oil supply is (are) stated.
4. Based on discussions in chapters 4 and 6, the demand for OPEC oil is derived.
5. Based on the (simple) model which is developed in chapters 5 and 8 with the production function of chapters 4 and 7, all key market variables are assumed identified.
The objective in these chapters is to provide an understanding of the philosophy behind tanker demand, by providing an analysis of the oil supply, theories about the oil market, and (OPEC) oil supply behaviour. The empirical validity of the several alternative hypotheses about oil production behaviour and the (individual) OPEC member countries is also examined. This leads into chapter 6 where the objective is to test the validity of the hypotheses stated in chapter 4 (ref. cartel theory).
A different empirical test, to previously published empirical studies, of the aggregate OPEC (oil pricing) behaviour is conducted by assuming a cartel.
The (quarterly average) spot price for oil is hypothesized (and tested) to be a function of the disequilibrium between the adjusted demand (see chapter 6 for definition) for OPEC oil and the actual supply of OPEC oil.
Chapter 4 ends by suggesting a production function for the tanker market. The objective of chapter 7 is to test the validity of the function, and to perform a comprehensive study of tanker movements to support the validity of stating such a production function.
The (OPEC) Middle East oil supply is related to aggregate tanker demand by a production function by hypothesizing that production (tonne-miles) is a function of the OPEC Middle East oil supply (exports). The analysis is based on aggregale statistical data, an approach which may be labelled a top-down approach.
states that from a large lanker perspective one can focus entirely on the (OPEC) Middle East situation as far as tanker demand is concerned, a comprehensive study of tanker movements has been performed.
This comprehensive study is based on extensive search in Lloyd's of London Press' Databases. From individual tanker (and combined carrier) movements, the number of sailings and total deadweight tonnes (dwt) for several years have been established. By combining tanker and combined carrier movements with distance matrices, it is possible to establish the amount of Middle East employment (amount of tonne-miles which are produced) by large tankers. The analytical technique or process of aggregating and structuring disaggregated industry data, can be labelled a bottom-up approach.
In this particular case we are talking about a bottom-up approach to the analysis of (VLCC) tanker demand.
parameters.
The objective of chapter S is to develop a new capacity utilization term which incorporates the (stated) production function for the tanker market. The objective of chapter 8 is to provide an empirical analysis of the (new concept of) capacity utilization, and its expansion into a simple analytical model. The capacity utilization term proposed by the author differs from all the five discussed methods.
establishing a conceptual framework or model along the following lines: seaborne trade, measured in tonne-miles. The output (tonne-miles demand) is converted to demand for trading tonnage by a conversion- or productivity factor (output to capital relationship). Together with the amount of storage vessels, this constitutes the demand side for tankers.
The pure tanker fleet and the combined carriers make up the supply side. By taking account of the orderbook for tankers and combined carriers and scheduled deliveries, future developments of the total [leet can be stated. By combining supply and demand for tankers, it is possible to establish likely future capacity utilization rates for the total fleet. Utilization rales are hypothesized (and tested) to be a good indicator of the VLCC spot rate level.
The objective of chapter 9 is to pinpoint the concept of adjustments or sensitivities to the production function with respect to the use and disuse of pipelines in the Middle East (due to political events in the region). With a general high level of tension in the Middle East region and associated great uncertainty, political events may influence aggregate tonne-miles demand. In relation to a discussion of spare oil exports capacity, a discussion of operational, inoperational and closed crude oil pipelines in the Middle East is performed, and possible new pipeline projects in the region are assessed. The consequences with respect to adjustments to the production function (tonne-miles consequences) due to the use of some of the pipelines, are analyzed for sensitivily purposes (scenarios).
Political events in the Middle East may influence oil supply behaviour directly or indirectly through the alteration of the oil flow (OPEC Middle East exports of crude oil and refined petroleum products)
variations in tonne-miles demand.
This may influence capacity utilization which again will influence spot tanker freight rates.
behaviour (oil supply).
theory (ch. 4), empirical il test (ch. 6)
|| (production function), theory (ch. 4), empirical test (ch. 7)
consequences). A suggested analytical scenario procedure for the analysis of the tanker market, (ch. 3)
lf empirical evidence (ch.
Å empirical test (ch. 8)
Adjustments in tanker demand (production function)
events (ch. 9)
A different way of viewing the structure of the thesis.
Figure 1.2 A different way of viewing the structure of the thesis is to follow the flow of oil, ref. figure 1.2.
Based on a sequential theoretical and empirical analysis, the flow of oil is followed from the behaviour of the OPEC Middle East oil producers, all the way to the planning table of a tanker company.
primary market variable within the planning process of a tanker company.
Throughout the analytical part of the dissertation the concept of disequilibrium has been used (e.g.
hypothesis, capacity utilization for the tanker market).
A different empirical test from those discussed in section 4.3 of the aggregate OPEC (oil pricing) behaviour, is conducted by assuming a cartel. The (quarterly average) spot price for oil is hypothesized to be a function of the disequilibrium between the adjusted demand for OPEC oil and the actual supply of OPEC oil. Adjusted demand for OPEC oil is the residual demand for OPEC oil (Dy) corrected by the factor [actual Organization for Economic Cooperation and Development (OECD) company stocks - desired OECD company stocks]; 1. where desired OECD company stocks are X-11 (statistical adjustment procedure) adjusted OECD company stocks figures.
both upward and downward price fluctuations.
procedure with some trend-impact elements was argued, and is suggested for the analysis of the tanker market, with emphasis on the OPEC Middle East supply situation.
particular scenario.
The (OPEC) Middle East oil supply is related to aggregate tanker demand by a production function (top-down approach) by hypothesizing that production (tonne-miles) is a function of the OPEC Middle East oil supply (exports). To support the production function from a VLCC point of view, a comprehensive study of tanker movements has been undertaken.
quantity of the exportable oil in world trade comes from this region.
Both oil flow concepts ; "OPEC Middle East exports" and "(total) Middle East exports" are highly significant and representative aggregate behavioural variables for aggregate tonne-miles demand. At the same time it justifies the applied approach to establish production functions for the tanker market.
utilization in shipping, which has been developed.
The following new concept of capacity utilization (CAP) has been established;
CAP = [DTR + Dsv]/[F + (1-B)Sobo] (1.1)
petroleum products) P = Aggregate productivity Dgy = Demand for (stationary)
F = Total tanker fleet (1-B)Sobo = Combined carriers trading with dry cargo.
The new capacity utilization term may be labelled production and output to capital based. It (eq. 1.1) relates a production function (DTM)
factor (P) (output to capital relationship) which converts the production function 10 capital (dwt). Together with storage vessels (Dgy), this represents the total demand for capital or tonnage. The denominator represents the total supply potential of tankers and combined carriers (combined carriers not trading liquid bulk).
Data series for aggregate productivity have been established, together with functional relationships linking aggregate productivity to spot freight rates, trend factors etc. The functional relationship(s)
within the simple analytical model. The new concept of capacity utilization is brought into a managerial context by establishing a conceptual framework or model.
freight rates (SFR), was derived to be:
SFR = A[CAP]B, A and B are constants. (1.2) The dependant variable, SFR, was hypothesized to be a function of capacity utilization (CAP), which represents the disequilibrium between the total demand for ship tonnage and potential tanker supply. The model hypothesizes that by calculating the total demand for dwt and by comparing this to the potential liquid bulk supply, the subsequent capacity utilization rate is an indicator of spot freight rates.
Political events in the Middle East may influence oil supply behaviour directly or indirectly through the alteration of the oil flow (OPEC Middle East exports of crude oil and refined petroleum products) and subsequently may cause variations in tonne-miles demand. E.g. when the UN (oil) embargo against Iraq is lifted, tanker demand may differ 387 mrd. tonne-miles, depending on whether 1 mbd of oil is exported from Ceyhan with destination Rotterdam or from AG. This represents about 4.3 % of total tanker demand (based on a total demand of 9025 mrd. (109) tonne-miles in 1993).
which again will influence spot tanker freight rates.
communities are:
previously been treated from a large tanker management perspective.
- A different empirical test of the aggregate OPEC (oil pricing) behaviour is provided.
- Although tanker movement analyses probably are available in the proprietary domain, it is unknown to the author that such an analysis is available in the public domain.
- The capacity utilization term which is a combined production based and output to capital based method, is different from what has previously been published.
Prior to the first oil crisis in 1973 the international oil industry outside USA and Canada [and former Centrally Planned Economies (CPEs)] operated under a concession system (Thuong and Elvey 1985). Petroleum concessions entitled the oil companies ownership rights over oil discoveries, thus made them in control over production, distribution and the pricing of crude oil. Even the establishment of OPEC in 1960, made the oil exporting countries powerless over these matters. The oil market was dominated by a few major players, the socalled seven sisters: British Petroleum (BP), Exxon, Gulf, Mobil, Shell, Socal and Texaco. [For a history of the concessional system and the dominance of the international oil companies, see Sampson (1975), Yergin (1991)]. Their vertically integrated operations encompassed exploration, production, distribution, shipping, refining and marketing of crude oil and refined petroleum products. Fast rising demand for petroleum products in the 1960s, gradually strengthened the bargaining power of the oil exporting countries vis-a-vis the international oil companies. In 1971 OPEC, for the first time, successfully managed to press the major oil companies into agreeing to several oil price increases. Then in 1973 OPEC (OPEC I)
their agreement with the oil companies.
terms of tonnage and vessel size.
The first oil tanker was built in 1886 with a capacity of 3.000 dwt. See table 2.
for details about historical development of tankers size.
1966 206.
| 1971 370.000 1135 om pe lag | CA 10.
Historical development of maximum tankers size. All dimentions are in feet, except dwt (Cashman 1985). Table 2.1 During the 1920s the size of oil tankers rose to about 12.000 dwt. During WW II the US government built more than 500 oil tankers with a capacity of 16.000 dwt. These tankers were sold to private operators after the war, and caused an oversupply. Consistent economic growth and subsequent growth in energy (oil) demand caused the absorption of this tonnage surplus by the mid 1950s, and shipowners started to place orders for tankers of 50.000 + dwt. The term "supertanker" was introduced with the delivery of "Tina Onassis" of 45.300 dwt, which was built in 1953 (Beth et.al. 1984).
A continuous increase in tanker demand during the period 1968 to 1973, resulted in prosperity for tanker owners. With the prevailing freight rates, tankers could be completely amortized in a few voyages from the Arabian Gulf (AG) to Europe, USA or Japan. This possibility attracted new shipowners into the tanker business. All optimism came to an abrupt end with the 1973 oil embargo. A second wave of optimism (and the contracting of new tonnage) occurred in the late 1970s, caused by freight rate increases which again were caused by the second oil crisis (OPEC II). The renewed optimism and prosperity came to an end due to the consequences of the very same oil price increases associated with OPEC II. Reduced oil consumption and higher non-OPEC production caused the (residual) demand for OPEC oil to drop from 30.6 mill. bbl/day (mbd) in 1979 to 16.0 mbd in 1985. This in turn led to reduced demand for seaborne trade, and together with increased deliveries of newbuildings in the early 1980s (which were contracted in the late 1970s), caused falling freight rates and lower secondhand ship values for tankers up through 1985.
the tanker market experienced significant gains.
The average yearly VLCC spot rates (rates for single voyages) increased from approximately 8.000 USD/day in nominal terms in 1985 for a turbine tanker from e.g. Ras Tanura to Rotterdam, to about 20.000 USD/day in nominal terms in 1990. Secondhand values for a 1975/76 built 280.000 dwt VLCC turbine tanker (TT) increased from less than USD 5 mill. in 1985 to approx. USD 25 mill. in 1990.
for a 280.000 dwt TT VLCC for the period 1985 to q3 1994.
x1.000 USD/doy, x mill.
Source: The author, based on continuous contact wilh the shipbroking community.
1975/76 built 280.000 dwt turbine tanker VLCC. Figure 2.1 initially reduced the international flow of crude oil and refined products by 4.2 mbd. This caused the VLCC spot rates from Arabian Gulf (AG) and West (North West Europe or US West Coast) to drop from 20.000 + USD/day in the June to August period, to 11.000 - 13.000 USD/day in September and October 1990. Later the market recovered. In late December 1990 and during most of 1991, VLCC spot rates were in the 25.000 - 50.000 USD/day range for turbine tanker VLCCs. During the first quarter of 1992 the tanker market dropped dramatically. Turbine tanker VLCC spot rates fell to 5.000 USD/day. Except for the periods November 1992 - January 1993 and June/July 1993, when freight rates were above 20.000 USD/day, turbine tanker spot freight rates have been approx. 10.000 (+/- 2.000) USD/day through q3 1994.
secondhand prices for early 1970s vintage VLCC to drop close to scrap value.
The world's total energy consumption was 6431.7 mtoe in 1983. See figure 2.2 for a visualization of the total world primary energy consumption for the 1983 to 1993 period. In 1983 the proportions of oil, gas and coal were 43.0 %, 20.7 % and 29.8 %, respectively. Nuclear and hydro-electricity made up 4.0 % and 2.5 % of the energy consumption. Total energy consumption had increased to 7823.7 mtoe (an increase of 16.3 %) by 1990. However, a slight shift in the distribution had taken place. The proportion of oil had dropped to 40.1 % of the energy mix, coal had decreased its market share by 1.3 %-point to 28.
the proportion of gas had increased to 22.5 %.
1964 1985.
Source: BP Statistical Review of World Energy, June 1994.
Total world primary energy consumption in mtoe.
There had also been a marked increase in the consumption of nuclear based electricity, with an increased share of energy consumption to 6.5 %. For hydro electricity the share of total consumption was practically unchanged. Total energy consumption in 1993 was unchanged from the 1990. The energy mix had also remained fairly constant. The proportions for oil, gas and coal were 40.0 %, 22.9 % and 27.4 %, respectively. Nuclear energy had increased its share by 0.6 %-point to 7.1 % .
If one excludes former CPEs from the above analysis, it is evident that a more significant shift in the energy mix has taken place. The proportion of oil has dropped significantly, while coal has increased its market share substantially, ref.
essay one in Appendix C.
[For discussions about energy demand modelling in general and oil demand modelling in particular see e.g. Allen (1981), Ang (1991), Beenstock and Wilcocks (1981), EMF (1987), EMF (1991), Fiebig (1987), Hansen (1990), IEA (1987), Kouris (1983), Huntington (1993), Mountain (1989), Seale (1991), Welsch (1989).
The increase in oil prices in 1973/1974 and 1979/1980 led to a reversal of the trend in the growth of oil consumption prevalent in the 1960s and 1970s. The total pre-OPEC II oil consumption for world excluding CPEs peaked in 1979 with an average consumption of 52.4 mbd.
45.6 mbd. It took 10 years before oil consumption had reached the 1979 level.
A closer study of the trend in oil consumption will reveal a clearer picture of the forces that have had an impact on this situation. Substitution to gas, coal and nuclear power, particularly at the expence of heavy fuel oil, was the most dominating factor leading to a fall in the consumption of oil in the USA and other OECD countries during the early 1980s.
Between 1979 and 1983, OECD oil consumption fell by 7.6 mbd or 18 %. This decline was substantial in itself, at the same time it reversed decades of near continuous growth in products demand. As can be seen from table 2.
generation. High prices made HFO uncompetitive with fuels such as coal.
Source: [FA (1989). OECD oil product consumption mix for the years 1979, 1983 and 1988. Table 2.
Generally, it has been assumed [ref. Kowalski (1988)] that the oil price increases of the 1970s may have initiated a process of increasing energy efficiency and rising fuel substitution that due to technological advances, have made them irreversible even when oil prices fall back to their original levels or below.
This price asymmetry hypothesis states that a price rise has a greater depressing effect on demand that a corresponding price fall would have in term of stimulating demand. Table 2.
price movements.
| lopwad  [powswad | ee] co gg. einn ten)
Int. bunkers (2)
Other petr.
(1) Price of crude oil.
(2) Price of HFO.
(3) Price of crude oil.
Source: [FA, Kowalski (1955).
Long term average OECD own demand price elasticities for petroleum products, defined as the percentage change in demand over the percent change in end user consumer prices unless specified otherwise.
The estimates in table 2.3 measure only the direct own price effects. The values in table 2.4 take account of many of the inter-relationships between price and demand, like; cross-price effects on substitutes and the impact on economic activity. Table 2.4 suggests that the long term response of OECD total oil demand to a change in the price of crude oil is about -0.
movement.
Source: IFA, Kowalskr (7988). Sensitivity of OECD total oil demand to a change in the price of crude oil.
The values from tables 2.3 and 2.4 suggest that 30-40 % of the reduction in oil demand resulting from higher oil prices in the 1970s, is irreversible.
Rappoport (1988).
Independent of any oil price movements, the following trends are suggested to have taken place and are likely to gain momentum in the industrialized countries: - A shift to service economies.
- Å change in the composition of industrial products from very energy-intensive products (resource-intensive) to more high-technology industries/processes (competence based).
- Continued technological advances to enable an increase in energy efficiency in all sectors of the economies when capital equipment is gradually being replaced. In this respect oil efficiency gains, defined as oil use per unit of GDP, would continue to improve.
approx. 80 in 1980 and approx. 65 in late the 1980s (IEA).
The high oil prices associated with OPEC I and OPEC II, encouraged the (high cost) producers outside OPEC to increase their exploration and production, with the result that non-OPEC (OECD, developing countries, CPE net exports, processing gains) production increased from 21.0 mbd in 1979 10 26.8 mbd in 1985. In 1994 the total non-OPEC production had reached a level of approx. 30.5 mbd.
Middle tau) | BE eT Africa *
Source: Ol & Gas Journal. December 27, 1993, Global crude oil reserves.
As a residual supplier in this market, OPEC was forced to reduce its production from 31.6 mbd (incl. NGL) in 1979 to 17.2 mbd in 1985 (incl. NGL) in order to maintain its price targets. In 1990 the total OPEC production had reached 25.1 mbd. In 1994 the total OPEC crude oil and NGL production had increased to 27.3 (25.0 + 2.3) mbd. (Basic data: IEA, Global Oil Stocks & Balances) From table 2.5 it is seen that 662.9 mrd. bbls or 65.7 % of the 1009.0 mrd. bbls of global proven crude oil reserves, are located in the Middle East. The Middle East production can be sustained at its present level for more than 100 years. OPEC countries are thus in the possession of 76.5 % of the total global crude oil reserves. Due to the uneven distribution of global crude oil reserves, it is probably inevitable that future crude oil production will be dominated by OPEC in general and OPEC Middle East producers in particular.
region is of paramount importance with respect to tanker demand.
For an elaboration of subjects covered in chapter 2, see appendix C.
decreasing spot market exposure.
how the scenario approach may be implemented into a strategic context.
One of the most crucial problems not only concerning business activities, but human existence in general, is that our knowledge and experience concerns the past, while we have to make decisions for the future. Popper (1983) called this problem "Hume's problem of tomorrow", which can briefly be described as: "How can we know that the future will be like the past?" The answer to his question is (has been) the one of inductivism. Based on an observed regularity in a (limited) number of (past) cases, it is stated that it is possible to formulate a general statement concerning the regularity in all similar cases (for the future). Related to forecasting in general, this concept of inductivism has been used when formal quantitative models have been developed and used. A solution to this problem may be the scenario approach. Scenario planning is a means of modelling the future.
incorporating uncertainty in the analysis.
In constructing a scenario, a variety of internal and external options may be considered that will encompass both qualitative and quantitative factors (Asch 1991). The art of building models suitable for scenario planning is to strike the correct balance between complexity and simplicity to reflect the real world in a meaningful way, but also to be able to communicate both the model structure and the scenario process throughout the organization. It is important to be able to develop a strong commitment to particular strategies from all members of the firm, based on a sense of being in control of an organization's future.
The scenario planning exercise should, according to Werner (1990):
- Be geared to assemble and use information residing in the collective wisdom of the firm.
- Provide for a medium for choosing risk-return preferences with which the organization is politically and culturally comfortable.
- Provide a medium for the choice of sensible hedging strategies.
- Be designed to focus attention only on core issues.
opinions actually shape the organization's plans.
In general it is difficult to say when a company should use scenario planning instead of traditional forecasting procedures.
Schoemaker (1991), the following type of conditions would favour its use:
- Uncertainty is high (relative to one's ability to predict or adjust). - Too many costly surprises have occurred in the past.
- Insufficient new opportunities are perceived and generated.
- The industry has experienced significant change or is about to.
- A common language and framework is desired, without stifling diversity. - Strong differences of opinion exist, each which has merits.
- The competitors are using scenario planning.
The Middle East (Arab) countries have experienced a significant population growth over the last decade, which may have serious social and economic consequences. One may assume that the population growth in the lower socioeconomic groups have been/are more rapid than within other groups of the population, and particularly within these former groups one may find the most rapid advancements of Islamic fundamentalism. The Arab world has never been very closely united, and the prophesies seem to indicate a further diversification rather than unity. Religious confessionalism, local nationalism, and ethnological diversification (particularly in Iraq) are factors which might destabilize these countries and further aggrevate the polarization in the Arab world. Islamic fundamentalism, in the form it was expressed during the Iranian revolution, was a strong element in the conflict between Iran and Iraq. For the other countries in the Gulf, which all have Shia-muslim population groups, this interpretation of Islam may represent a threat to their stability.
religious-political activities all over the Islamic world.
With a general high level of tension in the Middle East region and associated great uncertainty, political events may alter the flow of oil and subsequently influence aggregate tonne-miles demand.
The first to use and define the word "scenario" were probably Kahn and Wiener (1967) in their book "The Year 2000". In this publication the word scenario was defined:
"Hypothetical sequence of events constructed for the purpose of focusing attention on causal process and decision points." Their intention was that the development of scenario(s)
a conceptual tool.
Scenario planning is a relatively new planning tool. According to Linneman and Klein (1979), the first published article affording a comprehensive methodology of scenarios for corporate use was published in 1975.
the system which is under consideration.
point, and the logic which is utilized, determines the end state of the particular scenario. The end state scenario approach simply tells how the future will be at some distance in time and not how the system will manage to get there.
identified. Among the process driven scenario techniques we have:
- Development or intuitive logics [Hirschhorn (1980), SRI (1987), Huss and Honton (1987)] - Trend impact [Gordon et. al. (1974), Huss and Honton (1987)] - Cross-impact [Gordon and Hayward (1968), Fortela (1976), Sarin (1978) and (1979), De Kluyver and Maskowitz (1984), CFR (1983)] - Battelle [Oberkampf (1976), Reibnitz (1981) and (1983), Brauers and Weber (1988), Honton et. al. (1985)
The end state scenario techniques are prophecy based.
Schematic overview of different scenario techniques.
Figure 3.1 Because the intuitive logics approach is not tied to any mathematical algorithm, it can, with careful tailoring, be adjusted to the particular needs and political environment of the company. The approach assumes that business decisions are based on a complex set of relationships among e.g. economic, political and technological factors which surround the company, and as such it should be a feasible technique applicable to the tanker market.
It was emphasized that the scenario process was an important element in the planning procedure of the company.
The trend-impact method is useful because it successfully combines more traditional forecasting techniques such as time series and econometrics with qualitative factors. It forces the user to identify explicitly impacting factors, and to evaluate both their probability of occurrence and their importance. The method does not evaluate possible impacts which the events may have on each other. In addition, it is designed primarily for the evaluation of one key decision or forecast variable which is quantitative and on which historical information exists. Related specifically to the tanker market, the method would not be suitable in its pure form, eventhough it is a beginning state and process driven technique. The cross impacting consequences of e.g. any political events in the Middle East could increase and/or alter the flow of oil in the region, which could influence the price of oil, which again would have an impact on aggregate oil demand.
impact on the spot rate level for tankers.
The INTERAX (Interactive Cross-Impact Simulation) [CFR op. cit.] is a forecasting technique that uses both analytical models and human analysts to develop a better understanding of alternative future environments. This is achieved by generating scenarios one year at a time so that policy makers can interact with each scenario as it is being generated, to experiment with policy options. There are a few disadvantages to the approach, according to Huss and Honton. First, the selection of events which occur in the first interval are based solely on a random selection using the initial user-entered probabilities. There is no consideration as to whether the combination itself is likely to occur. In addition, there is little indication as to which scenarios are more or less likely. In addition, INTERAX has a high start-up cost, and most analvsts find it difficult because they are not experienced with interactive design processes. The INTERAX method requires knowledge about (Monte Carlo) simulation techniques, which is probably not of normal occurrence within a tanker company. The need for external consultants mav also alienate some of the employees. The lack of covariance in the (INTERAX) procedure could e.g. cause the breakup of OPEC simultaneously with a significant oil price increase.
Within a "normal" probability band this would be regarded as an inconsistance.
The Battelle Scenario Inputs to Corporate Strategies or BASICS approach, Honton et al (op. cit.), has several advantages, according to Huss and Honton. Firstly, it is not based on a Monte Carlo simulation approach, hence the results generale a distribution of scenarios based on their level of consistency and relative likelihood of occurrence. Secondly, BASICS is structured using both ranges of influencing variables (descriptor states) and events (uncertain events).
and editing of data as well as numerous on-line sensitivity analyses.
The major weakness of BASICS as a probabilistic forecasting tool, is that the computer algorithm generates scenarios-description(s) of a business environment as it would occur at the end of the forecast horizon. The user must be creative in incorporating time dynamics by explicitly including alternative paths in the state definitions.
From a tanker company perspective, the Battelle Method (BASICS) is probably too demanding with respect to knowledge about probabilistics. As an end state driven technique it would probably not fulfil the process driven emphasis which was accentuated in the planning process.
In the end state procedures a "prophet" has the vision of how a system will or must be in the future, and the present situation or state of the system will be judged related to this vision. Most religious and some political ideologies besides ecological disaster scenarios, fit this kind of scenario technique. A variation of the prophecy procedure is the delphi technique. Within this technique a panel of persons are consulted. Those people could come from within the company or they could be outside experts. They will be asked to describe the future state(s)
several means of processing. [See for example Linstone and Turoff (1975)].
The delphi technique has been employed to merchant shipping. Moore and Pomrehn (1971) and Frankel and Markus (1973) used the method to forecast possible dates of expected technological developments in marine transportation. Ariel (1989) performed a three round delphi exercise of the dry bulk shipping industry in the year 2000.
bulking new edible commodities.
optimal vessel for the carriage of relevant commodities. Kapoor (1987) used the delphi technique to test the hypothesized weak links which lead to the failure of the system of international trade.
actual or potensial documentary fraud.
The end state procedures will probably have to be excluded from a tanker management perspective, due to the fact that they lack the process orientation.
the Middle East and possible consequences.
to the tanker market, was the Royal Dutch/Shell group in the early 1970's.
fragments of their experience had been available in the public domain before Wack (1985a), (1985b) published two articles in Harvard Business Review. Shell was dissatisfied with traditional planning techniques, but was aware of, or had the perception that no single "right" projection could be deduced from past history or behaviour. The perception was that one had to accept uncertainty, try to understand it, and implement it as an integrated part of the planning process. In Shell'
uncertainties, but the Shell group wanted to go further.
Prior to 1970 the Shell group was mainly concerned with physical planning, e.g. expansion of production capacity, building tankers, refineries etc.
considerations were only important on a project basis.
In 1965, as an extension of their regular planning, the Shell group undertook an experimental planning study to the year 2000, primarily because of the long lead time associated with oil field developments.
"predetermined elements" and (obvious) uncertainties.
The existing planning system at Shell at that time, the "Unified Planning Machinery" which provided planning details for all activities from production through refining and marketing, was not a suitable instrument to provide realistic planning assumptions. Therefore, in 1971, they decided to apply the scenario approach as a better framework for considering the future.
The scenarios provided a wide span of possible futures, each scenario was internally consistent, but no strategic thinking or action could be taken from the material (scenarios).
"So what?".
scenarios.
In the next generation of scenarios the Shell planners took a closer look at the principal actors in Shell's business environment; the oil producers, consumers and other oil companies.
revenues.
annual increments in import requirements. Shell also undertook the task of analyzing political aspects related to the oil market.
faced with a possible supply disruption (higher anxiety level).
After this initial analysis of hard and soft (political) data, they tried to expand the number of elements which were predetermined and what remained uncertain.
They gained the knowledge that every manager has a mental model of the world from which people act according to their experience and knowledge. If managerial behaviour should change, Shell would have to change the corporate climate.
and change them whenever necessary.
Later, when preparing for the 1973 scenarios, Shell regarded or viewed a supply disruption or a discontinuity as predetermined. The planners saw a very tight supply/demand situation, and that producers would take advantage of this situation.
They proceeded by incorporating a disruption into a surprise-free scenario. In addition to this principal scenario, they also constructed two "phantom" scenarios. In phantom scenario I, they assumed a delay of 5 years from the onset of a disruption, and in phantom scenario II they assumed a delay of 15 years. These phantom scenarios where used to measure the "regret"
which could summarize the anticipated business environment.
Figure 3.2 provides an overview of this model.
shown on the left and the dicontinuities are in the middle.
A conceptual framework of a new worldview, Wack (1985a).
Figure 3.2 Alternative fuels, which they anticipated only could be developed very slowly, and would not be available at least until the 1980's.
political, internal and physical incidents.
To communicate the right message they borrowed the concept of archetypes. They constructed some government archetype responses.
intervention (dirigiste) approach.
The arrows on the right side of figure 3.2 indicated the implications they wanted to underline. To those (of the Shell group) involved in exploration and production, they pointed out that they could lose some of their concessions and mineral rents.
Those involved in refining and marketing, were told that they could soon be in a low growth industry.
decision-making would have to be decentralized.
The Shell approach to scenario planning was clearly a process driven technique, and it is beginning state driven. The procedure is a developmental or intuitive logics variant. As mentioned, the basic principle of the Shell approach was to identify (likely)
obvious uncertainties.
One of the objectives was lo provide a conceptual framework for analysizing and understanding the market for large tankers by the majority of the individuals within the managerial ranks within a tanker company. Together with Asch' (Asch op. cit.) claim that one has to strike the right balance between complexity and simplicity so both model structure and the actual scenario process can be communicated throughout the organization, probably calls for a less sophisticated approach than what is technically available. Royal Dutch Shell has apparently had success with a beginning state and process driven developmental technique. Based on this experience and the emphasis on participation in the scenario process, the end state techniques and the Batelle method, which is end state driven, have to be excluded. At the same time the cross-impact technique has, in its pure form, to be ruled out because it requires the help of outside experts.
The following general analytical beginning-state-driven developmental heuristic scenario procedure with some trend-impact elements is suggested for the analysis of the tanker market, with emphasis on the OPEC Middle East supply situation:
1. Define the scope of the analysis. 2. Based on assumptions on:
- international energy markets - international policy and price influences on energy supply and demand with particular reference to oil (refined petroleum products), national or regional sector (or aggregate) oil demand projections are made. If a sectoral analysis is performed (before aggregation)
investigated:
products in other context than energy should be studied.
The techniques which can be applied (for the different sectors) are:
- econometrics (link to macro economic variables)
3. Forecast of non-OPEC oil supply, where above analytical methods may be applied.
demand for OPEC oil is derived.
5. Based on the (simple) model which is developed in chapters 5 and 8 with the production function of chapters 4 and 7, all key market variables are assumed identified. Basic assumptions related 10 these key parameters are stated.
One may assign probabilities to possible various impacting events by (inhouse)
delphi surveys.
The volatile nature of the Middle East region; politically - oil market wise, and subsequent impact on the tanker market, are all elements which may encourage an analytical approach with some scenario elements.
emphasis on the OPEC Middle East situation.
strong commitment throughout the organization. The outlined scheme contains a synthesis of various available scenario techniques, with a tailoring to the tanker market (and an emphasis on the Middle East). It is purposefully geperal, so it may be applied in various analytical applications. At the same time the outlined procedure may be interpreted as a managerial superstructure of the dissertation of which the various parts fit together. All the mentioned scenario techniques, including the proposed generalized scenario procedure for the tanker market, are very normative in their nature. The fact that the outlined analytical framework is not tied to any particular mathematical algorithm and that it represents little or no probabilistic or simulation features, may also be regarded as negative elements.
of an organization.
In the chapters to follow the various elements of the scheme are analyzed, both theoretically and empirically. In addition, possible (tanker demand) consequences due to events in the Middle East are outlined. For further research, it may be appropriate to incorporate political risk elements [e.g. Hibbs (1973), Kennedy (1984)], within the analytical framework of the (scenario)
Scenarios basically serve two purposes. The first is protective: to anticipate and understand risk. The second is entrepreneurial:
which one was previously unaware.
As far as the number of scenarios are concerned, one should probably never include three scenarios describing alternative outcomes, because most managers cannot resist the temptation to identify the middle scenario as a baseline. One should either develop two scenarios or four or more.
"histories of the future" are enough.
The most important element when developing scenarios, is that each of them has to be internally consistent. Also, the range of the scenarios should be near the extremes of possibility, but not beyond the realms of probability.
them of important events that subsequently happened.
The development of scenarios can be intellectually interesting and may provide people with a broader horizon.
Figure 3.3, partly based on Limhuis (1985), describes an outline of a strategic decision method involving the use of a strategic method based on scenarios. The right side of figure 3.3 deals with the long term objectives or goals. Different options or strategies can be derived based on these goals. Furthermore, a set of criteria is established from which it is possible to choose between the strategies.
The left side of figure 3.3 covers the company's business environment. The next step is to develop different scenarios (which are independent of the various projects, if the company is diversified or represents a conglomerate). [Key variables which have the greatest impact on the different projects are identified.
Expected income from the various projects can be calculated.
Strategic decision method involving the use of scenarios.
Expected income from the various projects within alternative strategies for the different scenarios, can be calculated e.g. based on net present value.
attractiveness etc.
Scenario/payoff matrix.
Figure 3.4 4.
This chapter provides an understanding of the philosophy behind tanker demand, by discussing theories concerning behavioural aspects related to the OPEC oil supply. The empirical validity of several alternative hypotheses about OPEC oil supply behaviour are also examined.
In this thesis a part of the OPEC oil supply, the OPEC Middle East exports of crude oil and refined petroleum products, will be established and related to aggregate tanker demand by a production function. The same order of sequence is used in the chapter.
production functions is tested in chapter 7.
Several different theoretical approaches describing the oil market and the role of OPEC can be identified. At the same time the angles from which the oil market is viewed are quite different. Some interpret OPEC as an organization with a monopolistic grip of the market.
competitive free market, an oligopoly or a cartel.
For a different approach see the interesting discussion by Mabro (1992).
In a competitive market, according to the Hotelling Rule [Hotelling (1931)], the difference between the price of oil and the marginal production cost (ie. marginal profit) must grow with time al a rate equal to the discount rate used by the oil producers.
For later works supporting this paradigm, see Miller and Upton (1985), Starrett (1987).
Roumasset et.al. argue that while efficiency prices were high in the 1970s relative to extraction costs, it is plausible that average monopoly profits were negligible.
return of real interest rates to their historic levels.
In early 1982, even spot prices, already below official prices, were substantially above the estimated efficiency or competitive price level. On the other hand, efficiency prices remained far above extraction costs, they further argue that even if the price-setting power of OPEC should be eroded (even more)
Adelman (1990), (1993) argues that the total mineral stock in the earth is an irrelevant constraint. It is a geological fact of no economic interest. In Adelman's view it is all about flows from unknown resources into a reserve of inventory. At the same time there are reasons to believe that reserve replenishment shows diminishing returns over time, but the larger deposits would be found earlier by chance. Once found, the better mineral would be developed first , thus marginal costs and prices would rise, even if ultimate depletion were infinitely distant. He further argues that a higher discount rate would make depletion more desirable but less accessible, and that a worldwide stability of development cost shows that oil has not become more scarce since 1955. The rate of interest has little net effect upon the optimal rate of reservoir depletion. Competitive mineral markets do not resemble monopolized markets.
would under competition have increased depletion, monopoly curtailed it.
Although economic wealth is important for nations, it is not the sole factor when undertaking decisions. It seems likely that nations are concerned with extending their political influences, assuring security as well as maximizing their wealth (from oil reserves as far as OPEC and OPEC member countries are concerned).
political models or incorporating political factors of OPEC behaviour.
Even though wealth maximization merely serves as a surrogate for security and power goals, the prediction of these models [e.g. Aperjis (1982)] should be accurale. Since wealth maximizing behaviour does involve an empirically measurable phenomenon, and economic theory has isolated the factors influencing choice, these models should provide explicit interpretations of the present and predictions of the future. In contrast, when introducing security or political influence, the models become more qualitative than quantitative, Griffin and Teece (1982).
Related to political aspects vs. economics as basis for OPEC decision-making, Moran (1982) argues that political and security concerns "wag the economic tail and where they have conflicted, the former have to prevail". He argues that Saudi Arabia's wealth maximizing price path is in practice an empirically elusive concept and of dubious predictive value. He further argues that the evolution of world oil markets defines the limits within which Saudi Arabia can exercise her considerable discretion on price matters.
political priorities while minimizing internal and external pressure.
The fundamental assumption within the political models is that economic factors exert limits on bounds within which political factors dominate, and that these bounds are so large that they suggest wealth maximizing models are of little value.
realities, Aperjis (1982).
OPEC as a multiplant monopolist.
Figure 4.1 Ås indicated in figure 4.1, the marginal cost curve (MC) could be derived as a horizontal summation of the individual MC-curves of the different OPEC member countries.
The demand curve (D) is the aggregate demand for oil. From economic theory the optimum point for a profit maximizing monopoly will be the intersection between Marginal Revenue (MR) and Marginal Cost (MC). The monopoly price and quantity are P* and X*, respectively.
A cartel acting as a monopolist.
Figure 4.2 A problem for cartels in general is the distribution of the total production among the individual cartel members.
From the theory for multiplant monopolies, the optimal point of allocating resources within a cartel is where the marginal cost (of the last unit produced) of the individual members are equal, and equal to the MR (of the last unit sold) from the cartel. Figure 4.2 indicates this graphically.
The MC curve represents the horizontal summation of the MC curves of the individual member countries.
between the MC and MR curves, represents the common MC level.
The distribution of the total (OPEC) production and associated revenue among the individual cartel members, is not necessarily the best for the individual members. The distribution of the monopoly profit based on the distribution of production might provide some of the individual member countries with a lesser profit than a competitive free market would have done.
difference in production costs for the different producers.
With the monopolization of a particular market, it is widely believed that aggregate quantity offered will decrease with increasing price, contrary to a competitive free market. It is reasonable to believe that this effect is applicable or related to a monopolization of an oligopolistic market. This reduction in output will, when the allocation of resources within the cartel is at an optimum, cause the producers with the highest production costs to reduce their production comparatively more than the producers with lower production costs. A solution to this problem has in economic theory been called lump sum side payment.
cartel members.
Mead (1978) and Johany (1978), argue that the oil market is a competitive market. The price level which existed in the 1970s reflected the long term production costs.
Johany argues that the price level before 1973/1974 was the result of the major oil companies (Majors) use of a comparatively larger discount factor because they feared nationalization of their oil involvements, particularly in the Middle East.
lower price.
The price of crude oil increased in the early 1970s because of the nationalization, and that the oil producing countries (in the Middle East) used a lower discount rate. The reason for this lower discount rate should be the lower capacity of absorbing oil revenues.
Johany's property rights model (applied to OPEC I) is challenged by Adelman (1982): "When the Arab countries cut production during the so-called "embargo"
itself tightening of production schedules implicit in the low discount theories."
Intuitively the introduction of a backward bending supply curve for the oil market could be viewed as a theoretical curiosity. It has found some application in labour economics and currency supply, but it might also have some application to production and export of exhaustible resources (crude oil)
developing countries where export of oil is the dominant industry, Teece (1982).
Cremer and Salehi-Isfahani (1980) argued that rising oil prices and production cutbacks in the 1970s, were the result of each exporting country faced a backward bending supply curve. The basic assumption for this theory is that there is a (approximate) competitive oil market, and OPEC as an organization is only acting as an "information bureau" for its individual members.
Also, it is assumed that the countries involved (OPEC countries) have limited absorptive capacity, and that investments abroad are irrelevant. It might be argued (hat the major OPEC countries (producers)
production goals that will reach these targets.
Do (elastic demand)
D1 (inelastic demand)
World supply and demand with a backward bending supply curve. Figure 4.3 constructed showing different price/quantity combinations. This isorevenue curve also represents the country's supply curve.
With near to parallelism between the supply and demand curve, an increase in demand will result in a large price increase. Subsequently, a decrease in demand will generate a large decrease in price.
This target revenue approach implies a backward bending supply curve for prices above those needed to support the target revenue. For a stationary isorevenue curve, a price increase will result in a reduction in production.
aggregated supply curve will correspond in shape.
Figure 4.3 indicates both an elastic - and inelastic demand curve. For an inelastic demand curve the price might be unstable in the range where the supply curve is backward bending, because at deviations from an equilibrium state forces will tend to pull into another equilibrium state.
a stable equilibrium.
Generally speaking, a dominant firm model of a market is characterized by one large producer which has enough market power to act as a price setter.
(small) producers/suppliers.
balance its output according to the current supply and demand situation.
utilization (as long as they are not cooperating with the dominant firm).
Figure 4.4 describes such an oligopolistic model of the oil market. D is the total aggregate demand for oil.
OPEC producing countries, including net export from former CPEs.
MCQPEC is the (average) marginal cost curve for OPEC.
curve is entirely lower than the non-OPEC supply curve.
'When the aggregate demand and the non-OPEC curves are known, the (residual) demand curve for OPEC can be established.
If the oil price is less than P1 there would be no non-OPEC supply and the aggregate demand curve will be identical (o the demand curve for OPEC oil. At a price level equal to P2, the aggregate demand would be provided by the non-OPEC producers.
For an oil price between P1 and P2, there would be a demand for both OPEC and non-OPEC.
The curve between a and b defines the demand for OPEC oil. MR is the associated marginal revenue curve [to the (OPEC)
curve].
OPEC would produce a quantity which would equal MR and MC. In figure 4.4 this is labelled Q*. The associated price is labelled P%.
In this situation there is a non-OPEC demand equal to QN-QPECNN Dagg.
OPEC as an oligopolistic dominant firm.
A mathematical quantification of the model outlined in figure 4.
structured as follows:
T Max Z 7 OPEC/(1+r)! (4.1)
'Which represents a maximization of net present value (NPV). Subject to the following constraint:
Z gOPEC = QOPEC (4.2) t=1 7 QPEC = revenue in period t = p(t) DopgEC(Y) - c(t) DopEC(t)
The solution to eq. 4.1 would be:
MRopec (1) = MCopec + s(1+r)! (4.3) € = shadow price (represents an increase in maximum value of the criterion function when the constraints are increased by one unit).
The subsequent price(s) is p*
OPEC oil is not derived (producing at or close to capacity limits).
Max X [P" (t) Capi(t) - Ci(t)V(1+r)! (4.4)
Which represents a maximization of NPV.
Subject to the constraint:
Tj 2 Capj(t) = total reserves for a particular (4.5)
Capj(t) = production (capacity)
non-OPEC country for a particular period of time.
Ci(t)
r = discount factor (for a particular country) Pt = MC; +ej(1+r)! (4.5)
Where g;(1+r)!
There are ways lo sophisticate (he dominant firm model by e.g.
OPEC into several subcategories according to their absorptive capacity.
In this way OPEC is viewed as a non-uniform cartel where the countries with large populations need larger oil revenues to finance (relatively large) development projects (high absorbers), and other countries will accumulate financial surpluses because (heir economies can not absorb all the oil revenues (low or lower absorbers).
a higher discount rate than the low or lower absorbers to their oil reserves.
The three categories into which OPEC can be divided are the following: Category I, the low absorptive countries, as grouped by, Teece (1982):
Category II, the moderate absorptive countries:
Category III, the high absorptive countries:
Gabon (and Ecuador) is (are) omitted because it is (they are) rather insignificant as OPEC producer(s).
In this way OPEC could be divided according to the Stackelberg model assuming that Group I (and II) dominates Group III.
III will be price taker and quantity setter.
OPEC as a dominant firm within an oligopolistic market framework.
In the mid to late 1980s it has been observed that Mexico, Egypt and Norway have restricted their output as å support towards OPEC. To introduce some non-OPEC nations as "semi OPEC countries"
will only add to the number of maximizing problems in the described model.
A way to extend the Stackelberg model in case of a conflict between the different OPEC groups, is to introduce game theory.
A conflict may arise when the low absorbing group is not willing to be quantity followers, and/or the high absorbing group is not willing to be price takers. A conflict of this kind can be resolved by the introduction of for example the Nash solution to cooperative games, Nash (1953), Aperjis (1982).
The competitive equilibrium (or threat point) will be the worst possible case for the different OPEC groups. This will be the case if each group maximizes ils profit, Wi.
I Wi=Z [p(D; - Ci(OV(1+r)! (4.6)
i= LIL (IM)
In figure 4.5 this situation is represented by the point TP (threat point).
agreed to maximize the expression:
W = ØW1 + (1-Ø)Wi 0=<@=<1 (4.7)
Where W is the weighted sum of the groups individual profits.
Pareto optimal frontier for a two group cartel.
Equation 4.7 is an expression for an agreement to maximize the weighted average of the profit for the two (three) groups.
For each value of Ø there exists a sequence of prices p(t) and quantities which maximizes W.
indicated in figure 4.
on the Pareto optimal frontier, N(WJ2, Wj2), which maximizes: Max A = (Win - WIP) (Win - wy IP) (4.8) Subject to:
Where WIP and WIP are the coordinates for the threat point; TPW IP. wyp TP).
among the players (OPEC groups).
The most widely accepted explanation of OPEC I (the oil price increase of 1973/74) among economists, is that OPEC cartellized the market to rise prices above competitive levels by restricting production. But this view has been increasingly challenged. During OPEC II (1979/1980) some argued that OPEC exploited the Iranian disruption to extract greater profits by tightening a market with low short term price elasticities. But more people started to favour the view that OPEC was irrelevant as an organization.
short term demand elasticities.
An interesting event which occurred in January 1979 was that Saudi Arabia cut its production. Adelman (1982) interpreted this behaviour in the following way: "The Iranian revolution is generally considered as the cause for the price jump of 1979-80, from about 12 $/bbl to about 32 $/bbl. But this cannot possibly be drue prices again rose in January, to not quite 20 $/bbl.
Then on January 20, 1979 - a day to remember - Saudi Arabia cut production from 10.4 mbd to 8.0 mbd.… by mid-February the price had jumped to over 31 $/bbl Saudi Arabia "led the regiment from behind", keeping its own official price usually $2 or so below the price for equivalent crudes sold by others...... Saudi actions speak louder than words. Their 1979 output cutbacks drove the price up to $32 from $12."
This view is consistent with "a cartel with a dominant firm"
with Saudi Arabia as a price setter and acting like a "swing producer".
Within the OPEC quota system the different OPEC member countries have been producing at or above their assigned production levels. Only Saudi Arabia, especially in 1985, has been producing less than her quota to balance the aggregated OPEC supply according to OPEC residual demand (at a particular price level) when the OPEC quota as a whole has been in excess of the residual demand for OPEC oil (at a particular price level).
that a Stackelberg Model can be applied within OPEC.
Moran (1982) is sophisticating Adelman's view by introducing political considerations. "(Saudi Arabia)
Palestinian sabotage against Saudi oil facilities......
With the shock of the Shah's departure.... and uncertainty about US dependability, Saudi leaders showed extreme reluctance to offend either the new regime in Iran or the newly preeminent Iraq..... While there is no certain explanation for Saudi behaviour from January to July, it seems apparent that the Saudi leadership could not or would not build the consensus necessary for an oil policy that would deny higher spot market premiums to its neighbours......
deprive them of markets, except for the highest political stakes."
Up to 1985 most empirical studies on OPEC mostly assumed that it was an effective cartel; Cremer and Weitzman (1976), Danielsen (1980), Ezzati (1976), Hnyilicza and Pindyck (1976) and Moran (1978). Loderer (1985) argues the policy decisions of an effective cartel affect the spot prices for oil. This hypothesis is tested by examining the correlation between OPEC policy changes and changes in spot prices for oil during the period 1974 through 1983.
finding of no correlation is argued to be consistent with a competitive oil market.
Loderer finds that there is no significant relationship between OPEC policy changes and spot oil prices during the period 1974 through 1980, but finds a significant relationship for the years 1981-1983. He concludes that the evidence is consistent with the notion that OPEC was an effective cartel during the latter years but not during the period 1974-1980, which may be contrary to conventional wisdom. Lowinger et. al. (1986) assumed that OPEC seeks to maximize the present value of its consumption, subject to the demand, OPEC's reserves, Non-OPEC supply, the expected growth in world GDP and the world interest rate.
of goods or for the acquisition of financial assets in the world capital markets.
Alternatively, OPEC may borrow in world financial markets for consumption and investment in real assets and thereby forgo current production of oil. Their findings seemed that from 1974 to 1979 OPEC did not adjust prices to correspond to changing economic conditions, but beginning in 1979 the oil prices and OPEC behaviour has adjusted, though not fully to changes in economic conditions. Geroski et. al. (1987) assumed that collusion within cartels is rarely perfect, and they allowed current OPEC behaviour to vary in response to previous actions. They captured this by following the coefficients of cooperation approach introduced by Cyert and de Groot (1973), in which producers are modelled as if they act non-cooperatively, but attach some weight in their objective function to the profits of other producers.
explaining oil price dynamics for the 1969 to 1981 period.
Griffin (1985) first tested the empirical validity of several alternative hypotheses about (he oil production behaviour of the individual OPEC member countries. Although Griffins' sample period, primarily from 1971:1 to 1983:3, contains both upward and downward price fluctuations, the overall trend was one of steadily rising real oil prices.
Later, Jones (1990) conducted a similar analysis based on time series from 1983:4 to 1988:4. This was a time period of basically falling oil prices.
production models:
linear production equation: InQy = 04 + PjlnQOy + yilnP; + Sj (4.9)
QU; = the aggregate oil production coming from the other (n-1) OPEC countries Bi = the elasticity of oil production with respect to other OPEC members'
aggregate oil output Y;
Griffin'
model:
- constant market sharing (y; = 0 and ØB; = 1) - market sharing (y;>O0 and f; = 1) - partial market sharing (y;>= 0 or y; < 0, and PB; >= 0)
The constant market sharing model implies that all OPEC members share equiproportionately in production cutbacks and increases, regardless of price. The market sharing model allows the price to affect the individual members' market shares.
responsiveness to price.
Griffin found that the constant market sharing model could only be supported for one OPEC member (Qatar), the market sharing model was supported by 5 of the 11 OPEC countries. Due to data deficiencies for Ecuador and Gabon, only 11 of 13 OPEC countries were examined. The partial market sharing model was supported by all 11 OPEC countries. The study found that Saudi Arabia appears to vary production in concert with other OPEC countries. This result contradicts dominant firm models where Saudi Arabia would act as the market leader and vary production inversely to the competitive output levels of the other producers (including the rest of OPEC). Based on the evidence, OPEC appeared (for the time period in question) to be a real cartel with at least a partial effective output coordination. It was not possible to test Moran's security maximization model directly, but Griffins' results indicate that (up through 1983:3) OPEC was much more than Saudi Arabia.
The property rights and the target revenue models did not have much empirical evidence. Re-estimation of these two models by Jones, over the 1983:4 - 1988:4 period, yielded results very similar to Griffin's. In addition, according to Jones, both theories depend on some very dubious assumptions.
Also, Linderoth (1992)
supply curve.
For the target revenue model, the assumption that OPEC would shun foreign investment opportunities is inconsistent with their willingness to invest their surplus oil revenues abroad, nearly USD 400 mrd. in the 1974 to 1983 period (Mattione 1985).
been questioned.
(1971:1- (1983:4-1983:3) 1988:4) Griffin (1985)
Comparison of alternative hypotheses tests for OPEC countries under rising and falling oil prices. Table 4.
Jones' findings strongly agreed with those of Griffin, particularly with regard to the three cartel variants. Only ome of the 11 OPEC countries' oil production behaviour appeared to support the stricter constant market sharing model, but this time it was Saudi Arabia and not Qatar. Four of the 11 OPEC countries'
but Iraq were found to support the partial market sharing hypothesis.
The result for Saudi Arabia is interesting, because it gives some insight into how its role in the cartel may have changed. In late 1985 Saudi Arabia introduced netback pricing. Netback pricing is the sale of crude oil at å price determined by the market price of refined petroleum products, and thereby the producer can sell some or conceivably all of his quota without price competition at the crude oil level. It automatically matches any rival's lower crude oil prices, which are speedily translated into lower product prices. Netback pricing subverted the cartel discipline in 1986 ("OPEC III") and caused oil prices to drop to 7-8 USD/bbl for OPEC marker crudes, according to Adelman (1990). The Saudis used it only as a last resort, to force their partners back into line.
Saudi Arabia wanted to rule out its role as guardian of OPEC policy.
than in Griffins sample, only being rejected for Kuwait and UAE.
In summary, the results of Jones supported Griffins conclusions regarding the empirical validity of alternative hypotheses about OPEC behaviour appeared to hold.
observed OPEC production behaviour than any of the alternatives.
Later, Dahl and Yucel (1991) tested competing hypotheses for both OPEC and Non-OPEC producers, based on more recently developed cost data. They found no evidence of dynamic optimization. Formal target revenue models were rejected, but they found some evidence that revenue largeting could have influenced production for some OPEC countries and a few Non-OPEC countries.
in a competitive manner.
They were unable to find formal evidence of coordination in the form of strict cartel behaviour or swing production among OPEC countries.
behaviour. The time series used, cover the period from 1971 to 1987.
It is interesting to notice that Adelman (1990) interprets the oil price shock in 1990 as a collusive act ("OPEC IV").
other OPEC countries to explain the final price jumps.
Two distinct paradigms dominate world oil market modelling; Intertemporal optimization and behavioural simulation (or recursive simulation), according to Powell (1990). Intertemporal optimization describes a model of decision making in which economic agents attempt to maximize some measure of wealth or utility. In natural resource modeling this assumes that the owner of a depletable natural resource would choose a production plan as to maximise the present value of the net return from the sale of the resource. This approach assumes perfect knowledge, perfect foresight, and an optimization motive.
To apply this concept to the world oil market, would require the modeller to decide how to model the decisions made by OPEC, non-OPEC oil producers, and the consumers of oil.
for the optimizing agents.
Å consequence of this reliance on equilibrium solutions, is that the typical price and quantity paths resulting from an optimization model are smooth and monotone over time. Another notable feature is that the solutions to optimizing models is that they typically do not generate current prices and quantities in the market as a starting point.
There are several obvious serious drawbacks related to the intertemporal optimization approach. The assumption of perfect knowledge and foresight appear unrealistic of human decision making. Also, the solutions are strongly influenced by the future cost of oil substitutes and the discount rate(s) of the decision makers. By focusing on equilibria, the models do not provide information on how the market evolve in the short term from a position of disequilibrium.
Optimization models have difficulty explaining the behaviour of oil markets over the last decades, and with reference to the empirical results of Griffin and Jones, any revenue or profit maximization behaviour of OPEC has not been evident. The second major paradigm for world oil markets is the behavioural simulation paradigm. The behavioural simulation approach has several advantages. Because they are solved forward in time recursively, they automatically begin with present prices and quantities. Secondly, as disequilibrium models, they offer a prediction of how today's disequilibrium will evolve in the future.
The dominant behavioural simulation model of OPEC is the Target Capacity-Utilization Model (TCU). The TCU is a simple behavioural rule that links OPEC's price with two other variables; OPEC production and OPEC capacity. Seven out of the ten models included in the Energy Modelling Forum, EMF (1982), used some version of the TCU model.
Pindyck (1982) made some general remarks to the EMF study: "The Energy Modelling study found considerable differences in the forecasts for oil prices produced by these various models. These differences were partly a function of the assumptions used regarding price responsiveness of non-OPEC production and world oil demand. Clearly there are differences of opinion regarding these empirical assumptions, and that alone will imply differences of opinion regarding future path of oil prices.
It seems to me that from a theoretical point of view, models of OPEC oil pricing have reached a practical limit as tools of analysis. As far as empirical predictions of oil prices are concerned, some of these models have clearly exceeded that limit. The problem is a simple one. The real world is not as rational and dynamic as economists would like to believe.
economic agents."
The TCU model is based on two basic assumptions; OPEC is the residual supplier of oil in the world oil market, and the organization sets the price of oil based on the gap between the current capacity utilization and some target level of capacity utilization.
Powell examined the empirical basis for the TCU model and studied its performance in a simple model of the world market. He examined the empirical relationship itself and uncovered a number of problems. Firstly, the market had not followed the Energy Information Agency, EIA (1984), curve since 1984. Secondly, the definition and measurement of capacity is a matter of considerable controversy, and the strength of the price changes-capacity utilization relationship depends heavily on which definition one uses. His conclusion is that both the empirical and theoretical support for the TCU model is weak.
TCU model does not achieve a particular desirable outcome for OPEC.
Based on the discussed empirical studies, within this dissertation a cartel behaviour is assumed for OPEC, in the sense thal (he organizalion is (he residual supplier of oil, and that the group supplies the difference between world oil demand and non-OPEC supply. An alternative empirical test of the OPEC cartel theory is shown in the empirical part of lls thesis, where the od price is dependent on lhe disequilibrium between a largel price and a delined level of residual OPEC demand, and OPEC's ability (or behaviour) lo produce an amount of oil equal lo this defined level of residual OPEC supply.
downward price fluctuations.
The demand for tanker freight services, expressed in tonne-miles, (total seaborne volume (mass) of oil traded multiplied by the total sea distance), represents the volumes of seaborne trade with crude oil and refined petroleum products. In this respect it represents both the level and structure of the world economic activity. In theory, demand is inversely influenced by the freight rates.
trade distances.
The purpose of the (empirical) analysis to follow, is to provide a correlation of the two oil flow concepts; international trade of crude oil and refined petroleum products and (OPEC) Middle East exports.
justification for stating the hypothesis about the production function.
Sources: BP Statistical Review of Word Energy-various Issues, OPEC Statistical Bulletin 1989 based on direct communications lo lhe OPEC Secretariat, UN Energy Statistics Yearbook, National sources, OECD Quarterly Ol & Gas Statistics.
International trade with crude oil and refined petroleum products vs.
OPEC Middle East exports of crude oil and refined petroleum products. Figure 4.
Figure 4.6 shows a graph of international trade with crude oil and refined petroleum products versus Middle East exports and OPEC Middle East exports. The difference (in volume) between the two supply groups are the following petroleum exporting countries; Bahrain, Oman, Syria, and Yemen.
In volume terms this group exported in 1989 0.76 mbd or 6 % of the crude oil and refined petroleum products exports of the OPEC Middle East producers.
To test hypotheses about empirical and/or causal relationships, a standard multiple regression technique like the ordinary least squares estimators method (OLS) with standard adequacy checking, has been used throughout the dissertation, because it represents the most widely used econometric procedure. For further references, see e.g. Montgomery and Peck (1982), Johnston (1984) and Appendix A.
The following is an OLS of internationally traded volumes of crude oil and refined petroleum products vs. Middle East exports and OPEC Middle East exports.
period. For actual data, see appendix at the end of this chapter.
The first relationship:
Y=a1*El +) (4.10)
Y = International trade with crude oil and refined petroleum products (mbd)
El = Middle East exports (crude oil and refined petroleum products) (mbd)
I 0.901 13.63 0.
| R2 = 0.935 F-test(1,13)= 186 | DW = 0.
Table 4.2 With reference to table 4.2, all parameters are significant (5 % significance level)
residuals. The second relationship: Y=01*E2 +a) (4.11)
E2 = OPEC Middle East exports (crude oil and refined petroleum products) (mbd)
| FFE sj 0.931 F-tesi(1,13)= 176] DW = 0.
With reference to table 4.
DW statistics is inconclusive with respect to autocorrelation.
Both the Middle East exports and the OPEC Middle East exports terms are highly correlated to the flow term;
petroleum products.
In e.g. existing econometric models like Beenstock and Vergottis (1989b), demand is considered to be completely inelastic with respect to freight rates and therefore it is assumed to be exogenously determined. In Strandenes (1986)
(GDP) and freight rates.
For the time period covered by the empirical analysis (q1 1987 to q4 1989), the costs of transporting one tonne of oil from the Middle East to North-West Europe (NWE), have been in the range 4.4 $/tonne of oil (q1 1987) to 10.2 $/tonne (q4 1988). Compared to e.g. the price of the crude oil quality West Texas Intermediate (WTI), the transportation costs represent approximately 3 % [based on an average WTI price in 1987 of 19.2 (nominal) $/bbl (FOB)] to 8.7 % [based on an average WTI price in 1988 of 16.0 (nominal) $/bbl (FOB)].
The above mentioned transportation costs relate to FOB prices. The end user prices within OECD constitute a tax element which vary substantially. For some European countries, petroleum taxes vary from less than 10 % on heavy fuel oil up to several hundred percent on gasoline.
a few percentage points.
miles demand) is inelastic wilh respect to freight rates. The aggregate fonne-miles demand (Draf)
as 2 Junction of OPEC Middle Fast petroleum exporis (SOPEC - MP) The following production function is hypothesized: Dry = al *SopEc - ME + 22 (4.12)
The OPEC Middle East oe exports quantity is a derived variable.
an analytical point of view ihe demand for OPEC oil (SopEC)
S OPEC = Dagg. - Snon-OPEC +- stocks movements (4.13)
supply (SOPEC, non-ME) and OPEC Middle East consumption (DQPEC-ME)
SOPEC-ME = SOPEC - SOPEC non-ME - DOPEC-ME (4.14)
For a discussion of total OPEC and OPEC Middle East production levels and capacities see chapter 9. For an analysis of DOPEC-MF.
of paragraph 3.3 may be applied.
The production function (eg. 4.12)
utilization, which will be developed in chapier 5.
products OPEC Middle East Exports (crude oil and refined petroleum products) in mbd. Source(s): OPEC Statistical Bulletin 1989, based on direct communications lo the OPEC secretaria, UN Energy Statistics Yearbook, National sources, OECD Quarterly Oil & Gas Statistics.
Middle East exports (crude oil and refined petroleum products) in mbd. Sources: BP Statistical Review of World Energy. varrous sues.
International trade with crude oil and refined petroleum products.
source as above.
Table ] App.Ch. 4 5.
Chapter 5 represents the last part of the theoretical section of the dissertation. Up to this point the managerial framework for analyzing the supply of oil from the Middle East has been outlined by a generalized analytical framework. The philosophy behind tanker demand, OPEC (Middle East) oil supply behaviour, has been investigated both from a theoretical and (published) empirical point of view. A cartel behaviour for OPEC was concluded, and chapter 7 will provide an alternative analysis by the author of testing the OPEC cartel hypothesis. Chapter 4 ended by hypothesizing a production or demand function linking aggregate tanker demand to OPEC Middle East petroleum exports.
(stated) production function of chapter 4.
The chapter is concluded by relating the developed capacity utilization term to spot freight rates for VLCCs, and the development of a simple analytical model for the tanker market.
In the literature on capacity utilization. the distinction is made between intended and unintended idle capacity. Intended idle capacity is the result of decisions by firms at the investment stage to allow for some excess capacity in anticipation of variations in demand. Unintended idle capacity occurs after the investment has been made, and the company is forced to reduce their output in response to changes in demand. In instances one may imagine that shortage of (imported) raw materials or any other supply input variable may cause idleness of installed capacity [Berndt and Hesse (1986), DeLeeuw (1979), DeLeeuw (1962), Klein and Jong (1973)].
In measuring capacity utilization one uses the aggregate of both inputs and outputs of all producers for the given economic sector. Related to the tanker market, it is possible to both aggregate capital input, measured in dwt and output, also measured in dwt, but after being converted from tonne-miles by a productivity factor. The use of these physical units, without referring to prices or costs, means that an engineering concept of capacity is used rather than an economic one.
Outside the shipping industry a substantial amount of work has been done to estimate capacity utilization for national economies or some particular sector of the economy. These studies or methods can be classified as production based and survey based categories, (Christiano 1981, Kalindaga 1990). In the production function method functions are estimated to measure relationships between input and output. Calculated output based on production functions by utilizing all available inputs is compared to capacity output which is achieved at peaks in business activity, (Harris and Taylor 1985).
function method is the Wharton trend-through-peaks method.
identifies peak values in time series.
The peak outputs are hypothesized to be a measure of full capacity. An extrapolation is performed based on these peak values. This method assumes that outputs move in straight lines between the peaks. A third production based method is the output-capital method. By calculating a series of actual outputcapital ratios, a trend line is constructed and deviations from this linear trend are interpreted as under or overutilization of capacity. A totally different way of measuring capacity utilization is the survey method. In this method firms are asked to state their full capacity and the current utilization rate. It is up to the company itself to define full capacity and utilization rate.
various firms are aggregated for the sector or the economy under consideration.
A general capacity utilization term for the tanker market is to be developed by the author. The objective is to establish a capacity utilization concept which is based on a production function. The production function, which output is tonne-miles, will have to be converted to capital (dwt) by a conversion or productivity factor. The numerator shall include all types of paid employment, which means that storage vessels will constitute an element of total tanker demand or employment.
combined carriers trading with dry cargo.
The following capacity utilization (CAP) term is defined:
CAP = [f(production function, productivity, storage vessels) (total tanker fleet)] (5.1)
term will be developed.
The concept of tanker demand, measured in tonne-miles, has, from a tanker capacity utilization point of view to be converted to capital, represented by ship tonnage, measured in deadweight tonnes. This conversion or productivity factor carries an important element, average vessel or fleet speed.
of freight rates and unit voyage costs.
During any time period the operating profit (OP) from the vessel (actually (he whole fleet) is defined by Beenstock and Vergottis (1989a) as:
OP = V + SFR - Va + UC - OC (5.2)
average of the tanker fleet) is:
V = (SFR/a UC) Hal) (a> 1) (5.3)
As seen, speed varies directly with the ratio of freight rates to unit voyage costs.
By assuming market clearing within each time period (a year)
tonne-miles = supply (of tonne-miles)
tonne-miles demand (per year) = Adj F * V (¥*hours/year)
Adj F = adjusted tanker fleet with respect to proportion of tankers in lay-up, tankers in storage and combined carriers [Oil-Bulk-Ore(OBO) and Ore-Oil (0/0)] trading oil.
Lay-up is hypothesized to depend on the profitability of the voyage market relative to the cost of laying up (endogenously determined).
components are exogenous.
Based on exogenous variables like e.g. tonne-miles demand, fleet size, unit voyage costs, (equilibrium) spot freight rate(s) are determined and balance supply and demand in the freight market. If demand for freight services rises, freight rates will rise and supply will increase by increased vessel (fleet) speed and a reduction in lay-up.
a component on the (fleet) supply side.
defined by Lloyd's Shipping Economist (LSE) [LSE (1989)].
LSE defines ship demand from the supply side and in the following way:
D=S-(L+D-0 (5.4)
All the parameters are measured in aggregate deadweight terms.
ships in each category are determined as follows:
Supply is the total deadweight tonnage of all vessels which are trading, or available for trading, which means everything that is afloat or in dry dock.
casualty either before or during lay-up.
for example casualties, repairs, floating storage.
Loss due to observed slow down or slow steaming (speed reduction)
proportion of shipping capacity lost due to operating speed below base speed.
weather at normal service draught, as reported in Lloyd's Register of Shipping.
The average trial speed is then reduced by a factor (15 %) to allow for allweather trading, hull fouling, ageing and non-optimal plant performance in order to obtain the base speed. The approach is supported by (Lloyd's)
the ship's maximum or base speed.
by slow steaming.
steaming is given by:
0 = 1 - (Tbs/Tobs) ("100 %) (5.5)
T ps = voyage length at base speed = [(S"24)
Tobs = voyage length at observed speed = [(S*24)
In the above expression, average deadweight and service factor may be included if data are available.
There are several problems in interpreting the results from the stated LSE productivity model. If an increase in demand is met by an increase in vessel operating speed, and actual fleet supply remains unchanged, the LSE model will show a reduction in slow steaming. But, if an increase in demand is met entirely by an increase in supply by newbuildings and/or ships moving out of lay-up, and the fleet '
element will rise in dwt terms.
As a basis for the understanding of the productivity factor wilhin lhe new capacily utilization lerm under development, an aggregate demand related productivity factor (P) may be delined by lhe expression:
DTR = DTM/P = Z DTMi/PF; (5.6)
P = DTM/E(DTM/PF;) (5.7)
DTM = production function = aggregate tonne-miles demand DTMi = tonne-miles demand represented by trading route (i)
representative average vessel category (i) employed in such a standard route.
PF; = corresponding disaggregate productivity factor(s).
productivity factor will be provided.
The disaggregate productivity factor (PF;)
average vessel category employed in one particular route (i), may be defined by:
PF; = RT; * CC; " LF; (5.8)
RT = number of round trips (per year) CCL = cargo carrying (leg) distance LF = load factor; cargo load (size)
dwt per trip)
The number of round trips per year may be expressed by:
RT; = (365 - RM;)/VD; (5.9)
VD; = voyage days = port days (PD) + canal days (CD) + sea days (SD) The number of port days may be expressed further by:
PD; = LD; + DD; (5.10)
LD = loading days = cargo load (size)/ (loading capacity * work hours per day)
The number of canal days may be expressed further by:
CD; = TD; + CDD; (5.11)
And the number of sea days may be expressed further by:
SD; = (CCL; + BL) / V; * 24 (5.12)
BL; = ballast leg V; = speed By combining equations 5.8 ihrough 5.
may be expressed:
Equation 5.13 says ihai for each representative trading route (i) ihere exist a standard representative average vessel category.
By combining equations 5.7 and 5.13, aggregate productivity (P)
expressed:
P=DTM EDTMIT (365-RM;) "CCL;"LF; (LD; + DD) HTD; + CDD) + (CCL; + BLIV 240)
contradict the objective of this thesis, which is to focus on aggregate variables.
In the remainder of the thesis (e.g. empirical analysis) only aggregate productivily values for the tanker (and combined carrier interface)
will be considered.
tanker fleet may be questioned. Due to the fact that there are literally thousands of different trading routes with corresponding optimal vessels, one may argue that the use of an overall conversion factor could be misleading or even inaccurate. Secondly one may object that the aggregate productivity factor is made up of many dynamic components which one strongly could argue are a function of e.g. rate level, which again may be a strong argument to treat P endogenously. On the other hand, vessel maintenance, like docking or major overhauls, will probably be tried to be carried out ahead of an expected market improvement, and equivalently maintenance will probably be tried to be postponed during an improved market situation. Also, mechanical engineering may suggest that the mean time between failures (MTBF)
function of velocity (speed), and subsequently will increase with increasing rate level [subject V; = f(SFR)].
In this respect one may argue that RM;  = f(SFR, SFR 41, V;), t = time period.
As discussed, from an equilibrium modeling point of view, speed is treated endogenously as a function of rate level. One may argue that increasing speed may cause delay days (waiting days) with respect to loading, discharge (both at discharge port and in connection with lightering) and canal transit. For a group of vessels the most typical cargo carrying distance(s) and ballast leg(s) may change due to different market conditions and/or political events.
aggregate productivity.
determined aggregate variable.
Up to this point we have defined a production function (equation 4.12), which represents aggregate tanker demand, measured in tonne-miles. Together with equation 5.6 the capital requirement for trading tonnage is established, measured in dwt. The total capital requirement for tankers, lo be in compliance with the numerator of equation 5.
demand side because they represent paid employment for the ships in question.
utilization term of equation 5.1, will then be defined as:
D = Dir + Dsv (5.15)
Dgy = demand for (stationary) storage vessels 5.3.
The denominator of equation 5.
capital (dwi), is hypothesized to be determined by the expression:
S = F + (1-B)Sobo (5.16)
F = Total tanker fleet The term includes lay-up, other idle (under repair etc.) (1-B)Sobo = Combined carriers trading with dry cargo (OBO = Oil-Bulk-Ore)
f = The proportion of combined carriers trading with liquid bulk (oil)
The expression represents a tanker (liquid cargo) supply potential, and as such it is assumed to be part of the supply side.
oil are considered a demand sided effect.
By combining equations 5.6, 5.15 and 5.16 into 5.
concept for the tanker market may be defined as:
CAP = (DTM/P + Dsy)/IF + (1-B)Søbo] (5.17)
capital based. It relates a production function (DTM)
(P) (output to capital relationship) which converts the production function to capital (dwt). Together with storage vessels (Dgy). this represents the total demand for capital or tonnage. The denominator represents the total supply potential of tankers and combined carriers (combined carriers not trading liquid bulk).
concept.
Capacity utilization (equation 5.17) will tend to increase with increasing OPEC Middle East output (through the production function), and increasing use (demand) for storage vessels. The term, other things equal, will tend to decrease with increasing aggregate productivity.
cargo), will also tend to reduce capacity utilization.
There are several bodies that publish (in the proprietary domain) oversupply or capacity utilization rates related to commodity shipping; Lloyd's of London Press (Lloyd's Shipping Economist), John I. Jacobs plc (World Tanker Fleet Review) and United Nations Conference on Trade and Transport (UNCTAD) (Review of Maritime Transport). In the following, the oversupply or capacity utilization concepts from these institutions will be analysed.
(op.cit.) for a comparison of several capacity utilization terms.
SP= 0+ L(+] (5.18)
The oversupply concept by Lloyd's is closely linked to their way of analysizing slow steaming.
shortcommings as their slow steaming concept, which is already discussed.
SP = L(+ Og + Py + Wt + Pej + Svi (5.19)
Estimates of the slow steaming element is calculated in a similar way as the term is treated by Lloyd's. Slow steaming is calculated based on a sample of tankers which are surveyed over a six month period.
compared to design speed, and the difference is interpreted as slow steaming.
Oy = [(Vdy - Vobs()/Vd]*Sactive (5.20)
To calculate excess port time, a sample of tankers is surveyed to establish the average number of canal and port days. By comparing to "normal"
canal and port days, excess port time is calculated.
The approach by both Lloyd's and J.I.
operators. Their methods also relies almost entirely on inputs.
They do not pay attention to output factors as tonnes carried or tonne-miles produced. One may view both the LLoyd's and J.I.
survey-based and production based methods of calculating capacity utilization.
SP = Surplus tankers in %, [(SP/S)*
SP = R'(Dpot - DTM) (5.21) R = Ratio of tonne-miles to capital (dwt) = Average tonne-miles for the 1965 to 1974 period, divided by the average tanker fleet for the same years.
derived from trade statistics)
The UNCTAD method of calculating capacity utilization differs from the LLoyd's and J.I. Jacobs methods. Firstly, that it is not based on an analysis of individual components of idle capacity, but on a computed aggregate estimate of tonnage surplus. Secondly, it uses both inputs and outputs and that it is an interaction between input and output that provides capacity utilization.
There are several shortcommings with the UNCTAD procedure. Their ratio of output (tonne-miles) to capital (dwi) was calculated as an average of yearly calculations of total tonne-miles divided by total tanker fleet for the 1965 10 1974 period. UNCTAD claims that this is an expression for productivity, but il is simply a static output to capital ratio. It does not take into account changing trading patterns, different structure of the active tanker fleet etc., which have occurred since the stated time period.
Kalindaga op. cit. has introduced two other capacity utilization concepts. One is based on a production function and one is based on the output-capital ratio method. Both expressions are basically derivatives of the UNCTAD method.
output.
The production function method has the following form:
CAP = DTM/DPTM (5.2243)
DTM = actual seaborne shipments (in tonne-miles), (data taken from Fearnleys, which are based on trade statistics)
DprM = potential seaborne shipments (in tonne-miles)
= ag + aj Sactiveq +ap(Time) + ug (5.22b) [Sactive = active tanker fleet (total tanker tonnage less laid-up vessels)
technological change, ag, a1, ap = regression coefficients, u = error term] The potential seaborne shipments equation (5.22b) was calculated by OLS for the 1965-1974 period (based on a logarithmic form)
more "normally" utilized during this period.
The output-capital ratio method has the following form:
CAP = P/R end (5.23)
R =tonne-miles performed (taken from Fearnleys, based on trade statistics)
Rirend = OLS fitted trend using R-values for the 1965 to 1974 period.
The production function linking capital to output does not represent any behavioural demand element.
capacity method as for the UNCTAD model.
The primary purpose of a capacity utilization term for tanker shipping will have to be prediction. In this respect the major shortcommings with the discussed concepts of capacity utilization may be summarized:
None of the discussed methods have a reference to the underlying oil market. They only refer to tonne-miles, which are derived from trade statistics. In addition, the UNCTAD and Kalindaga methods relay heavily on a static output to capital ratio dating back to the pre 1973 era. The approach by Lloyd's and J.I. Jacobs require e.g.
unavailable to outside bodies.
five discussed methods in the following way:
- It is quarterly based.
- It incorporates a production function for the tanker sector. This represents a link to underlying oil market, which again governs oil supply and demand and tanker trading patterns, and subsequently tanker demand.
- It incorporates an output-capacity ratio which represents a productivity element for the liquid cargo carrying segment of commodity shipping, at the same time provides the derived productivity factor a thorough insight of the various elements which constitutes productivity.
- It provides a link to the dry cargo market by taking account of combined carriers trading with liquid bulk.
- It treats storage vessels as an integrated part of the demand side for tankers.
production and output-capital based method.
5.5 The E ;
It is postulated that the tanker market (with the combined carrier interface) represents a single, competitive and homogenous freight market. Glen (1990) argues that the assumption that the oil tanker market is homogenous is no longer valid. Based on empirical data for the period 1970 to 1978, he claims that market differentiation by size and by route emerged in the 1970s.
characteristics for lankers differ by size, and that profit margins vary across routes. This is taken as the emergence of differentiation.
context it is simply assumed that there is substitution on the margin.
It is further assumed that vessel owners and operators maximize profil under conditions of perfect competition. At the same time they are price takers on spot freight rates (SFR) and operating or unit voyage costs.
primarily bunkers expenses, port and canal fees and crew costs.
Statistical (econometric and simulation) models of the world shipping markets have focused on the joint determination or simultaneous solving for equilibrium of freight rates and the supply and demand for shipping (freight markets) and (to a lesser degree) to the market for ships as such (ship markets). Beenstock and Vergottis (1989a) and (1989b) (econometric models) and Strandenes (1986) (simulation model) are mentioned. Others are Norman and Wergeland (1981) (simulation model), Hawdon (1978), Charemza and Gronicki (1981)
(econometric models).
Spot freight rates within this framework or model are hypothesized lo be a function of the capacity utilization which represents lhe disequilibrium between the total demand for ship tonnage (D) and potential tanker supply (5).
The model hypothesizes that by calculating the total demand for dwt and by comparing this lo the potential liquid bulk supply, the subsequent capacity utilization rate (CAP) is an indicator of spot freight rates (SFR).
CAP = (DTM/P + Dsy)/IF + (1-B)
Based on the general transformations proposed by Box and Cox (1964)
(YA 121 31 <>0O YI)
(XA2-1)/A2 22<>0 X(A2)
Into the linear model:
SFR (Al) = a + BICAP](A2)
Equation 5.25 says that SFR is a power function of the capacity utilization.
The relationship of equation 5.
model of the world tanker market.
tankers. As stated earlier (Asch op. cit.)
in a meaningful way.
Tonne - Miles/dwt Conversion Factor (Productivity)
A generalized scheme for the analysis of the market for large tankers.
The analytical scheme, which is schematically outlined in figure 5.
quarterly based and have a time horizon of 6 to 8 quarters.
The exogenous variables will be: OPEC Middle East petroleum (crude oil and refined petroleum) exports, amount of storage vessels, total tanker (F) and combined carrier fleet, and the proportion of combined carriers trading with dry bulk. Based on a fundamental oil market supply and demand analysis, which is beyond the scope of the topic of the dissertation, with OPEC treated as a cartel and the residual supplier of oil, OPEC Middle East oil exports figures are derived. Aggregate productivity when treated as an exogenous variable, could be treated as a constant or as trend (time) variable over the planning horizon.
'When treated endogenously, P = f(SFR) or P = f(SFR, trend).
F=F1 +DL- SC=VL (5.26)
DL = deliveries of new vessels (dwt)
The amount of lay-up tanker tonnage is considered to be a demand sided response in the system. Due to the lead time in shipbuilding, deliveries of newbuildings can be treated as a function of the orderbook if the time frame is 6 -8 quarters.
The level of scrapping may be assumed to be a function of demolition prices (for lightweight tonnes of scrap steel), the secondhand value of the vessel, cashflow versus rate expectations, age structure of the fleet, etc. The above is also applicable for combined carriers. The only endogenous variable(s)
will be the spot rate for VLCCs (and productivity).
are assumed identified.
Chapter 6 represents the first part of the empirical section of the thesis. The primary objective of the chapter is to test the validity of the OPEC cartel hypothesis by the alternative aggregate approach which was stated in chapter 4. By the thorough and comprehensive analysis of the behavioural aspects behind the OPEC Middle East oil supply (of chapter 4), and the (accepted) empirical test of the oligopolistic dominant firm hypothesis of OPEC (which is to be tested in this chapter), one may argue that there is a causal relationship between OPEC Middle East oil supply and aggregate tanker demand. This will be investigated in chapter 7.
(OLS) method.
As outlined in chapter 4 it was concluded that "
any of the alternatives".
In the following a cartel behaviour for OPEC is assumed (oligopolistic dominant firm), in the sense that the organization is the residual supplier of oil and that the group supplies the difference between world oil demand (consumption measured as ex-refinery deliveries and inventory movements)
OPEC supply.
The schematics of a model of the world oil market.
Figure 6.1 outlines the schematics of a model of the world oil market. As opposed to the TCU model (see section 4.4), it is hypothesized that the (quarterly average) spot price for oil is a function of the disequilibrium between the (residual) demand for OPEC crude oil (D) and actual supply of OPEC crude oil (S) or OPEC behaviour.
mathematical expression can be stated:
d(SP)/d(D/S); = a3[(SP); - e¥] (6.1)
y = aj(OSP) + ax(SP/OSP)
= world consumption (world outside former centrally planned economies) + change in stocks - (non-OPEC production + net exports from centrally planned economies + processing gains + NGL production etc.)
Solving eq. 6.1 yields the following:
(SP) = e 21 (OSP) + aX(SP/OSP) 1 + a3(D/S); + b (6.2) When analyzing oil (or energy) statistics, it is evident that; supply = demand (consumption + stock movements)
close the gap between supply and demand.
by the factor (actual OECD company stocks - desired OECD company stocks)
The real expression for (SP); is then hypothesized to be:
(SP) = e 31(OSP)4 + a (SP/OSPH-1 + a3(Dadj/SH +b (6.3)
stocks)
price determination, a further analysis is appropriate.
In general, oil inventories may be classified into three categories;
secondary and tertiary. The primary stocks network includes: - Stocks at tanker loading ports.
- Crude oil and products at sea and in pipelines. - Crude oil and products at discharge terminals. - Crude oil and products at refineries.
- Refined products at large distribution terminals.
wholesalers. Tertiary stocks are stocks held by consumers.
Once oil (and refined petroleum products) get out of the primary sector and into distribution and consumer channels, it is lost to statisticians.
secondary and tertiary stocks are measured as fluctuations in consumption.
A seasonal component within the company stocks data is evident. If these components are analyzed further, it is stated that there is a company stocks buildup during the second and third quarter and a stocks drawdown during the first and fourth quarter.
The reason for the second quarter stocks buildup is primarily gasoline stocks buildup to meet increased transportation requirements during the summer months.
stocks buildup to meet increased heating requirements during the winter.
The following behavioural relationship for OECD company stocks is assumed:
(Stocks); = eB! (SP/OSP).1P2 (Desired stocks), B3 (6.4)
(SP/OSP)
sales price (Arabian Light) in the previous quarter.
(Desired Stocks);
quarter t.
A regression analysis (OLS) of the company stocks movements attributable to price fluctuations, yields the following results (ref. table 6.1)
transformed data:
B1=0.78 0.
53-090 fn.
Estimated regression parameters.
R2 = 0.98, DW = 1.72, F-test = 557.29 The analysis is based on data for the period Q2 1979 - Q3 1985. Basic data are provided in appendix at the end of this chapter (Table 1 App.Ch. 6).
"desired stocks" and "stocks" are in millions of barrels.
All the coefficients and the F-test are significant at a 5% significance level. The Durbin-Watson test indicates that there is no autocorrelation in the residuals.
The coefficient of multiple determination, R2, is high (0.98).
Figure 6.2 shows a plot of actual data versus the fitted values from equation 6.4.
The graph visualizes the strong coefficient of multiple determination.
Actual company stocks data and model fit.
Figure 6.2 The OLS statistical analysis confirms the hypothesis about the stocks equation, and that equation 6.
for OECD company stocks.
The stocks equation says that when the spot price in quarter t-1 is higher than the official (OPEC) sales prices (in quarter 1-1), the expectation of ever higher prices in quarter t, will encourage refineries to buy more crude oil.
measured as an increase in company stocks in quarter t. 6.72 Hypolhesss.
identical to equation 6.3 with b = 0:
(SP) = e 21(OSP)4 + a (SP/OSP)-1 + a3(Dadj/Sh (6.5)
(SP); = Nominal spot price for Arabian Lt. (or Iranian Lt.)
(OSP) = Official selling price for Arabian Lt. (or Iranian Lt.) for quarter t (SP/OSP).1 = Ratio between (nominal) spot price for Arabian Lt.
Lt.) and official selling price for previous quarter.
(Dad;j/S)
A regression (OLS) analysis provides the following result (ref. table 6.2)
on In-transformed data:
Parameter estm.
R2 = 0.93, DW = 0.002 (), F-test = 115.
(*) Because of the presence of lagged variables, the use of the DW-test is invalid.
The analysis is based on data for the period Q1 1980 - Q4 1986, which represent both upward and downward price fluctuations.
appendix at the end of this chapter (Table 2 App. Ch. 6).
All the coefficients and the F-test are significant at a 5% significance level.
coefficient of multiple determination, R2, is high (0.93).
Figure 6.3 shows a plot of actual data versus the fitted values from equation 6.5.
Graph of the spot price for Arabian Lt. (or Iranian Lt.), actual data and model fit.
Equation 6.5 with estimated parameters from table 6.2 is interpreted as an empirical test of the OPEC cartel hypothesis, assuming that the oil price is a function of the disequilibrium between (adjusted) demand for OPEC oil and actual supply of OPEC oil.
What the price determination equation basically tells (eguation 6.5), is that the spot price for Arabian Lt. (or Iranian Lt) is dependent on the target price (official selling price)
Equation 6.5 with estimated regression parameters (table 6.2), may be used in predictive purposes (oil price forecasting). The official selling price (OSP) is a published target price which is fixed for a longer period of time (several consecutive quarters or even years). With a forecasting horizon of 6-8 quarters, OSP may be regarded as a constant or, through an iterative procedure with a consistency check, it may be adjusted due to significant and sustained spot price increases. For the time period covered by the regression analysis, the OSP for specific crude oils were published. After OPEC III, with the oil price collapse of 1986, the organization has focused on a basket of crude oils as a basis for the target price. The adjusted demand (Dadj); may be obtained by utilizing the analyses of section 3.6 and last part of section 4.5 with or without the use of energy/oil market demand models. The actual OPEC production (behaviour) may be obtained (forecasted) in the context of the (OPEC)
play, ref. chapter 9 and section 3.6.
The advantage of equation 6.5, compared to the TCU modeling concepts (ref. section 4.4), is that the presented oil pricing relationship is supported by both theoretical and empirical analyses, and that it is independent of (estimated) OPEC production capacity.
(additional) independent exogen variables.
topics for further research.
[19793 19794 fr (2 Dee fe low | fer spd for a I | 19822 mm | mes je an Je | ome dan.
en ser dma Leh Consumption data for World Outside (former) Communist Countries, and total Non-OPEC supply [incl. net exports from (former) CPEs, processing gains and NGL production]. Both time series are mbd. Time series Q1 1979 - Q4 1985.
Actual and desired OECD company stocks data (total crude oil and refined products) in millions of barrels. Time series Q2 1979 - Q3 1985.
Table 1 App. Ch. 6 La(SP) La(OSP) In(SP/ La(Dqadj/Sh OSP)
3.5995 3.3021 0.5135 0.0327 980.2 3.5701 3.3611 0.2974 -0.
980.3 3.5056 0.2090 -0.0883 980.4 3.6540 3.4446 0.0974 0.0812 981.1 3.6195 3.4843 0.2095 -0.
9812 1981.
ll | 1983.4 3.3453 3.3673 -0.0052 -0.0203 1984.1 3.3513 3.3673 -0.
1984.2 3.3421 3.3673 -0.
1984.3 3.3196 3.3673 -0.0251 -0.0281 1984.4 3.3236 3.3673 -0.0477 -0.0454 | 1985.1 3.3240 3.3439 0.0437 -0.0057 1985.2 3.3010 3.3322 0.
1985.3 3.3078 3332) -0.0312 0.0425 1985.4 3.3250 3.3250 -0.0246 0.
2.3674 2.3674 0.0000 0.
Sources lor basic data: PIW, Platt s, IFA.
Official selling price for Arabian Lt. (OSP), spot price - official price ratio (SP/OSP) and OPEC adj. demand/supply ratio. Time series Q1 1980- Q4 1986.
Table 2 App. Ch. 6 7.
In chapter 4 a discussion was concluded by hypothesizing a production function relating aggregate tonne-miles demand to OPEC Middle East oil exports (crude oil and refined petroleum products).
demand to various oil supply variables.
The oil flow concepts; OPEC Middle East exports and (total) Middle East exports were in section 4.5 tested to be highly correlated to international trade of crude oil and refined petroleum products. Together with the accepted hypothesis that OPEC is an oligopolistic dominant firm (acting as a cartel) (ref. chapter 6), and an empirically tested and accepted hypothesis of aggregate tanker demand as a function of (OPEC) Middle East exports, (which is to be tested in this chapter)
aggregate tanker demand and (OPEC) Middle East exports.
In the second part of chapter 7, the predominance of VLCC employment out of the Middle East region is investigated by an analysis of actual tanker movements.
capacity utilization term from a VLCC perspective (ref. chapter 5).
measured in tonne-miles;
- OPEC crude oil production (mbd), (X1) - OPEC crude oil and NGL production (mbd), (X2) - OPEC Middle East crude oil production (mbd), (X3) - OPEC Middle East exports (crude oil and refined petroleum products) (mbd), (X4) - Total OPEC exports (crude oil and refined petroleum products) (XS) - Middle East exports (crude oil and refined petroleum products) (mbd) (X6)
The variables X1, X2 and X3 are production figures (which include domestic consumption, stocks movements and exports), while the variables X4, XS and X6 represent pure exports figures. The time series are yearly figures for the 1975 to 1989 period. The actual time series are provided in Table 1 App. Ch. 7. In the first production function:
Drm =2a1* Xl + ap (7.1)
X1 = OPEC crude oil production (mbd) The following regression parameters have been estimated, ref. table 7.1:
NI ET a Se | ameter estm.
F test(1,13)
All the statistical parameters are significant (5 % significance level)
test indicates that there is no autocorrelation in the residuals.
constant term, the validity range is limited because X1 ->0 => DTM > neg.
In the production function:
DTM = af "X2+ 22 (7.2)
X2 = OPEC crude oil and NGL production (mbd)
Le 0.983 test(1,13) =| DW =1.
The parameters (ai, ap) are significant, but the DW test indicates autocorrelation. Also, X2 -> 0 => DTM - > neg.
DTM = aj"X3 + 22 (7.3)
X3 = OPEC Middle Fast crude oil production (mbd) The following regression parameters have been estimated, ref. table 7.3:
1.64 F test(1,13) DW = 1.75 =1032 Estimated regression parameters.
All parameters, except the t-statistic for the constant term, are significant.
are no formal limits for the validity range; X3 -> 0 => DTM > pos.
For the production function:
DTM = aj"X4 + ap (7.4)
X4 = OPEC Middle East exports (crude oil and refined petroleum products) (mbd) The following regression parameters have been estimated, ref. table 7.4:
Parameter estm. | T-statistic | sure!
All parameters are highly significant, and there are no formal validity limits; X4 0 DTM? pos.
DTM = af "X5+ 22 (7.5)
XS = OPEC exports (crude oil and refined petroleum products) (mbd) The following regression parameters have been estimated, ref. table 7.5:
| | em sto | 364. CAEL | sec)
All parameters are significant.
significance level, but not at the 1 % significance level. There are no formal validity limits; X5 ->0 => DTM > pos.
DTM = af "X6 + 22 (7.11)
X6 = Middle East exports (crude oil and refined petroleum products) (mbd)
R2 = 0.992 F test(1,13) DW = 2.
All parameters are significant, and there are no formal validity limits;
=> DTM > pos.
Based on the provided statistical analysis, both X4, "OPEC Middle East exports" and XS, "(total) Middle East exports"
representative variables for aggregate tonne-miles demand.
As stated earlier; based on the empirical analysis of section 4.5, the theoretical and empirical analysis of OPEC and the oil market (ref. chapters 4 and 6), and the provided analysis in this chapter, it is concluded that e.g. variable X4, OPEC Middle East exports, represent an aggregate behavioural variable for aggregate tanker demand, and as such represents a causal relationship between the stated dependent variable (aggregate tonne-miles demand)
(OPEC middle East exports).
The established production function(s) represents one of several input variables of the developed capacity utilization term (ref. chapters 5 and 8), which again is the core element in the VLCC spot freight rate relationship (see sections 5.5, 8.3, 8.3.1, and 8.3.2). In this respect, to support the hypothesis that from a large tanker (VLCC) perspective one can focus entirely on the (OPEC)
to VLCC employment.
A comprehensive study of tanker movements has been performed based on extensive search in Lloyd's of London Press' Databases.
From individual tanker (and combined carrier)
following four size categories, have been established:
- 100,000 - 199,999 dwt - 200,000 + dwt 1989 were included because they cover the same time period from which quarterly time series are used to calculate both productivity and the spot rate relationship(s).
maximum and minimum aggregate tanker demand for the 1980s, respectively.
The universe is defined as follows:
From: 1. AG = Mina Qaboos - Chah Bahar 2.Red Sea (RS) = Assab - Aden (including Gulf of Suez excluding Suez Canal) 3. West Africa = Cap Blanc - Baia Dos Tigres 4. North Africa = El Arish - Porto Praia (includes Azores Canaries and Cape Verde) 5. North Europe = UK, Horum - Gibraltar (including Baltic and Scandinavia) 6. South Europe = Malaga - Trieste, Greece 7. Carribs/North America = All islands (Excluding Venezuela) + Beverly - San Diego, Texas - Tukfoyakuk 8. Far East (incl Australia) = Phuket - Ogasawara Islands, Saipan Island- Tabuaeran (excluding Singapore, Japan, Korea) 9. Ceyhan (Turkey) 10.
11. Venezuela 1.
For details about the basic data see Appendix B.
the following reference locations are used:
- AG (Saudi Arabia, Ras Tanura)
- Turkey (Ceyhan/Iskenderun)
- Far Fast/ Australia (China, Dalian)
- North Africa (Libya, Es Sider)
- North Europe (Nederlands, Rotterdam) - North America/ Caribbean (Mexico, Vera Cruz) - Red Sea (Saudi Arabia, Yanbu)
- South Europe (France, Fos/ Marseilles)
- Venezuela (Amuay Bay)
- West Africa (Nigeria, Bonny) - North Europe (Nederlands, Rotterdam) - South Europe (France, Fos/ Marseilles) - North America (USA, Houston/LOOP) - Korea (Inchon)
- Japan (Yokohama)
- Far East/ Australia (Sydney)
See table 2 App. Ch. 7 for actual distance data.
When calculating tonne-miles a load factor of 0.
throughout the calculations.
In section 7.3.1 of this chapter the following elements have been investigated;
for the individual years 1980, 1985, 1987, 1988, and 1989.
In section 7.3.2 the various calculations of section 7.3.
a soon... Sumas 2] Corton A TA esac lw ser | iy.
figures from trade statistics. VLCC employment in 1980. Table 7.
In 1980 a total of 3936 OBOs (trading with oil) and tanker sailings were recorded (vessels > 200.000 dwt). Of these sailings 1439 or 36.6 % were out of the Middle Fast (AG, Ceyhan. RS). For the same year a grand total of 53082 sailings were recorded (for vessels above 10.000 dwt).
Based on dwt VLCC employment out of the Middle East related to total employment out of the region (tankers and OBOs trading with oil), represented 72.2%.
Based on data from table 7.7: Measured in tonne-miles 80.1 % of the VLCCs traded out of the Middle East, while large tanker employment constituted 42.
of grand total tonne-miles.
(See tables 3-7 App. Ch. 7 for disaggregated tonne-miles matrices). For the same year 59.
Middle East. Based on data from table 7.8: In 1980 53.15 % of the total dwt were represented by vessels larger than 200.000 dwt, while 55.
active fleet were made up by VLCCs.
326.785 12.429 6.
191.87 10.403 6.
1980 Tankers & OBOs (mill. dwt) Total tanker fleet Tankers > 200.' Total OBO fleet OBOs > 200'
48.376 0.
7.541 0.
OBOs in oil 0.
Vessels >  200'| 199.
Total fleet V>200'
V>200'
53.15 % 176.
Sources: Basic fleet data from Fearnleys, OBOs trading in od from Lloyd's Shrpping Economist.
Representative 1980 mid year data.
VLCC employment in 1985. Table 7.
In 1985 a total of 1589 OBOs (trading with oil) and tanker sailings were recorded (vessels > 200.000 dwt). Of these sailings 665 or 41.9 % were out of the Middle East (AG, Ceyhan, RS). For the same year a grand total of 52522 sailings were recorded (for vessels above 10.000 dwt).
Based on dwt VLCC employment out of the Middle East related to total employment out of the region (tankers and OBOs trading with oil), represented 52.5%.
Based on data from table 7.9: Measured in tonne-miles 69.5 % of the VLCCs traded out of the Middle East, while large tanker employment constituted 32.4 % of grand total tonne-miles. For the same year 38.7 % of international crude oil and products were transported out of the Middle East. Based on data from table 7.10: In 1985 47.63 % of the total dwt were represented by vessels larger than 200.000 dwt, while 38.58 % of the active fleet were made up by VLCCs.
11985 Tankers | Fleet Floating storage end OBOs (mill. dwt)
tanker fleet | 251.
[Tankers > 200 | > 200.' 131.533 47.698 8.895 Total OBO fleet [36725 1.
OBOs > 200' 5.
Vessels >  200'| 137.
Active vessels >|76.51791 200'
Sources: Basic fleet data from Fearnleys, OBOs trading in od from Lloyd's Stupping Economist.
Representative 1985 mid year data.
Table 7.10 —L73E+12 | 2.
VLCC employment in 1987. Table 7.
In 1987 a total of 1779 OBOs (trading with oil) and tanker sailings were recorded (vessels > 200.000 dwt). Of these sailings 942 or 53.0 % were out of the Middle East (AG, Ceyhan, RS). For the same year a grand total of 57830 sailings were recorded (for vessels above 10.000 dwt).
Based on dwt VLCC employment out of the Middle East related to total employment out of the region (tankers and OBOs trading with oil), represented 58.5 %.
Based on data from table 7.11: Measured in tonne-miles 85.4 % of the VLCCs traded out of the Middle East, while large tanker employment constituted 36.1 % of grand total tonne-miles. For the same year 41.9 % of international crude oil and products were transported out of the Middle East. Based on data from table 7.12: In 1987 44.72 % of the total dwt were represented by vessels larger than 200.000 dwt, while 42.04 % of the active fleet were made up by VLCCs.
Active vessels >|92.64541 200"
Sources: Basic fleet data from Fearnleys, OBOs trading in od from Lloyd'
1987 Tankers and OBOs (mill.
Stupprag Economist. Representative 1987 mid year data. Table 7.12 —— i nn am |tonne-miles | 245523 1.89E+12 | 21619 1.
[sum — 200749 2.193E+12 | Total (>200'dwt 563499 2.
VLCC employment in 1988. Table 7.
In 1988 a total of 2081 OBOs (trading with oil) and tanker sailings were recorded (vessels > 200.000 dwt). Of these sailings 1075 or 51.7 % were out of the Middle East (AG, Ceyhan, RS). For the same year a grand total of 57953 sailings were recorded (for vessels above 10.000 dwt).
Based on dwt VLCC employment out of the Middle East related to total employment out of the region (tankers and OBOs trading with oil), represented 62.7 %.
Based on data from table 7.13: Measured in tonne-miles 84.3 % of the VLCCs traded out of the Middle East, while large tanker employment constituted 39.9 % of grand total tonne-miles. For the same year 42.5 % of international crude oil and products were transported out of the Middle East. Based on data from table 7.14: In 1988 44.03 % of the total dwt were represented by vessels larger than 200.000 dwt, while 43.6 % of the active fleet were made up by VLCCs.
1988 Tankers | Fleet and OBOs (mill.
Total tanker fleet | 230.
| Active fleet 220.
V>200' dwt in % | 43.
Sources: Basic fleet data from Fearnleys, OBOs trading in od from Lloyd's Shipping Economist.
Representative 1988 mid year data.
VLCC employment in 1989. Table 7.
In 1989 a total of 2367 OBOs (trading with oil) and tanker sailings were recorded (vessels > 200.000 dwt). Of these sailings 1254 or 53.0 % were out of the Middle East (AG, Ceyhan, RS). For the same year a grand total of 60607 sailings were recorded (for vessels above 10.000 dwt).
Based on dwt VLCC employment out of the Middle East related to total employment out of the region (tankers and OBOs trading with oil), represented 65.8 %.
Based on data from table 7.15: Measured in tonne-miles 84.4 % of the VLCCs traded out of the Middle East, while large tanker employment constituted 41.6 % of grand total tonne-miles. For the same year 44.2 % of international crude oil and products were transported out of the Middle East. Based on data from table 7.16: In 1989 43.91 % of the total dwt were represented by vessels larger than 200.000 dwt, while 45.31 % of the active fleet were made up by VLCCs.
and OBOs (mill.
Total tanker fleet |234.96 Tankers > 200.' 111.
Total OBO fleet * | 32.93 0.43 OBOs > 200' 6.
5.94 0.
| Vessels >  200'
Total fleet V>200' dwt in % | 43.91 % | Active vessels >|105.9926 200'
Active fleet 233.
V>200' dwt in % | 45.
Sources: Basic feel dala from Fearnleys, OBOs trading in od from Lloyd's Shipping Economist.
Representative 1989 mid year data.
[able 7.
RR LT AR Loo ls bon fon tr fon too | 4 1548 [387 Jaro [os [442 someon)
1) VLCC employment out of the Middle East related to total VLCC employment. Data based on tonne-miles.
2) VLCC employment related to total tanker employment. Data based on tonnemiles.
3) VLCC employment out of the Middle East related to total tanker employment. Data based on tonne-miles.
4) Middle East exports of crude oil and refined petroleum products in relation to international trade with crude oil and refined petroleum products. Data are based on mbd.
5) VLCC: related to total dwt.
6) Active VLCCs related to active dwt.
7) VLCC employment out of the Middle East related to total employment out of the region, based on dwt.
8) If only OPEC Middle East was considered, the number would be 42.0 %.
9) If only OPEC Middle East was considered, the number would be 40.7 %.
All numbers are percentage. The data take into account combined carriers trading with liquid cargo.
A comparison of yearly tanker employment data.
Table 17.7 Middle East for all the years considered is 81.4 %, based on tonne-miles. At the same time represented total large tanker employment 39.1 % of total tanker employment (based on tonne-miles). VLCC employment out of the Middle East constituted 31.8 % of total tanker employment (based on tonne-miles) for the years considered. As an average for the same years, total Middle East exports and OPEC Middle East exports represented 45.0 % and 42.0 % of the total international trade with crude oil and refined petroleum products, respectively. The weighted average of the VLCCs traded out of the Middle East for the years 1987 through 1989 was 84.6 %. For the same time period the weighted average of total large tanker employment represented 39.4 % of total tonne-miles. Middle East large tanker employment represented a weighted average of 33.3 % of grand total tonne-miles for the years 1987, 1988 and 1989. Total Middle East exports and OPEC Middle East exports represented 43.0 % and 40.7 % respectively, for the 1987 through 1989 period. Based on dwt, approx. 63 % of the total tonnage which were employed out of the Middle East region were represented by VLCCs.
Based on the sustained high activity level of the (OPEC) Middle East region, both with respect to tanker employment and oil exports, it is concluded that the Middle East is predominant with respect to VLCC employment, and that the production function(s), in a broader capacity utilization context and from a VLCC point of view, can be justified based on individual tanker movements.
Based on the provided (disaggregate) tanker and combined tanker trading data of Appendix B, it would be possible to analyse any changes in trading patterns for various tanker size categories, disaggregate and aggregate tonne-miles figures, various productivity factors for different size categories etc.
any related subjects are possible areas of further research.
FR bry | 1975 | 27.10 | 2760 | 1887 | 17.94 | 2561 | 1850 | 9730 1976 31.10 | 21.45 | 20.58 | 29.33 | 20.
1977 31.00 131.70 [21.62 |-20.48 129,39 20.
| 1978 | 2970 | 30.40 | 20.55 | 19.45 | 2798 | 1973 | 10546 | | 1979 | 3060 | 3150 | 2103 | 1995 | 2890 | 2043 | 10497 | 1981 15.
| i982 | 1820 | 1990 | 1229 | 11.08 | 1652 | 11.
1987 | 17.70 | 19.50 | 11.31 10.31 | 6016 1988 21.40 | 1335 | 11.22 | 16.76 6510 1989 | 21.80 | 23.80 | 14.30 | 1262 | 18.
X1 = OPEC crude oil production in mbd. Sources:
and various IEA Od Market Reports. X2 = Total OPEC crude oil and NGL production in mbd. Same sources as XZ Statistical Bulletin 1989 based on drect communmcations lo the OPEC secretanat, Twentieth Century Petroleum Statistics, De Golyer and MacNaughton, PIW, Weekly Petroleum Argus.
products) in mbd. Source(s).
National sources, OECD Quarterly Od & Gas Statistics.
X5 = Total OPEC exports (crude oil and refined petroleum products)
mbd. Same source(s) as X4.
X6 = Middle East Exports in mbd. Source: BP Statistical Review of World Fnergy, various Issues.
DTM = Aggregate tanker tonne-miles in mrd. (or billion). Source:
Fearnleys Review, various issues.
Table 1 App. Ch. 7 [Fromho [NEv SE:
F.E./Aus 14363 N.
Zables and Distance Tables by Norwegian Shipowner 's Association.
Distance matrix in nautical miles.
Fo | | fo re fre [v7] fer | ene 1.24E+11 231E+10 2.
Tonne-miles matrix for OBOs (trading with oil)
200.000 dwt in 1980. Table 3 App. Ch.
[ma (OT 2.41E+09 2.53E+09 Li 2.29E+09 7.
200.000 dwt in 1985. Table 4 App. Ch.
N.Am/Car 1.52E+10 9.86E+09 4.01E+10 7.62E+09 7.7E+09 0 1.56E+10 9.61E+10 22E+10 6.87E+09 1.99E+10 3.46E+09 291E+10 3.82E+09 7.43E+09 9.
LEN dt A i [OR 9.03E+09 [er | 4.
200.000 dwt in 1987. Table 5 Ch. 7 4.83E+11 ER 8.49E+10 5.79E+11 ra 9.
200.000 dwt in 1988. Table 6 App. Ch.
200.000 dwt in 1989. Table 7 App. Ch. 7 8.
comparison of the various empirical relationships.
In chapter 5 aggregate productivity, P. was derived as:
In order to calculate an aggregate quarterly productivity data series (by utilizing a iop-down approach), it is necessary to quarterlize several yearly time series, due to lack of such data series.
As long as only veariy OPEC Middle East consumption data are available (known to the author), quarteriv OPEC Middie East exporis data (SQPEC-ME q) are derived by subtracting annual OPEC Middle East consumption data from quarterly production levels (SQPEC-ME y) (ref. table ! App. Ch. 8).
From an aggregate point of view quarierly ionne-miles demand (DTM q)
are hypothesized to be adequately represented by the expression:
DTM q = DTM y [1- (SOPEC-ME 4 - SOPEC-ME y)/SInt.Tr. yl (8.2)
DTM y = Yearly tonne-miles data (which are calculated from trade statistics) Sint Tr.
Eguivalently, from an aggregate point of view, the denominator of 8.
Sirading (g)
and refined peiroleum producis. Vessels used (or not used)
operation (storage, repair etc.) are excluded.
on quarterly basic data from Lioyd's Mardata.
are provided in table 2 App. Ch.
Quarterly aggregate productivity figures for the q1 1987 io g4 1989 period.
Figure 8.1 The aggregate productivity has gradually improved over the period, from approx. 25.000 tonne-miles/dwt in q1 1987 to approx. 33.000 tonne-miles in q4 1989.
function of actual spot freight rates level.
productivity may be viewed as a constant or as a function of time.
The following expression for aggregate productivity is assumed:
P = aj+(trend) + a7 (8.4)
a1, a)
By applying OLS the following results are obtained, ref. table 8.1, based on quarterly time series for the 1987 through 1989 period: Estimated regression parameters.
By hypothesizing a linear relationship between aggregate productivity and trend, all the statistical parameters are significant (5 % significance level)
relationship may be used as an accepted hypothesis.
When aggregate productivity is used in predictive purposes, but treated endogenously, P may be hypothesized to be a function of spot freight rates and time.
The following expression for aggregate productivity is then assumed:
Pus a1 *(SFR)(1) + a2+(trend) (1) +a3 (8.5)
trend = Trend or time factor ay, ap, a3 are regression coefficients 1» 22:
By applying OLS the following results are obtained, ref. table 8.2, based on quarterly time series for the 1987 through 1989 period:
3 F  test(1,13)
By hypothesizing a linear relationship between aggregate productivity and spot freight rates and trend, all the statistical parameters are significant (5 % significance level)
residuals, and as such the relationship may be used as an accepted hypothesis.
The objective was to calculate a time series of an aggregate productivity factor as a parameter for the simple analytical model.
may be areas of further research.
In chapter 5 a general expression for spot freight rates, SFR, was derived to be: SFR = A[CAP]P (8.6)
S =F + (1-B)
(1-B)Sobo = Combined carriers trading with dry cargo.
Dir = Demand for trading tonnage = Dp/P*
refined petroleum products)
Dgy = Demand for (stationary)
To apply OLS regression analysis it is necessary to linearize equation 8.6.
On linearized or logarithmic form equation 8.6 becomes:
in SFR = InA + B[CAP] (8.7)
SFR = Spot [reight rates = In USD/tonne of oil for a 250.000 dwt TT VLCC AG-NWE.
A regression analysis (OLS) yields the following results, based on Intransformed data, ref. table 8.3:
| | Parameter estm. | T-statistie | Std. error | | 40723 10738 24142 19516 0.
Bi 0.59 F test(1,12) DW = 1.
All the estimated parameters are significant (5 % significance level) and the DW test indicates that there is no autocorrelation in the residuals. The R2 may be slightly low.
representation for the spot freight rates relationship and capacity utilization.
Actual spot freight rates (USD/tonne of oil) and model fit. Figure 8.
Figure 8.2 visualizes actual data and model fit based on equation 8.7.
The performed analysis is interpreted to be a confirmation of the hypothesis that SFR = A[CAP]P and that the capacity utilization term which has been developed, represents a causal representation of the tanker market, and as such can be regarded as a simple analytical model of the tanker market.
are beyond the scope of the dissertation and may be areas for further research.
may be assumed:
d(SFR)/d(CAP) = a[SFR - c] (8.8)
SFR =e b+ a(CAP)
where e = 2.71828...
SFR = e b + a(CAP) . e b (8.9) Which says that SFR is an exponential function of capacity utilization.
The following specific expression for spot freight rates may be assumed:
SFR = e 4 "CAP + ap (8.10)
ap = 0, to make equation 8.10 equivalent to equation 8.
SFR -> 0 when CAP -> 0.
SFR = Spot freight rates = In USD/tonne of oil for a 250.000 dwt TT VLCC AG-NWE.
A regression analysis (OLS) yields the following results, based on Intransformed data, ref. table 8.4:
F-test(1,13) 135.
The actual time series are provided in table 3 App. Ch. 8 and table 4 App. Ch. 8. In addition to the stated data, the value: SFR = 0, CAP = 0, has been introduced.
(Based on the original data series, SFR =ea!CAP, a1 = 2.204 with t-stat = 38.87, F-test = 8.66, DW = 1.55, R2 = 0.44)
Actual spot freight rates (USD/tonne of oil) and model fit. (Points #2 to # 13 represent q1 1987 to q4 1989.)
SFR = Spot freight rate = T/C equivalent VLCC spot rates in USD/day for a 280.000 dwt TT VLCC built in 1975, average for Ras Tanura-Rotterdam/L OOP.
A regression analysis (OLS)
transformed data, ref. table 8.5:
fær da 7 der.
| R2=0.95 F-test(1,13)=230.4 | DW=1.11 fro tom).
Table 8.5 The actual time series are provided in table 3 App. Ch. 8 and table 4 App. Ch. 8. In addition to the stated data, the value: SFR = 0, CAP = 0, has been introduced.
(Based on the original data series, SFR =e21CAP, a1 = 10.41 with t-stat = 51.77, F-lest = 5.48, DW = 1.11, R2 = 0.33)
Actual spot freight rates (USD/day) and model fit. (Points #2 to #13 represent q1 1987 to q4 1989.)
Figure 8.4 visualizes actual data and model fit based on equation 8.10.
Originally specified SFR!) = e2-41[CAP]4-07 | 0.
model, based on eq. 8.
Alternatively specified | SFR1) = ¢2.204[CAP] 10.92, 0.
models, based on eq. 8.
SFR2) = ¢10.41[CAP] |0.95,0.
1) SFR = Spot freight rates in USD/tonne of oil for a 250.000 dwt TT VLCC. 2) SFR = Spot freight rates as T/C equivalents in USD/day for a 280.000 dwt TT VLCC.
A comparison of the various models.
Table 8.6 summarizes the findings related to the originally specified model (equation 8.7) and an alternatively specified expression (equation 8.9). The alternative model has been specified for two different concepts for spot freight rates; in USD/tonne of oil, as the originally specified model, and as T/C equivalents in USD/day. Both cases have been analyzed with the original data series and with the introduction of an additional data point (SFR = 0, CAP = 0).
For both the alternative models all the statistical parameters are significant (5 % significance level) and the DW tests indicate that there is no autocorrelation in the residuals.
(0.92 and 0.95, respectively).
With the original data series the R2s become rather small (0.44 and 0.33, respectively), eventhough the statistical parameters are significant (5 % significance level). The statistical results associated with the hypothesized model(s), may confirm the stated hypotheses, but the introduction of an additional data point may be questioned.
The same comments about further research associated with equation 8.
to the alternative model.
OPEC ME| OPEC ME! OPEC ME! OPEC ME'Intern. crude prod. (1)
Sources: (1) IEA. (2)
communications lo the OPEC secretarial, National Sources, IEA, World Energy Statistics and Balances, UN Energy Statistics Yearbook, OAPEC Report. (3) OPEC Statistical Bulletin 19589, based on direct communications to the OPEC secrelarzal, UN Energy Statistics Yearbook, National sources, OFCD Quarterly Od & Gas Statistics. (4) BP.
(*) Derived by the author.
Some quarterly time series.
yearly (109)
(1) (109) (*)
1987.1 221.9 24945.48 | 19872 987.3 29263.37 987.4 ETE. 28502.
27005.
D *) 219 1988.1 6510 27650.05 19882 29146.54 988.3 29919.78 | 19884 315754 986.1 304114 1989.2 31291.08 19893 31900.
(1) Source:Fearnleys (*) Derived by the author.
ill. dwi Tanker i Capacity supply (1) trading with | storage (3)
| | + lows — 12306333 [ins — [1520667 Joss | [19881 — 12400667 — |23.3667 — [1362333 — [084555 | lioss2 — 12416333 [259667 [1316  |osssoy | h9ss3 — [240367 1235 — [120353 — [oser | | 1988.4 1989.
Sources: (1), (2) Lloyd's Mardala, (3) Howard Houlder. (*) Derived by the author.
FK pt Fo vasa ewan on Augie 2 pnt vie misao)
je fan — | Tri rr ho fk:
(1) Spot freight rates for 250.000 dwi TI VLCC AG-NWE. Sowrre:
Lloyd's Skipping Economist. (2) Spot freight rates for 280.000 dwt TT VLCC built 1975, average for Ras Tanura - Rotterdam/LOOP. Sowve: P.S. Platou Fconom Research.
Table 4 App. Ch. 8 9.
The overall objective of this chapter is to pinpoint the concept of adjustments or sensitivities (bottom-up analysis) to the production function(s) (top-down analysis) (ref. section 4.5 and chapter 7). This in respect to the use and disuse of (possible) crude oil pipelines in the Middle East, in the context of possible political events in the region (ref. section 3.6), in relationship to available production capacity of the various Middle East OPEC producers.
on the identification of pipelines.
A discussion of the OPEC oil resource situation and an analysis of the various crude oil capacity terms, and an outline of how particularly sustainable capacities and actual production levels have developed over time, are provided. Also, estimates are provided of OPEC as a whole and individual OPEC members' crude oil sustainable production capacities up to the late 1990s (1997-1998). Throughout the analysis the Middle East OPEC members are emphasized. This is followed by a discussion of operational, inoperational and closed crude oil pipelines, and possible new pipeline projects in the Middle East are assessed. The consequences with respect to tanker demand (tonne-miles consequences)
due to the use of some of the pipelines, are analyzed.
possibility of bypassing the Strait of Hormuz by means of crude oil pipelines, was frequently reproposed not only by Iran, Iraq and Saudi Arabia, but also from other oil exporters in the Middle East.
After the Iraqi invasion of Kuwait on August 2, 1990, and the subsequent UN (oil) embargo of Iraq, the whole question about OPEC production capacities in general and export capacities in particular has been reemphasized.
may be of vital importance for the tanker market.
Intertanko (1988) addressed the question about possible impacts to the tanker market due to the use of crude oil pipelines in the Middle East. The analysis of this subject by the author differs from the Intertanko study by:
- The starting point is production capacity for the individual OPEC Middle East countries and possible future oil production capacity for the same nations. The Intertanko study did not have any references to production capacity.
- The Intertanko analysis was incomplete with respect to closed, operational, inoperational and proposed pipelines. It did not consider canal expansions.
- Intertanko did not relate any possible consequences to a production function.
is generally the highest capacity estimate.
crude oil production, processing and transportation.
capacity term is available capacity.
This reflects the production that relatively instantaneously can come onstream from wells and facilities (gas-oil separating plants, main trunk pipelines, oil loading terminals) and which could be maintained for three months. Daily production rates could exceed this level. The most common capacity concept is (maximum) sustainable, sometimes called output or operational capacity. This is the maximum production rate that can be sustained for several months (one year).
within design rates and production practices that avoid damage to oil reservoirs.
The total installed crude oil capacity within OPEC is (was) 41.13 mbd. The major share of this capacity is among the Middle East OPEC members, 30.28 mbd or 73.6 % of the total OPEC installed capacity. Saudi Arabia is the OPEC member with the highest installed capacity, 12.5 mbd or 30.4 % of the historically installed capacity belongs to this nation. Outside the Middle East area it is Nigeria, Libya and Venezuela which are in possession of the largest installed capacities.
As seen from table 9.1 there is a good (non-statistical) correlation between resources (proved oil reserves) and capacity. OPEC Middle East is the holder of 84.5 % of the OPEC proved oil reserves, of which Saudi Arabia has the proprietorship of 33.5 %.
Venezuela which are in possession of the highest conventional oil reserves.
(mbd) (1)
% of total |Proved (2) reserves (x1000 mill.bbl)
(years) (6)
30.4 258.70 335 89.5 ns)
17.0 92.90 12.0 70.
9.7 100.00 13.
62 98.10 12.7 123.
7.1 94.00 12.2 139.
1.6 5.00 0.6 34.
3.70 0.5 25.
652.40 84.5 105.
2.50 6.1 17.90 23! 33.
2.50 6.1 22.
OPEC total Sources: (1) Central Intelligence Agency (CIA), International Energy Statistical Review, October 28, 1956. (2) Od & Gas Journal, December 27, 1993.
(3) Excluding share of capacity in the Neutral Zone. (4) Abu Dhabi, Dubar, Ras al Khaimah, Sharjah. (3) Capacity is shared equally between Kuwail and Saudy Arabia. (6) Based on production figures from table 9.2.
Installed OPEC crude oil capacity and proved oil reserves. Table 9.
jor | 0.61 (Dec 75) (1)
OPEC 27.14 21.95 16.
Middle East 2.
fa 221 (ape 7 = |Algeria | 1.16 (Dec 78)
[Gabon | 0.34 (Aug 99)
Sources: (1) CIA, Oclober 25, 1956.
(2) Petroleum Intelligence Weekly (PIW), February 4, 1950.
(3) 7W, February 10, 1992.
(4) August 7994 production, PIW's Global Oil Stocks & Balances (GOSB) September 1994.
(3) Comprises lotal Neutral Zone production (which is shared equally between Saudi Arabia and Kumwail).
OPEC crude oil production levels. Table 9.
As seen from table 9.2, the aggregate of the post 1973 oil embargo production peaks of the individual countries is 37.42 mbd or 91.0 % of overall installed capacity. The individual peak production levels were obtained in the December 1975 to August 1994 period. 27.14 mbd or 72.5 % of the sum of the individual production peaks are represented by OPEC Middle East production.
The highest individual production was by Saudi Arabia, which crude oil output was recorded in August 1981 at 10.3 mbd.
The collective OPEC crude oil production reached its peak in July 1979 at 31.64 mbd (excluding NGL production of 0.9 mbd). 21.95 mbd or 69.4 % of this production was from the Middle East.
Figure 9.1 visualizes OPEC Middle East and total OPEC crude oil production for the 1983 to 1994 period.
Sources: [EA Oi Market Report, PIW, various issues. OPEC Middle East and OPEC non-Middle East oil production.
Figure 9.1 assumed that the OPEC spare production capacity would be sufficient to provide the necessary balance between world oil demand and non-OPEC oil supplies over the next 10 to 15 years. This was certainly true in June 1985, when OPEC oil production had dropped to 14.08 mbd (excluding 0.95 mbd of NGL production).
feos Jo laser yon Taos åsen Toon fin) hes.
Source(s): PIW-various 15SUes. (Representative) OPEC sustainable crude oil capacities (mbd). Table 9.
With reference to table 9.3, the total OPEC sustainable capacity was reduced from 39.22 mbd in 1979 to 26.83 mbd in June 1985, a drop of 12.39 mbd or 38.6 %. In this period the biggest capacity losses were recorded in Iraq and Iran. Iraq's capacity fell percentage wise most, from 4.00 mbd in 1979 to 1.3 mbd in June 1985, a 2.7 mbd drop or 67.5 % over the period.
Falling oil production and prices in the 1980s, and subsequently reduced income, and very high reserve to production ratios for the major market players, were all elements that provided little incentives to invest in maintenance of production capacity.
terminals, pipelines etc.).
OPEC sustainable capacity increased about 0.6 mbd from 1985 to 1990. The net increase of 0.6 mbd was primarily caused by a 1.5 mbd decrease in the Saudi Arabian output capacity and a 2.0 mbd increase in the Iraqi (exports) capacity. The 1990 sustainable capacity was estimated to about 27.2 mbd, with 19.0 mbd as sustainable OPEC Middle East output and 8.15 mbd as operational capacity for the rest of the organization, ref. table 9.4. The available 1990 year-end capacity was estimated by the IEA to be in the 19.6 to 20.1 mbd range for the OPEC Gulf Area, while total OPEC available crude oil capacity was stated between 28.1 mbd and 28.6 mbd. The August 1994 OPEC Middle East sustainable capacity was 19.53 mbd, up from16.18 mbd in November 1991 primarily due to an increase in Kuwaiti sustainable production capacity from 0.35 mbd to 2.15 mbd. (It would have been 22.23 mbd with 1990 sustainable capacity for Iraq.) The total OPEC sustainable capacity was 28.10 mbd in August 1994. (And equivalently it would have been 30.
sustainable capacity for Iraq.)
Based on tables 9.2 and 9.4 and figure 9.
very near) their production capacities.
pm SS Janae 060 5 2.
loPEC 28.32 19.03 19.6-20.1 19.53 (9)
| Gabon 0.25 0.23 0.
oe OPEC total 27.17 28.1-28.6 28.10 (9 Sources: (1) PIW, March 12, 1990. (2) Arithmetic average between data from CIA, February 27, 1990 and PIW, March 12, 1990. (3) International Energy Agency (IEA) Od Markel report, October 1990, Supplement. (4) GOSB, September 1994.
(3) Limited by UN embargo.
(6) Originally included in the Saudi Arabran and Kuwaiti capacity figures.
(7) Excludes onshore production.
(8) May not add due to rounding.
(9) With 1990 (pre-invasion) sustainable capacity for Iraq and Kuwar, Middle East sustainable capacity would be 22.23 mbd and total OPEC sustainable production capacity would be 30.50 mbd.
1990 and 1994 sustainable and available capacities.
Between June 1985 and first half of 1989 OPEC crude oil production (and residual demand at current crude oil prices) increased by 6.6 mbd to 20.7 mbd. At this point in time there was a positive outlook for increased call on OPEC crude oil. Prior to the 23-27 September 1989 meeting of OPEC's eight member Market Monitoring Committee (MMC))D, there were discussions about how to allocate incremental increases to existing quotas. Several "scientific criteria" were proposed; e.g. idle production capacity, crude oil reserves, historical output, population, external debt.
The meeting agreed on a 1.0 mbd quota increased on a pro-rata basis, but the process before the meeting may have contributed significantly to the subsequent increase in planned crude oil capacity enlargements. Particularly Saudi Arabia, Iraq, Iran, Kuwait, UAE and Venezuela had all announced plans to increase their production capacities up to the late1990s.
*)See section 11.2 (Notes).
new wells in existing fields, restoring gas injection facilities and pipelines etc.
Saudi Arabia published 2) plans to raise the country's sustainable crude oil capacity to 10.0 mbd by 1995 +. The capital costs associated with this expansion plan is USD 16.7 milliard (mrd) in current dollars or USD (1990) 12.5 mrd. (10% discount rate). After the Iraqi invasion of Kuwait on August 2, 1990, Saudi Arabia decided to accelerate its crude capacity expansion program 3). The aim was to be capable of producing 10.0 mbd on a sustained basis in 1992 rather that 1995 as originally scheduled. Most of the immediate increase in capacity came from already producing fields, but some smaller, shut-in fields will probably be revived later in the program. Ghawar and Abqaiq medium and Safaniya heavy grades form the bulk of the rise. But there will also be increases or reopening of crude flows from onshore Khurais and Abu Hadriya and offshore Qatif, all of which produce 33 to 34 API gravity oil, presumably adding somewhat to the Arabian Light crude steam.
oil finds in the central region are separate from the expansion program.
Iraq had most of its exports capacity, and not production capacity, damaged during the eight year long war with Iran. The total (potential) Iraqi pipeline export capacity is 3.15 mbd. In 1990 the war damaged Mina al-Bakr offshore terminal was parily reopened with an exports capacity of about 0.35 mbd. A complete reopening of both the (war damaged) oil loading terminals Mina al-Bakr and Khor al-Amaya, could add about 2 mbd of exports capacity. Together with a single buoy mooring system with 0.6 to 0.8 mbd of capacity, Iraq's exports capacity could reach 6 mbd in the late 1990s and outstrip output capacity (when the UN embargo ends).
Iran had problems repairing and restoring onshore gas injection facilities (after the war with Iraq), particularly related to the Marun and Gach Saran fields. The country has also had severe difficulties solving mounting water encroachment problems. A major gas injection plan could boast Iran's production capacity by 1.0 (+) mbd, but it would be costly (USD 2-5 mrd.) 4). More concrete plans for output expansions were outlined by Iran's Minister of Petroleum, G. Aghazadeh 5). By repairing offshore fields damaged during the war and expanding onshore capacity, total production capacity could be expanded by 0.5 mbd and 0.4-0.5 mbd respectively. The country announced revised plans ©) 7) to increase its crude oil capacity. The previously publicly stated target of adding 50 % to potential output to 5.0 mbd by mid 1990s and the new goal of 5.5-6.0 mbd of capacity by the end of the decade, is considered overly ambitious by many.
spending will result in a rapid jump in onshore capacity to more than 4.1 mbd.
Before the invasion, Kuwait had a 5 year program to increase its crude oil production capacity by (approx.) 1.2 mbd to 3.5 mbd. Yearly additions of 0.2-0.3 mbd were scheduled. This program was a reversal of the country'
from the early 1970s to reduce capacity in order to conserve reserves.
For UAE, and for Abu Dhabi in particular, there were plans to increase production to about 3 mbd by 1994 9). Later 10.11) it was learned that Abu Dhabi was expected to raise ifs sustainable production capacity to 2.4-2.
by 1995.
[PIW 12) reported that construction contracts were awarded to upgrade and expand water-injection facilities associated with the Bab Structure, also, firms had been invited to bid for the design phase of the Bu Hasa gas-injection scheme, which will increase capacity by 0.1 mbd to 0.55 mbd.] The aim was to take onshore sustainable output to 1.3 mbd from a 1990 level 0.62 mbd. Onshore crude is marketed as Murbank blend. Offshore expansion centres are on the Upper Zakum field.
capacity is right on schedule.
Among the other significant OPEC producers, the Libyan situation is unclear. The oil Minister F. Shakshuki stated 13) that the output capacity could be raised within six months to 1.8 mbd. It has become evident 14) that due to financial constraints, it will be impossible to reach the target of 2.0 mbd from the capacity level at the end of 1994 of 1.45 mbd. At a conference 15) representatives from Venezuela and Nigeria outlined their countries' crude oil capacity expansion programs for the late 1990s. For Venezuela the expansion plan was underway before the Iraqi invasion of Kuwait, but "the crisis only confirms the need to carry on with the program". The Venezuelan plan outlined an increase in crude oil production capacity to more that 4 mbd before the end of the century. The General Assembly of Petroleos De Venezuela (PDV) approved 16) plans to expand the country's crude oil capacity to 3.25 mbd by 1995 +. The new PDV president G. Roosen 17) admitted that due to financial constraints, the company would have to set a more sedate pace in its expansion plans but that the basic programme prevailed. Later 18)
postponement of the capacity increases.
Nigeria planned an increase in crude oil production capacity.
0.3-0.4 mbd by late 1994 to approx. 2.1 mbd.
| 0 om) 70 > nmoumeerleg] gg 00 plus gå] J)
24.15| 23.45-25.25 26.1-27.6 19.
| Middle East Rr 23)
a Nr — oms] os) om fanen.) rr B28) coil bop] 1 — es see ae findonesia | — 160] uw] ul åa] Jorec omr | 998] 10320) — 90] ss (OPEC total | 3368] 3340-3570] 360375] 28.10 (30.8)
Sources: (1) Fesharaki (January 19589) (2) PIW. March 12, 1990 (3) Author's estmale for the late 1990s. (4)
included with the Saudi Arabian and Kuwait figures. (5) August 1994 sustainable production capacity, GOSB, September 1994 (6) Same as (5) but with pre-znvasion sustainable capacity figure for Iraq.
Late 1990s (1997-1998) OPEC crude oil sustainable capacity projections. Table 9.5 capacity will come onstream in the Middle East. The OPEC Middle East sustainable production capacity could reach 26.1 to 27.6 mbd by the late 1990s. This would represent an increase of 3.9-5.4 mbd compared to the mid 1994 figure. In mid 1994 19) the region had reached a sustainable capacity of approx. 22.2 mbd including Iraq at prewar capacity. For OPEC as a whole the total sustainable capacity could add up to between 36.0 and 37.5 mbd by 1997-98. This would be between 7.9 and 9.4 mbd higher capacity than the mid 1994 level. In mid 1994 the organization had reached 28.1 (30.8) mbd of sustainable capacity. As seen from table 9.5, the compiled capacity projections by the author are higher than what are published by earlier sources. This may be an example of the dynamics associated with OPEC production capacity increases and the role of politics of the region.
producers.
From the previous discussion it is also quite evident that the predominance of the Middle East region of OPEC will tend to increase.
With reference to table 9.6 there are 8 operational oil pipeline systems in the Middle East, including two internal pipelines in Oman, one in Syria and one in Jemen. In addition we have the 3 Iraqi pipelines, which are not in use due to the UN (oil) embargo, but which otherwise could have been operational.
figure 9.2.)
From an oil market point of view the most important pipeline in the Middle East is the Saudi Arabian East West pipeline (Petroline). The line goes from Abqaiq/Ghawar to Yanbu. The 1200 km and 48 in. diameter line began operations in 1981 with a capacity of 1.85 mbd. This capacity was increased to 3.2 mbd in 1987 by adding a 56 in. pipe, and again in 1992 to 5.0 mbd by increasing the pressure in the pipeline. In addition to these two pipelines, Saudi has a parallel 26 to 30 in. diameter NGL pipeline with a capacity of 0.27 mbd. All these pipelines are labelled Petroline20).
Before the Iraqi invasion of Kuwait, the total capacity utilization rate of Petroline was about 50%. During the Iranian/Iraqi war Iraq obtained a throughput right of 0.5 mbd related to Petroline. This flow was supplied through the Iraqi pipeline from Rumaila (Iraq) to pump station 3 (PS 3) of the Petroline-system.
The Iraqi pipeline Trans-Saudi Arabia (IPSA-2) became operational in 199021). IPSA-2 goes from PS 3 to Janbu in Saudi Arabia. The capacity of this pipeline is 1.
3 (with an initial capacity of 0.5 mbd).
The IPSA system was completed in two phases. Work on IPSA (-1) started in 1984 and was completed in 1985, securing the delivery of 0.5 mbd of Iraqi crude oil on Petroline. The second stage, IPSA-2, aimed to increase the capacity of the pipeline to 1.65 mbd and to create a complete and integrated exports system from Zubair in southern Iraq to Mu'ajjiz, SO km south of Yanbu. IPSA-2 represents the extension of a 960 km 56 in. diameter pipeline from end of IPSA-1. The total length of the pipeline system is 1575 km, the largest crude oil pipeline constructed in the Middle East. The loading terminal at al Mu'ajjiz can handle vessels up to 500.000 dwt22).
Iraq had two tanker terminals in AG; Mina al Bakr and Khor al Amaya, each with an exports capacity of 1.6 mbd. Both were destroyed at the start of the war between Iran and Iraq in 1980. Khor al Amaya sustained the greatest damage and is not regarded as a prospect for restoration in the foreseeable future. After the war ended in 1988, the capacity was briefly restored to 0.8 mbd before it was shut down once again following the Iraqi invasion of Kuwait. In addition to Mina al Bakr, Iraq has four Single-buoy mooring (SBM) oil loading facilities. These four SBMs could increase exports capacity by 1 mbd23). It is unknown if these SBMs survived the military confrontation during the allied recapturing of Kuwait.
Iraq's "Strategic line" used to be reversed, and was part of the Irag/Turkey pipeline system before it became inoperational. Of the 1.4-1.5 mbd of crude oil throughput in the "Strategic line", about 1/3 used to be the crude oil Basra Light and 2/3 used to be the oil quality Kirkuk.
The tanker terminals and the SBMs should probably be viewed in the context with the Iraqi-pipeline from Rumaila to the Faw Peninsula.
viewed as a part of the "Strategic line".
The Eliat - Ashqelon pipeline in Israel was built after the Suez Canal was closed in 1967. After the Canal was reopened in 1975 and the Sumed pipeline in Egypt was completed in 1977, the need for this Israeli pipeline diminished and has been used only for domestic Israeli purposes. However, its commercial use has been reignited 24) and expansionary work are under way.
pipeline. In mid 1994 total capacity was scheduled to have reached 2.3 mbd, with a throughput of 2+ mbd 25).
po Start-End mer es) Yr. Remarks mbd compl.
| Kirkuk (Iraq) - Ceyhan (Dortyol)
» |Mostly completed.
Sumed line, Suezincreased from 0.
mbd to 0.
oa Kangan Taher mer |m…  Jorm om. Jemen, Alif - Saif | Alif - Salif mm 1987 Operational in 1988.
IPSA-2, to Second step of the (Mu'ajjiz)
(Aqaba)
hgelon (Israel) ere | use.
Sources: "Pipelines in the Middle Fast' unpublished, [FA 1987. Petroleum Economist Map of Middle Fast Od and Exports Routes, 1990. The Oi Day; Special Report, September 1989 Middle Fast Economic Survey (MEES), January 15, 1990, MEES, April 16, 1990, MFES, September 17, 1990, PIW, June 13, 1994.
(*) Not in use due to UN (oil) embargo.
Operational and inoperational pipelines in the Middle East.
ddle East.
Source: Petroleum Economist, 1990.
Map of the M 9.
There are 4 closed pipelines in the region, ref. table 9.7. The pipeline from Iraq to Haifa was closed permanently in 1948 by the first Arab-Israeli war. Both the Iraqi lines to Tripoli (Lebanon) and Barias (Syria) repeatedly fell victim to Syrian-Iraqi antagonism. In 1966, Syria raised transit fees, demanded payment for retroactive charges, and closed the line until its demands were mel. Syria raised its fees again in 1972 and 1976, at which point Iraq discontinued shipments. The line was later reopened, but was closed entirely in April 1982, CERA (1986). Part of the Barias line has been used by Syria for domestic transportation.
In 1990 the Syrian and Lebanese Governments finalized an agreement for the supply of 20.000 b/d of Syrian Light crude oil to the Tripoli refinery in northern Lebanon through the existing pipeline to Tripoli. This was the first time since 1982 that this section of the pipeline was used26).
Aramco built the Trans-Arabian Pipeline (Tapline) to avoid Suez Canal transit fees. Later, transit fees on Tapline's oil, imposed by Syria in particular, undermined the line's economic value. The pipeline was damaged several times during the 1970s, and it was finally closed in 1983 as a complete operational pipeline. It was partly reopened in 1990. In August 1990 the Jordanian Oil Ministry announced27) that Jordan would receive 3.000 b/d of Saudi oil via Tapline.
It has been reported that the Israeli Energy Minister Shahal 28) had proposed the reopening of the Tapline to several OPEC states.
further advancements of the Middle East peace process to materialize.
compl.
Closed and reopen several times in the 1970s. Finally closed in 1983.
Sources: "Pipelines in the Middle East", Mille Fastilimpublisked "IBA . [EA 1987. Petroleum Economist Map ol Middle East Oil and Exports Routes, 1990.
Closed pipelines in the Middle East.
Table 9.7 In 1989 it was clear that Saudi Arabia would go ahead with plans to increase the capacity of Petroline to 5.0 mbd by late 1992, as a part of the strategy to increase crude oil production capacity to 10.0 mbd and provide added flexibility to shift crude oil exports to the Red Sea (bypass the Straits of Hormuz)29.30). The increased capacity from 3.2 mbd to 5.0 mbd was carried out by adding two new pumps at each of the lines 11 pump stations.
As previously mentioned, the expansion of the Sumed crude oil transit pipeline to a design capacity of 2.
199425), The Sumed expansion plan included the construction of two booster pumping stations at Dahshur, south of Cairo, midway along the two parallel 42 in.-diameter 320 km pipeline system, and the expansion of storage and loading facilities at both ends of the line. New SBMs will be installed to allow tankers up to 500.000 dwt to unload crude oil at the Ain Sukhna terminal south of Suez town, and 350.
Mediterranean.
About 15 proposed pipeline projects in addition to Suez Canal expansions have been identified, of which several are in tandem or are interconnected, ref. table 9.8. Most of these proposed projects have been discussed for years without being seriously considered.
In 1992 31) new discussions emerged about a 1.0 mbd pipeline from Iraq's K-3 pump station to Aqaba (Jordan). The Talks were based on the US engineering company Bechtel's plans from the mid 1980s for such a pipeline. Real progress in such talks will probably not take place before the UN sanctions are lifted.
Of the different Iranian pipeline projects, the Iran/Turkey line is subject to "further studies", in part because of Teheran'
USD 2.5 mrd. cost32). A "Letter of Intent" between Iran and the Italian company Saipem was signed in 1988 for the construction of a pipeline from Gach Saran to Taheri33).
The proposed pipeline to Jask was shelved in 1986 by Iranian authorities34), but rumours have emerged quite frequently that this project would be reconsidered. This is symptomatic for most pipeline projects in the Middle East; "a lot of talk but less action".
A contract to construct an export pipeline from the oilfields in the Masaila Block in the eastern part of Yemen has been awarded to the Canadian company Oxy Offshore Int.35). The initial capacity of the pipeline will be 0.2 mbd, and with additional pump boosting it could be expanded to 0.45 mbd. The contract calls for the construction of about 150 km of 24 in-diameter pipeline. The plan also entails the construction of 2 mill.
installed to accommodate VLCCs.
The first expansion programme of the Suez Canal, which begun in 1975 and was completed in 1980, deepened the waterway to handle vessels up to 150.000 dwt to transit. After this expansion all large tankers can be accommodated in ballast. Plans to expand the Suez Canal, at an expected cost of between USD 0.7 and 1 mrd. have been seriously considered, but are being delayed30) awaiting new studies on the effect of US maritime safety laws. Consultants, led by Nedeco of the Netherlands, are to advise Egypt on whether to back plans to increase the transit draught maximum for fully laden tankers to be suitable for 250.000 dwt, or even 280.000 dwt ships.
Other projects than the newly completed projects (Petroline, Sumed expansions, Yemeni line)
Eliot-Ashqelon pipeline.
Iraq, Haditha - Aquaba|0.5-1.
Israeli non-attack assurance.
"Letter of intent"
lack of financing.
Iran, Gach Saran -|1.0 100 Taheri Iran, Gach Saran - Jask | 1.0 - 2.
of financing.
line, Kuwait, | 2.
Saudi - Cameroon 4.
Kuwait - Janbu (Saudi) | 0.5 (Option 1)
Egypt, trans - Sinai N/A 150 Realization doubtful.
Iran - Turkey (Dortyol) | 1.0 1860 "Further studies", lack of å financing.
Iran, Gurreh (Kharg) 10.6 +0.4 380 Realization doubtful.
Iran - Soviet - Black|0.
Sea realization doubtful.
Abu Dhabi - Dubai -/0.5-0.8 1300 Uncertain.
Oman, Mamul - Kuria|0.3 33 Uncertain.
Realization doubtful.
Not realistic.
To be completed by 1994.
To be completed 1995/96.
Sources: Pipelines in the Middle East" unpublished, IEA 1987. Petroleum Economist Map of Middle East Od and Exports Routes, 1957, 1990. PIW, April 11, 1988. MEES, April 25, 1985. MEES, August 22, 1955. MEES, Seplember 5, 1988. MEES, July 1, 1991. MEES, January 27, 1992, MEES May 18, 1992, PIV, June 13, 1994, Business Week, May 23, 1994.
Proposed pipelines in the Middle East.
The worst possible scenario with respect to large tanker demand would probably be the total closure of the Straits of Hormuz. The total width of the Strait is about 48.5 nm. South of Didamar the maximum depth is 214 m. North of Didamar the water is more shallow. The Strait is practically impossible to block by sinking oil tankers. Shore based guns may be capable of shelling tankers, but such guns should be easy to eliminate by naval or air forces if such an event should occur. During the later part of the Iranian/ Iraqi war, Iran installed Chinese "Silkworm missiles" on their side of the Strait, but they were not knowingly in use. Placement of large numbers (several hundred?) mines could effectively block the VLCC/ULCC lane(s), but such a large mining operation would probably be detected and stopped. Due to pure topography, it is doubtful that national or irregular military forces would be able to block the VLCC lane(s) of Hormuz.
Hormuz is not analyzed further.
Due to the high level of tension in the Middle East the construction of pipelines are at first hand often politically rather than commercially motivated. At the same time past experiences with pipelines over foreign territory are not particularly advantageous for the proprietary country.
The construction of new pipelines or the expanded use of existing ones may reduce the need for long haul transportation.
may be difficult to assess.
With reference to table 9.9, when the UN (oil) embargo against Iraq is lifted, tanker demand may differ 387 mrd. tonne-miles, depending whether 1 mbd of oil is exported from Ceyhan with destination Rotterdam or from AG. This represents about 4.3 % of total tanker demand (based on total demand of 9025 mrd. tonne-miles in 1993).
—" N.Eu (Rotterdam) |)
| Tanura (via Cape) To:
fromne-mmies >=" æsuD 0 Teoh |] [Distance from Ceyhanfo:
Difference in tonne-miles when exporting 1.0 mbd from Ceyhan (Turkey) instead of from AG (Ras Tanura is used as a reference point instead of Mina al Bakr).
With reference to table 9.10; if 1 mbd of oil is transported from AG to South Europe via Suez (carried on VLCCs northbound through an expanded Suez Canal or shipped to Ain Sukhna and transported through Sumed) instead of via Cape (of the Good Hope), the difference (reduction) in tanker demand is 304 mrd. tonne-miles. By shipping 1 mbd from Yanbu [by increased throughput of Petroline or a possible Kuwaiti -Yanbu (option 1) pipeline] to North Europe via Suez instead of via Cape, the difference in tanker demand would be 365 mrd. tonne-miles. The tonne-miles consequences of some (additional)
projects are outlined in table 9.11.
S.Eu = Fos/ Marseilles, N.Eu = Rotterdam, N.Am = Houston/LOOP.
(*) Difference in tonne-miles for sailings via Cape vs. via Suez.
(**) Difference in tonne-miles for sailings via Cape vs. from Yanbu (Red Sea) and via Suez.
Difference in tonne-miles when exporting 1.0 mbd from AG (Ras Tanura) via Cape of the Good Hope (Cape) vs. via Suez and from Yanbu (Red Sea) via Suez.
sim — form distance (am)
(*) With destination west via Suez.
Tonne-miles consequences per 1.0 mbd due to the use of some possible pipelines in the Middle East.
Table 9.11 The use or disuse of oil pipelines has a significant impact on tanker demand. The long lead time associated with possible pipeline (or canal) constructions, will provide time to analyse possible consequences thoroughly. Within a scenario planning approach (ref. chapter 3), political events may be assessed and possible consequences with respect to tanker demand due to alteration of oil flows could be calculated in (he context of available (OPEC Middle East)
capacities.
An analysis of the supply of oil from the Middle East from a large tanker management perspective has been provided.
To promote options planning, understanding and behaviour within the organization of a tanker company, the scenario approach to both market analysis and planning has been encouraged. The approach might help both the decision maker and the planner to anticipate and understand risk, as well as it may help to discover both short and long term options. The volatile nature of the Middle East region; politically - oil market wise, and subsequent impact on the tanker market, are all elements which may encourage the scenario approach. A general beginning-state-driven developmental analytical (and heuristic scenario)
tanker market, with emphasis on the OPEC Middle East supply situation.
The analytical procedure is represented by the following steps: 1. Define the scope of the analysis. 2. Based on various assumptions oil demand projections are made. The techniques which can be applied are: - naive extrapolation - time series analysis - econometrics - market surveys - bottom-up 3. Forecast(s) of the non-OPEC oil supply is provided, where the above analytical methods may be applied. 4.
the demand for OPEC oil is derived.
production function of chapters 4 and 7, all key market variables are assumed identified. Basic assumptions related to these key parameters are stated.
6. Impacting events are identified with particular reference to the Middle East.
7. The impacts (consequences) of certain events are estimated. Particular reference is made to chapter 9 about possible alteration of the oil flow due to events in this particular region.
8. Check for consistency and/or cross impacting events.
9. Make spot freight rate forecasts (scenarios).
10. Iterate forecast if results are inconsistent with assumptions.
11. Analyze consequences.
12. Evaluate strategic implementation.
with an overall emphasis on the OPEC Middle East situation.
The proposed generalized analytical procedure is not tied to any formal mathematical algorithm, and as such it represents a heuristic approach.
to bound uncertainties.
superstructure of the thesis.
non-OPEC supply.
The cartel behaviour (oligopolistic dominant firm) was tested by an alternative aggregate approach.
supply or behaviour.
cartel behaviour:
(SP)=e0.049'(0SP)+0.678t(SP/OSP). 1 + 1.247" (Dagj/S) [USD/bbl] (10.1)
(18.65) (6.68) (9.95)
Dagj = Adjusted demand for OPEC oil = D; + actual OECD company stocks -desired OECD company stocks)
= world consumption (world outside former centrally planned economies)
economies + processing gains + NGL production etc.) (Desired company stocks);
All coefficients and the F-test are significant at a 5 % significance level. The coefficient of multiple determination, R2, is very high (0.93).
statistical results were taken as a confirmation of the hypothesis.
What the expression (eq. 10.1) really tells is that the spot price for oil (Arabian Light) is dependent upon a target price, the ratio of spot price to target price in previous quarter, which may be interpreted as the disequilibrium of the market situation of the previous period (quarter) and the present disequilibrium in the market. The expression does probably not work for other market situations than variants of cartels.
and two in Appendix C.
The advantage of equation 10.
crude oil market functions.
Part of the OPEC oil supply, the OPEC Middle East exports of crude oil and refined petroleum products, was hypothesized to be the key element of a production function for the tanker market.
demand, Dry, and OPEC Middle East petroleum exports.
production functions were tested.
(es) most thoroughly, were:
DTM = 475.3% (OPEC Middle East Exports) + 1295.3 [109 tonne-miles] (10.2)
(46.21) (8.56)
DTM = 507.09%(Middle East Exports) + 505 [109 tonne-miles] — (10.3) (39.48) (2.57)
i-values are in parentheses. Both exports figures are exports of crude oil and refined petroleum products.
The R2s represent an almost perfect fit.
Based on a statistical analysis, both "OPEC Middle East exports" and "(total) Middle East exports"
aggregate tonne-miles demand.
As a confirmed hypothesis, OPEC (ME) is the residual supplier or swing producer in the world oil market and any variations in supply will (most likely) be provided from the OPEC Middle East area.
An empirical analysis provided a significant correlation of the oil flow concepts; international trade of crude oil and refined petroleum products and (OPEC) Middle East exports.
Together with the theoretical and empirical analysis of OPEC and the oil market, and the analysis establishing the relationship between aggregate tonne-miles demand and OPEC Middle East petroleum exports, it was concluded that the (DTM) relationship represents a causal relationship between the dependent (tonne-miles) and the independent variable (OPEC Middle East petroleum exports).
The production function(s) can be used for prediclive purposes.
function(s) may represent an excellent tonne-miles forecasting tool.
The production function(s) constitutes one of several parameters of a new capacity utilization concept, which is developed. VLCC spot freight rates are treated as a function of capacity utilization. In this respect il was important to establish that the Middle East is predominant with respect to VLCC employment. For the years 1987 to 1989 84.3 % to 85.4 % of the VLCCs traded out of the Middle East, on a tonne-miles basis.
view, can be justified based on individual tanker movements.
the following empirical relationship was established: Pr) = 510.6* (SFR) (y) + 467.9% (trend) yy + 22721  [tonne-miles/dwt] — (10.4) (5.3) (10.3) (35.8)
t-values in parentheses.
All the estimated parameters are significant (5 % significance level) and the DW-test indicates that there is no autocorrelation in the residuals.
The R2 value (0.97) represents an almost perfect fit.
The new capacity utilization term for the tanker market was defined:
CAP = (DTM/P + Dsy)/[F + (1-B)Sobol (10.4)
B = The proportion of combined carriers trading with liquid bulk capital based. It relates a production function (DTM)
(P) (output to capital relationship) which converts the production function to capital (dwt). Together with storage vessels (Dsy), this represents the total demand for capital or tonnage. The denominator represents the total supply potential of tankers and combined carriers (combined carriers not trading liquid bulk).
Capacity utilization (equation 10.4) will tend to increase with increasing OPEC Middle East output (through the production function), and increasing use of (demand for) storage vessels. The term, other things equal, will tend to decrease with increasing aggregate productivity. A large proportion of the combined carrier fleet available for liquid cargo employment (meaning trading with dry cargo), will also tend to reduce capacity utilization.
The capacity utilization term differs from other discussed methods by the following;
The capacity utilization term which was developed, was derived to be the major parameter in a function linking VLCC spot prices to CAP.
SFR = e2-4! [cAp]4.07 (10.5) (3.79) (19.52)
t-values in parentheses and R2 = 0.59. where SFR = USD/tonne of oil for a 250.000 dwt TT VLCC from AG-NWE.
All the estimated parameters are significant (5 % significance level)
Spot freight rates, within this framework or model, are a function of the capacity utilization which represents the disequilibrium between the total demand for ship tonnage and potential tanker supply. The model hypothesizes that by calculating the total demand for dwt and by comparing this to the potential liquid bulk supply, the subsequent capacity utilization rate is an indicator of spot freight rates.
such can be regarded as a simple analytical model of the tanker market.
The relationship of eq. 10.5 can represent a simple aggregate analytical model of the world tanker market. The scheme may at the same time be applied as a conceptual framework, within the analytical procedure, for analyzing and understanding the market for large tankers. As stated the art of building scenario planning models is simplicity, so it is possible to communicate the model structure throughout the organization, but at the same time it must represent the real world in a meaningful way.
and have a time horizon of 6 to 8 quarters.
The exogenous variables will be: OPEC Middle East petroleum (crude oil and refined petroleum) exports, amount of storage vessels, total tanker and combined carrier fleet, and the proportion of combined carriers trading with dry bulk. Based on a fundamental oil market supply and demand analysis, which is beyond the scope of the topic of the dissertation, with OPEC treated as a cartel and the residual supplier of oil, OPEC Middle East oil exports figures are derived. Aggregate productivity could be treated exogenously or endogenously. The amount of lay-up tanker tonnage is considered to be a demand sided response in the system. Due to the lead time in shipbuilding, deliveries of newbuildings can be treated as a function of the orderbook if the time frame is 6 -8 quarters.
The only endogenous variable(s)
(and productivity).
The theme of the thesis is on the flow of oil (from the Middle East) and how it relates to tanker demand. With a high level of tension and frequent attacks on both oil terminals and merchant ships in the Arabian Gulf during the war between Iran and Iraq. the possibility of bypassing the Strait of Hormuz by means of crude oil pipelines, was frequently reproposed not only by Iran, Iraq and Saudi Arabia, but also from other oil exporters in the Middle East.
Å sensitivity analysis has been suggested within the conceptual VLCC tanker framework. The analysis may be integrated into the analytical procedure, to relate adjustments to the production function due to different loading points in the Middle East, as consequences due to political events.
The question about loading points may have a significant impact on aggregate demand.
company decisions about spot market exposure.
At year-end 1994, it may be concluded that, for any practical purposes, all the spare production capacity of OPEC was located within the OPEC Middle East region, and subsequently the non-Middle East OPEC producers were producing near their production capacities. It is also quite evident that the predominance of the Middle East region of OPEC will tend to increase.
East producers.
When the UN (oil) embargo against Iraq is lifted, tanker demand may differ 387 mrd. tonne-miles, depending whether 1 mbd of oil is exported from Ceyhan with destination Rotterdam or from AG. This represents about 4.
perspective (VLCC) has been performed. The study starts with the behaviour of Middle East exports, to the management (planning) of VLCCs with respect to buy/sell decisions or chartering policy.
disuse of the pipeline grid in the area.
the general beginning-state-driven developmental planning scheme, as a topic of further research. The cartel behaviour was tested by an alternative aggregate approach. As a further research topic in the area, a comparable analysis of the 1987 to 1994 period may be proposed, besides a comparable study to other methods of testing the cartel hypothesis for various time periods.
Based on the provided (disaggregate) tanker and combined tanker trading data in Appendix B, it would be possible to analyze any changes in trading patterns for various tanker size categories, disaggregate and aggregate tonne-miles figures, various productivity factors for different size categories etc. All these topics or any related subjects could also be investigated further.
a parameler for the simple analytical model. An extension of the aggregate productivity factor (time series) with other time periods or any disaggregate productivity factors (time series)
productivity factor (eq. 10.4) with other time periods, or to provide any disaggregate productivity factors, are beyond the scope of the dissertation and may be topics of further research.
The performed analyses of this thesis have been from a tanker owner's or operator's perspective. Any equivalent analyses from a Middle East OPEC producer's or combined oil producer/tanker owner's or operator'
are also possible research topics of the future.
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Numerical data were taken from the following sources:
Chapte;
BP Statistical Review of World Energy, June 1994. Oil & Gas Journal, December 27, 1993.
Chapter 4 BP Statistical Review of World Energy-various issues.
Statistics Yearbook, National sources, OECD Quarterly Oil & Gas Statistics.
Chapter 6 IEA Annual Report 1985. PIW-various issues. Platt's.
Report-various issues.
Lloyd's Shipping Economist-various issues. IEA Annual Report 1988 and various IEA Monthly Oil Market Reports. OPEC Statistical Bulletin 1989, based on direct communications to the OPEC secretariat, Twentieth Century Petroleum Statistics, De Golyer and MacNaughton, PTW, Weekly Petroleum Argus. OPEC Statistical Bulletin 1989, based on direct communications to the OPEC secretariat, UN Energy Statistics Yearbook, National sources, OECD Quarterly Oil & Gas Statistics. BP Statistical Review of World Energy-various issues. Fearnleys Review-various issues.
Norwegian Shipowner's Association.
IEA Monthly Oil Market Report-various issues. OPEC Statistical Bulletin 1989, based on direct communications to the OPEC secretariat, National Sources, IEA, World Energy Statistics and Balances, UN Energy Statistics Yearbook, OAPEC Report. OPEC Statistical Bulletin 1989, based on direct communications to the OPEC secretariat, UN Energy Statistics Yearbook, National sources, OECD Quarterly Oil & Gas Statistics.
Fearnleys. Lloyd's Mardata. Howard Houlder. Lloyd'
various issues. R.S. Platou Economic Research.
CIA (International Energy Statistical Review), October 28, 1986. Oil & Gas Journal, December 27, 1993. CIA, October 28, 1986. PIW, February 4, 1980. PIW, February 10, 1992. PIW's Global Oil Stocks & Balances (GOSB), September 1994. IEA Annual Oil Market Report, PIW, various issues. CIA, February 27, 1990. PIW, March 12, 1990. IEA Monthly Oil Market report, October 1990, Supplement. "Pipelines in the Middle East', unpublished, IEA Report, 1987. The Oil Daily, Special Report, September 1989. MEES, January 15, 1990. MEES, April 16, 1990. MEES, September 17, 1990. PIW, June 13, 1994. Petroleum Economist, 1990. MEES, October 15, 1990. Petroleum Economist Map of Middle East Oil and Exports Routes, 1987, 1990. PIW, April 11, 1988. MEES, April 25, 1988. MEES, August 22, 1988. MEES, September 5, 1988. MEES, July 1, 1991. MEES, January 27, 1992. MEES May 18, 1992. Business Week, May 13, 1994.
1) MMC = Saudi Arabia, Iran, Iraq, Kuwait, Nigeria, Algeria, Indonesia, and Venezuela. However, this particular MMC meeting was attended by all 13 member countries.
2) Saudi Arabia Monitor, April 1990.
3) Petroleum Intelligence Weekly (PIW), October 8, 1990.
4) PIW, July 10, 1989.
5) Middle East Economic Survey (MEES), December 4, 1989. 6) PIW, January 28, 1991.
7) MEES, May 4, 1992.
8) PIW, April 26, 1993.
9) PIW, May 21, 1990.
10) MEES, March 2, 1992. 11) PIW, June 7, 1993.
12) PIW, March 16, 1992. 13) MEES, October 2, 1989. 14) PIW, December 13, 1993.
15) Oil & Money Conference, London, October 18-19, 1990. A.S. Pietri, President of PDV, and J. Aminu, Petroleum Resources Minister of Nigeria.
16) PIW, May 4, 1992.
17) MEES, January 7, 1991.
18) PIW, June 1, 1992.
19) PIW's Global Oil Stocks & Balances, September 1994. 20) The oil Daily, Special Report, September 1989. 21) MEES, April 16, 1990.
22) MEES, January 15, 1990.
23) MEES May 15, 1989.
24) Business Week, May 23, 1994.
25) PIW, April 27, 1992.
26) MEES, October 15, 1990.
27) MEES August 27, 1990.
28) PIW, June 6, 1994.
29) PIW, October 23, 1989.
30) MEES, July 1, 1991.
31) PIW July 13, 1992.
32) PIW, March 7, 1988.
33) Petroleum Economist (PE), November, 1986. 34) PE, March, 1988.
35) MEES, May 18, 1992.
36) Lloyd's List, December 27, 1991.
The general form of a multiple linear regression model is:
Y=Bo+ Bix +.+Pn<n"*e (al)
unknown regression coefficients Bj. j=0.1.
e = error term.
Suppose that n > k observations are available, and let y;
response and Xjj denote the ith observation or level of regressor Xj.
Then a.1 may be written:
k S= Bo + EBjxij + ej, j=12.n (a.2)
In matrix notation (a.2) may be written: y=XB+e (4.3)
The least squares estimator of is: B=(xu)lxy (2.4)
The difference between the observed value y;
vi is the residual e; = y;
n SSR = Z(y*; - y)? : (a.5)
n y= l/nZy; (2.6)
n SSE = I(yv; - y )2 7 E=Z(yi-Y » (2.7)
To test for significance of regression is a test to determine if there is a linear relationship between the response y and any of the regressor variables.
The appropriate hypotheses are:
Ho: B1 =P2=-Px=0 Hy:
Fo = [SSR/KV[SSE/(n-k-1)] = MSR/MSE (2.8)
coefficients, such as Bj» are: Hj:
tg=b'j/se(b";) (2.9) Hg: Bj = 0 is rejected if Itol > ty/2, n-k-1.
n Syy= Hoi - 22 (2.10)
The coefficient of multiple determination, R2, is defined as:
R2 = SSRISyy (a.11)
regressor variables x1 .. xi.
The test by Durbin and Watson (DW) is the most widely used to detect the presence of autocorrelation.
observed at equally spaced time periods; that is:
& = PE-1 + (a.12)
p (Ipl < 1) = autocorrelation parameter Ho: p=0 Hj:
The test statistics is:
n n d=[E(e- 1? VEe] (2.13)
conclusion regarding the hypotheses (a.12) can be reached.
The decision procedure is:
d < dj, reject Hg: p=0 d > du, do not reject Hg:
Europe From: ++ Size: 10,000 -AG 55 CEYHAN 0 FE/AUST 23 N.AFRICA 333 N. EUROPE 12039 NA /CARR 429 RS 46 S. EUROPE 447 SING 33 VENEZ 96 W.AFRICA 112 ++ Subtotal %+ 13613 ** Size: 60,000 -AG 29 CEYHAN 2 FE/AUST 0 N.AFRICA 85 N.EUROPE 1520 NA /CARR 115 RS 4 S.EUROPE 51 SING 2 VENEZ 29 W.AFRICA 32 ** Subtotal **
TANKERS:
South N.
Japan F.
East/ Aust.
From: ** Size: 100,000 - 19 AG 44 CEYHAN 4 FE/AUST 0 N.AFRICA 83 N.EUROPE 1077 NA /CARR 68 RS 0 S. EUROPE 41 SING 0 VENEZ 16 W.
AG 375 CEYHAN 2 FE/AUST 0 N.AFRICA 177 N.EUROPE 1042 NA /CARR 9 RS 0 S.EUROPE 37 SING 0 W.AFRICA 53 *%* Subtotal. +*
275 79 185 3820 Europe From: ** Size: 10,000 -AG 2025 CEYHAN 0 FE/AUST 588 N.AFRICA 8806 N.EUROPE 294538 NA/CARR 12306 RS 1361 S. EUROPE 11951 SING 843 VENEZ 3444 W.AFRICA 2977 ** Subtotal ** 338839 +" Size: 60,000 = AG 2376 CEYHAN 153 FE/AUST 0 N.AFRICA 6920 N. EUROPE 119023 NA/CARR 9081 RS 302 S.EUROPE 4227 SING 145 VENEZ 2438 W.AFRICA 2630 Subtotal ""
TANKERS: TOTAL DEADWEIGHT ('000)
F.East/ Aust.
36352 1020 97064 51939 130595 246158 6837 40955 28916 19121 9990 YEAR 1980 TANKERS: TOTAL DEADWEIGHT ('000)
To North South N.Amer/ Korea Japan F.East/ Sing. TOTAL Europe Europe Carr Aust.
AG 6399 6439 1046 2863 23498 11769 2839 54853 CEYHAN 573 3284 0 0 0 +0 0 3857 FE/AUST 0 0 7835 104 12376 14442 12659 47416 N.AFRICA 10913 35593 13468 0 369 0 343 60686 N. EUROPE 133815 7734 6183 0 0 0 199 147931 NA/CARR 8608 4724 154561 0 1445 4760 3843 177941 RS 0 105 1524 0 0 105 309 2043 S.EUROPE 5359 28825 4846 0 262 155 251 39698 SING 0 0 1992 335 2412 11970 2764 19473 VENEZ 1912 678 526 0 0 0 0 3115 W.
**%* Subtotal. **
AG 104677 36462 62958 15363 120698 7967 19858 367983 CEYHAN 508 7018 0 0 0 0 0 7526 FE/AUST 0 215 1305 697 1865 1182 6164 11428 N.AFRICA 48092 24983 4804 0 0 0 1516 79395 N. EUROPE 285599 10984 4690 0 0 332 1540 303145 NA/CARR 2415 3282 102467 0 268 646 2680 111758 RS 0 255 0 0 0 0 0 255 S. EUROPE 10096 57951 2345 0 0 215 273 70880 SING 0 216 1997 1297 2240 3674 10618 20042 W.
CEYHAN FE/AUST N.
VENEZ W.
++ Sizer:
CEYHAN FE/AUST N.AFRICA N.
få Subtotal **
OBOS:
OCoOWOoOOOOONOOo An occ'
Aust.
CO ®WHKFNOOSNOW o obo ASD.
From: ** Size: 100,000 - 199,999 dwt AG 3 8 4 å 0 CEYHAN å 4 0 0 0 FE/AUST 39 23 21 9 169 N.AFRICA 15 49 31 0 2 N.EUROPE 255 10 98 0 1 NA /CARR 200 17 100 20 42 RS på 2 4 0 0 S.EUROPE 5 63 5 0 0 SING 5 0 12 2 16 VENEZ 3 0 4 0 0 W.AFRICA 20 20 5 0 7 **. Subtotal "
547 196 284 31 237 ** Size: +200,000 dwt AG 7 å 3 0 0 CEYHAN 0 0 0 0 0 FE/AUST i 0 0 0 2 N.AFRICA 7 0 0 0 0 N.EUROPE 77 I 0 0 0 NA/CARR z 0 2 0 1 RS 0 0 0 0 0 S.EUROPE 0 3 0 0 2 SING 0 0 0 0 1 W.AFRICA 0 0 0 0 0 ++: Subtotal; **
220 69 3239 From:
** Size: AG CEYHAN FE/AUST N.AFRICA N. EUROPE NA/CARR RS S.EUROPE SING VENEZ W.
OBOS: TOTAL DEADWEIGHT ('000)
North South N.
** Size: AG CEYHAN FE/AUST N.AFRICA N.
S. EUROPE SING VENEZ W.
To North South N.Amer/ Korea Japan F.East/ Sing.
Europe Europe Carr Aust. From: *% 'Size: 100,000 - '199,999 'dwt AG 426 1213 548 165 0 373 442 3167 CEYHAN 163 558 0 0 0 = 0 0 721 FE/AUST 5788 3763 2442 1161 25546 11503 2062 52265 N.AFRICA 1996 6409 3578 0 285 0 145 12413 N. EUROPE 33428 1314 11610 0 168 0 0 46520 NA/CARR 24692 1956 11918 2188 6074 1046 222 48096 RS 160 263 649 0 0 0 0 1072 S.EUROPE 726 8328 603 0 0 0 0 9657 SING 685 0 1569 103 2088 2768 163 7376 VENEZ 322 0 429 0 0 0 0 75% W.AFRICA 2333 2441 578 0 946 0 0 6298 ++ Subtotal **
70719 26245 33924 3617 35107 15690 3034 188336 ** Size: +200,000 dwt AG 1609 262 674 0 0 0 225 2770 CEYHAN 0 0 0 0 0 0 0 0 FE/AUST 248 0 0 0 497 0 946 1691 N.AFRICA 1710 0 0 0 0 0 0 1710 N.EUROPE 18300 217 0 0 0 0 0 18517 NA/CARR 219 0 492 0 228 249 0 1188 RS 0 0 0 0 0 0 0 0 S.EUROPE 0 732 0 0 262 0 0 994 SING 0 0 0 0 265 0 459 724 W.AFRTCA 0 0 0 0 0 0 0 0 ++ Subtotal +"
141507 43781 66942 4823 46597 23891 7726 335267 From: ** Size: 10,000 -AG 55 CEYHAN 0 FE/AUST 23 N.AFRICA 344 N. EUROPE 12183 NA /CARR 479 RS 47 S.EUROPE 454 SING 33 VENEZ 96 W.AFRICA 114 ** Subtotal ** 13828 ** Size: 60,000 -AG 29 CEYHAN 2 FE/AUST 21 N.AFRICA 94 N. EUROPE 1767 NA/CARR 256 RS 6 S. EUROPE 62 SING 3 VENEZ 58 W.AFRICA 63 +" Subtotal "
OBOS AND TANKERS:
Japan F. East/ Aust.
483 13 1379 679 1973 3593 101 576 407 297 176 OBOS AND TANKERS:
From: ** Size: 100,000 - 19 AG 47 CEYHAN 5 FE/AUST 39 N.AFRICA 98 N.EUROPE 1332 NA /CARR 268 RS I S.EUROPE 46 SING 5 VENEZ 19 W.
AG 382 CEYHAN 2 FE/AUST x N.AFRICA 184 N.EUROPE 1119 NA/CARR 10 RS 0 S.EUROPE 37 SING 0 W.AFRICA 53 +" "Subtotal **
416 33 753 561 1548 1678 2)
279 82 185 3936 From:
f% Size:
AG CEYHAN FE/AUST N.AFRICA N.
AG CEYHAN FE/AUST N.AFRICA N. EUROPE NA/CARR RS S.EUROPE SING VENEZ W.AFRICA **
OBOS AND TANKERS: TOTAL DEADWEIGHT ('000)
AG 6825 CEYHAN 736 FE/AUST 5788 N.AFRICA 12909 N.EUROPE 167243 NA /CARR 33300 RS 160 S.EUROPE 6085 SING 685 VENEZ 2233 W.AFRICA 8051 ** Subtotal *=*
AG 106286 CEYHAN 508 FE/AUST 248 N.AFRICA 49802 N.EUROPE 303899 NA/CARR 2634 RS 0 S. EUROPE 10096 SING 0 W.AFRICA 13829 **"Subtotal ** 487302 ***
1047917 Europe From: *%*, Size: 10,000 -AG 23 CEYHAN 4 FE/AUST 28 N.AFRICA 475 N. EUROPE 13584 NA/CARR 448 RS 75 S.EUROPE 518 SING 26 VENEZ 76 W.AFRICA 29 ++)Subtotalcks 15286 ** Size: 60,000 -AG 43 CEYHAN 13 FE/AUST 1 N.AFRICA 215 N. EUROPE 1963 NA/CARR 90 RS 12 S.EUROPE 44 SING 0 VENEZ 42 W.AFRICA 67 ++ Subtotal **
1 156 444 9157 Europe Europe From: ** Size: 100,000 - 199,999 AG 30 82 CEYHAN 49 74 FE/AUST 2 0 N.AFRICA 122 291 N.EUROPE 1504 76 NA/CARR 21 12 RS 19 54 S.EUROPE 48 309 SING 0 1 VENEZ 18 7 W.AFRICA 97 71 ++ "Subtotal **
1909 947 ** Size: +200,000 dwt AG 63 9 CEYHAN 13 7 FE/AUST 0 0 N.AFRICA 30 31 N. EUROPE 270 20 NA/CARR 8 6 RS 0 4 S.EUROPE 17 84 SING 0 0 W.AFRICA 27 40 ** Subtotal **
N.Amer/ Korea Japan F. East/ Sing.
Carr Aust.
129 0 i:
10524 353 2661 6174 ¥783 49460 Europe From: *%* Size: 10,000°-AG 705 CEYHAN 135 FE/AUST 807 N.AFRICA 12906 N.EUROPE 311666 NA /CARR 13750 RS 2367 S.EUROPE 12724 SING 688 VENEZ 2762 W.AFRICA 891 ++ Subtotal ++ 359401 "+ Size: 60,000" -AG 3480 CEYHAN 1110 FE/AUST 97 N.AFRICA 16546 N. EUROPE 165846 NA/CARR 7423 RS 972 S.EUROPE 3675 SING 0 VENEZ 3569 W.AFRICA 5814 ++ Subtotal **
33205 5372 174153 47874 174742 168622 12423 43485 35239 18158 13655 TANKERS: TOTAL DEADWEIGHT ('000)
Europe Europe From: ** Size: 100,000 - 199,999 AG 4279 6863 CEYHAN 6918 10348 FE/AUST 138 0 N.AFRICA 16214 39731 N.EUROPE 187237 10338 NA/CARR 2831 1640 RS 2556 6998 S.EUROPE 6647 42624 SING 0 128 VENEZ 2262 885 W.
241563 128961 ++ Size: +200,000 dwt AG 18524 2671 CEYHAN 3456 1846 FE/AUST 0 0 N.AFRICA 8118 8204 N.EUROPE 74746 5737 NA/CARR 2272 1541 RS 0 1115 S.EUROPE 4762 22642 SING 0 0 W.
0 30789 20769 596295 12376 162744 0 6629 7457 16550 554 18191 499 85164 1227 40006 0 4300 1093 29476 3979 17270 257 21822 27442 402152 112917 2643409 From:
54 Europe From: ** Size: 100,000 AG 5 CEYHAN 5 FE/AUST 42 N.AFRICA 22 N. EUROPE 342 NA/CARR 114 RS 6 S. EUROPE 10 SING 5 VENEZ 5 W.AFRICA 37 "+ Subtotal ** 593 ** Size: +200,000 AG 0 CEYHAN 0 FE/AUST 11 N.AFRICA 4 N. EUROPE 39 NA /CARR 0 RS 0 S. EUROPE 0 SING 0 W.AFRICA 0 "
86 YEAR 1985 OBOS: TOTAL DEADWEIGHT ('000)
AG 186 159 0 0 0 110 0 455 CEYHAN 0 0 0 0 0 0 0 0 FE/AUST 0 0 102 0 55 475 195 827 N.AFRICA 720 1335 258 55 0 0 0 2368 N.EUROPE 2857 567 348 0 0 0 0 3772 NA /CARR 900 765 4059 98 50 149 0 6021 RS 109 488 0 0 0 0 0 597 S.EUROPE 469 4676 204 0 0 0 50 5399 SING 104 0 0 0 0 104 100 308 VENEZ 209 149 255 0 0 0 0 613 W.AFRICA 103 96 54 0 0 0 0 253 ++ Subtotal **
5657 8235 5280 153 105 838 345 20613 xx Size: 60,000 - 99,999 dwt AG 862 239 240 78 633 249 562 2863 CEYHAN 232 222 0 0 0 0 0 454 FE/AUST 152 0 708 1920 317 2791 1607 7495 N.AFRICA 3062 4876 1391 0 0 0 0 9329 N.EUROPE 29723 1385 3841 0 0 150 0 35099 NA /CARR 8526 2835 11183 375 759 1046 84 24778 RS 314 1494 164 0 66 90 66 2194 S.EUROPE 1351 6700 862 0 0 71 85 9069 SING 0 0 832 72 562 704 0 2170 VENEZ 1441 820 864 0 0 0 0 3125 W.
++ Subtotal ++ 48942 19805 20140 2445 2337 5101 2404 101174 From:
AG 615 CEYHAN 688 FE/AUST 6239 N.AFRICA 2638 N. EUROPE 41152 NA/CARR 13294 RS 729 S.EUROPE 1240 SING 741 VENEZ 531 W.AFRICA 4259 ++"
AG 0 CEYHAN 0 FE/AUST 2482 N.AFRICA 896 N. EUROPE 8997 NA/CARR 0 RS 0 S. EUROPE 0 SING 0 W.AFRICA 0 ** Subtotal ** 12375 xxx Total ***
218 0 0 0 0 0 218 2412 249 0 1967 904 2265 20172 57237 44986 9024 19363 17141 13604 300455 Europe From: ** Size: 10,000 -AG 27 CEYHAN 4 FE/AUST 28 N.AFRICA 490 N. EUROPE 13649 NA/CARR 466 RS 77 S.EUROPE 527 SING 28 VENEZ 80 W.AFRICA 31 ** Subtotal ++ 15407 +% Size: 60,000 —-AG 54 CEYHAN 16 FE/AUST 3 N.AFRICA 254 N.EUROPE 2336 NA/CARR 198 RS 16 S.EUROPE 61 SING 0 VENEZ 58 W.AFRICA 105 ** Subtotal **
448 72 2386 705 2511 2524 179 646 478 278 210 YEAR 1985 OBOS AND TANKERS:
AG 35 68 12 11 74 32 25 257 CEYHAN 54 79 6 0 0 sä 0 140 FE/AUST 43 21 43 56 128 216 147 654 N. AFRICA 144 311 15 1 0 0 2 473 N. EUROPE 1846 92 51 0 2 3 2 1996 NA /CARR 135 33 840 18 24 11 15 1076 RS 25 64 10 5 15 12 9 140 S. EUROPE 58 398 12 0 3 2 3 476 SING 5 3 33 7 29 139 20 236 VENEZ 23 15 8 0 0 0 0 46 W.AFRICA 134 85 72 1 0 0 0 292 ** Subtotal **
AG 63 9 35 44 383 42 49 625 CEYHAN 13 7 3 0 2 0 0 25 FE/AUST il 2 2 10 3 24 34 86 N. AFRICA 34 31 0 2 2 1 1 71 N.EUROPE 309 21 7 2 2 5 2 348 NA/CARR 8 6 130 0 5 0 4 153 RS 0 4 0 3 6 2 0 15 S. EUROPE 17 90 2 1 0 i 4 115 SING 0 0 2 6 12 33 16 69 W.AFRICA 27 41 31: 0 0 2 Å 82 rt Subtotal **
xxx Total xxx 21493 8494 11070 431 2801 6338 1895 52522 From:
36068 6026 181648 57203 209841 193400 14617 52554 37409 21283 18253 From:
AG 4894 CEYHAN 7606 FE/AUST 6377 N.AFRICA 18852 N. EUROPE 228389 NA/CARR 16125 RS 3285 S.EUROPE 7887 SING 741 VENEZ 2793 W.AFRICA 16740 **.Subtotal *
OBOS AND South N.
AG 18524 CEYHAN 3456 FE/AUST 2482 N.AFRICA 9014 N. EUROPE 83743 NA /CARR 2272 RS 0 S. EUROPE 4762 SING 0 W.
422324 Europe From: ** Size: 10,000 -AG 41 CEYHAN 0 FE/AUST 40 N.AFRICA 541 N. EUROPE 14626 NA/CARR 471 RS 61 S.EUROPE 614 SING 7 VENEZ 57 W.AFRICA 32 ** Subtotal ++ 16490 ** Size: 60,000 -AG 36 CEYHAN 21 FE/AUST 0 N.AFRICA 254 N.EUROPE 1971 NA/CARR 156 RS 19 S. EUROPE 39 SING 1 VENEZ 63 W.AFRICA 58 ** Subtotal **
500 72 2514 690 2111 2794 154 561 600 466 119 Europe Europe From: ** Size: 100,000 - 199,999 AG 37 36 CEYHAN 50 91 FE/AUST 1 3 N.AFRICA 74 282 N. EUROPE 1483 79 NA/CARR 28 15 RS 21 37 S. EUROPE 59 340 SING 0 3 VENEZ 10 5 W.AFRICA 84 74 ++ Subtotal ** 1847 965 ** Size: +200,000 dwt AG 108 18 CEYHAN 26 7 FE/AUST 0 0 N.AFRICA 39 11 N.EUROPE 230 18 NA/CARR 10 7 RS 6 2 S.EUROPE 13 42 SING 0 0 W.AFRICA 4 8 ++ Subtotal **
N.Amer/ Korea Japan F.
a Size:
N.AFRICA 13980 N.
NA/CARR 14250 RS 1972 S.EUROPE 15983 SING 187 VENEZ 2161 W.AFRICA 921 *%* Subtotal fæ 387021 ++ Size: 60,000:
N.AFRICA 20217 N.
NA/CARR 13186 RS 1487 S.EUROPE 3165 SING 83 VENEZ 5379 W.
39579 6000 199005 56373 182534 214226 12273 43717 47480 35868 10442 TANKERS: TOTAL DEADWEIGHT ('000)
** Size: 100,000 — 199,999 AG 5198 4971 CEYHAN 7185 12813 FE/AUST 172 385 N.AFRICA 9930 38234 N. EUROPE 186589 10687 NA/CARR 3606 1896 RS 2845 4686 S.EUROPE 7938 47162 SING 0 385 VENEZ 1155 549 W.
AG 32077 5130 CEYHAN 6905 1836 FE/AUST 0 0 N.AFRICA 10738 3079 N. EUROPE 64158 5160 NA/CARR 3241 1945 RS 1917 617 S.EUROPE 3333 11729 SING 0 0 W.
F.Bast/ Aust.
460566 Europe From: ** Size: 10,000 -AG 1 CEYHAN 0 FE/AUST 2 N.AFRICA 17 N.EUROPE 126 NA/CARR 30 RS 2 S.EUROPE 5 SING 0 VENEZ I W.AFRICA 0 ++ Subtotal ++ 184 ++ Size: 60,000 -AG 6 CEYHAN 0 FE/AUST 3 N.AFRICA 51 N. EUROPE 158 NA/CARR 106 RS 4 S.EUROPE 7 SING 2 VENEZ 2 W.AFRICA 8 ** Subtotal **
From: ** Size: 100,000 - 199,999 AG 7 19 CEYHAN 7 3 FE/AUST 17 2 N.AFRICA 24 44 N. EUROPE 215 20 NA/CARR 99 32 RS 4 7 S.EUROPE 21 109 SING i 2 VENEZ 4 0 W.AFRICA 15 18 ** Subtotal  **
FE/AUST N.AFRICA N.
YEAR 1987 OBOS:
Amer / Korea Japan F. East/ Carr Aust.
58 From:
kk Size: AG CEYHAN FE/AUST N.AFRICA N.EUROPE NA/CARR RS S.EUROPE SING VENEZ W.
1233 Europe From: ** Size: AG 989 CEYHAN 901 FE/AUST 2597 N.AFRICA 2933 N. EUROPE 28059 NA/CARR 11987 RS 464 S. EUROPE 2811 SING 152 VENEZ 417 W.AFRICA 1750 str Subtotal "
AG 513 CEYHAN 0 FE/AUST 686 N.AFRICA 523 N. EUROPE 2338 NA/CARR 0 RS 0 S.EUROPE 445 SING 0 W.AFRICA 0 ** Subtotal '**
0 270 258 1637 492 1675 0 0 3021 13901 15447 254650 From: ++ Size: 10,000 -AG 42 CEYHAN 0 FE/AUST 42 N.AFRICA 558 N.EUROPE 14752 NA /CARR 501 RS 63 S.EUROPE 619 SING 7 VENEZ 58 W.AFRICA 32 ** Subtotal ** 16674 ** Size: 60,000 -AG 42 CEYHAN 21 FE/AUST 3 N.AFRICA 305 N. EUROPE 2129 NA/CARR 262 RS 23 S. EUROPE 46 SING 3 VENEZ 65 W.AFRICA 66 ++ Subtotal **
** Size: 100,000'
AG 44 55 CEYHAN 57 94 FE/AUST 18 5 N.AFRICA 98 326 N.EUROPE 1698 99 NA/CARR 127 47 RS 25 44 S.EUROPE 80 449 SING 1 5 VENEZ 14 5 W.AFRICA 99 92 ++ Subtotal "
AG 110 18 CEYHAN 26 7 FE/AUST 3 3 N.AFRICA 41 21 N. EUROPE 240 19 NA/CARR 10 7 RS 6 2 S.EUROPE 15 46 SING 0 0 W.
xxx Total ***
1779 YEAR 1987 OBOS AND TANKERS: TOTAL DEADWEIGHT ('000)
AG 1460 2156 484 1165 15108 3118 3358 26849 CEYHAN 0 142 0 0 0 0 0 142 FE/AUST 1037 805 3191 2211 20007 97961 27201 152413 N.AFRICA 14841 22594 1618 0 128 142 134 39457 N. EUROPE 340596 16457 5350 0 0 697 419 363519 NA/CARR 15754 5180 238098 1513 8442 3170 512 272669 RS 2074 3716 797 181 1787 1828 1717 12100 S. EUROPE 16245 109324 1574 47 132 473 359 128154 SING 187 0 533 1287 7298 25179 3742 38226 VENEZ 2210 428 12487 0 123 67 53 15368 W.
AG 3254 6002 560 1691 15884 7089 8594 43074 CEYHAN 1856 4144 0 0 0 0 0 6000 FE/AUST 267 163 5748 3797 55200 104941 33197 203313 N.AFRICA 24208 37049 5680 0 295 64 79 67375 N. EUROPE 183448 8567 7751 0 80 0 61 199907 NA /CARR 21390 5358 205597 1390 3006 2508 1208 240457 RS 1786 8741 703 81 820 337 2180 14648 S.EUROPE 3717 46336 2045 0 197 437 411 53143 SING 231 220 2276 840 9613 33042 4122 50344 VENEZ 5617 2925 28305 0 0 0 0 36847 W.
se Subtotal ++ 251508 122566 261446 7799 85095 148517 49852 926783 OBOS AND TANKERS: TOTAL DEADWEIGHT ('000)
To North South N.
Europe Europe Carr From: ** Size: 100,000 - 199,999 dwt AG 6187 7447 2808 CEYHAN 8086 13212 1715 FE/AUST 2769 685 2807 N.AFRICA 12863 43174 2598 N. EUROPE 214648 13108 7984 NA/CARR 15593 5463 141142 RS 3309 5484 1648 S.EUROPE 10449 60556 1753 SING 152 601 4368 VENEZ 1572 549 1992 W.AFRICA 12813 12238 17357 *% Subtotal "**
288441 162517 186172 ** Size: +200,000 dwt AG 32590 5130 44130 CEYHAN 6905 1836 833 FE/AUST 686 682 0 N.AFRICA 11261 3079 1204 N. EUROPE 66496 5395 3039 NA/CARR 3241 1945 65401 RS 1917 617 1567 S.EUROPE 3778 12663 0 SING 0 0 750 W.AFRICA 1173 2241 1576 ** Subtotal **
474467 YEAR 1988 TANKERS:
AG 43 61 18 34 375 98 103 732 CEYHAN 0 i 0 0 0 0 0 1 FE/AUST 46 33 82 119 543 3782 1095 5700 N.AFRICA 495 830 40 6 8 14 12 1405 N. EUROPE 14063 583 166 2 3 34 15 14866 NA/CARR 532 129 6974 48 298 83 8 8072 RS 45 88 15 3 43 58 57 309 S.EUROPE 536 4007 40 4 9 21 21 4638 SING 27 22 15 41 251 1026 151 1533 VENEZ 58 13 408 0 5 3 0 487 W.
15873 5791 7765 257 1535 5119 1462 37802 ** Size: 60,000 - 99,999 dwt AG 25 66 12 14 251 91 165 624 CEYHAN 3 60 3 0 0 0 0 66 FE/AUST 2 i 52 65 803 1160 396 2479 N.AFRICA 293 459 24 1 8 2 3 790 N. EUROPE 1872 84 35 0 2 1 2 1996 NA/CARR 131 27 2916 18 25 32 12 3161 RS 8 58 ll 3 9 2 23 114 S. EUROPE 33 365 19 0 5 2 0 424 SING 0 1 17 14 129 398 61 620 VENEZ 82 20 373 0 0 0 3 476 W.
**. Subtotal; ** 2483 1157 3480 115 1232 1689 663 10819 Europe Europe From: ** Size: 100,000-- 199,999 AG 13 21 CEYHAN 43 91 FE/AUST 0 1 N.AFRICA 86 291 N. EUROPE 1531 39 NA/CARR 38 9 RS 21 49 S. EUROPE 44 268 SING 0 0 VENEZ 9 9 W.AFRICA 112 95 ** (Subtotal "*= 1897 873 ** Size: +200,000 dwt AG 163 15 CEYHAN 31 4 FE/AUST i 0 N.AFRICA 62 8 N. EUROPE 307 20 NA/CARR 16 9 RS 5 0 S.EUROPE 12 57 SING i 0 VENEZ z 0 W.AFRICA 6 11 **
1998 Europe From: **. Size: 10,000 -AG 1435 CEYHAN 0 FE/AUST 1074 N.AFRICA 13045 N.EUROPE 321650 NA/CARR 16157 RS 1335 S. EUROPE 13803 SING 761 VENEZ 2268 W.AFRICA 756 ** Subtotal ** 372284 +%,Size: 60,000 —AG 1949 CEYHAN 253 FE/AUST 156 N.AFRICA 23133 N.EUROPE 162111 NA /CARR 10824 RS 652 S.EUROPE 2635 SING 0 VENEZ 6900 W.AFRICA 3022 ** Subtotal **
South N.Amer/ Korea Japan F.East/ Sing. TOTAL Europe Carr Aust.
AG 1828 CEYHAN 6064 FE/AUST 0 N.AFRICA 11834 N. EUROPE 194263 NA/CARR 5122 RS 2926 S.
W.AFRICA 14758 ++ Subtotal **
243967 ** Size;
N.AFRICA 17223 N.
NA/CARR 4930 RS 1454 S.EUROPE 3038 SING 265 VENEZ 284 W.AFRICA 1660 ++) Subtotal **
398356 828384 45729 273990 349248 170350 3063947 Europe From: ++ Size: 10,000 -AG 0 CEYHAN 0 FE/AUST 0 N.AFRICA 13 N. EUROPE 89 NA/CARR 30 RS 0 S. EUROPE 7 SING 0 VENEZ 5 W.AFRICA 0 ** Subtotal'»*+ 144 ** Size: 60,000 -AG 5 CEYHAN 0 FE/AUST 4 N.AFRICA 53 N. EUROPE 188 NA/CARR 154 RS å S.EUROPE 8 SING i VENEZ 14 W.AFRICA 4 **
** Size: 100,000 - 199,999 AG 4 9 CEYHAN 4 I FE/AUST 39 5 N.AFRICA 21 13 N. EUROPE 257 3 NA/CARR 125 28 RS 3 6 S.EUROPE 11 44 SING 1 0 VENEZ 2 0 W.
æ vw From:
xx Subtotal **
1558 252 4067 11180 18714 32141 1567 9282 2020 1203 659 OBOS: TOTAL DEADWEIGHT ('000)
Europe Europe Carr From: +% Size: 100,000 — 199,999 dwt AG 524 1270 504 CEYHAN 505 114 102 FE/AUST 5969 686 898 N.AFRICA 2811 1536 462 N.EUROPE 33830 372 4388 NA /CARR 14960 3170 4477 RS 329 753 232 S. EUROPE 1349 5200 771 SING 161 0 1453 VENEZ 208 0 105 W.AFRICA 2254 1793 382 ** Subtotal **
62900 14894 13774 ** Size: +200,000 'dwt AG 515 224 742 CEYHAN 0 0 612 FE/AUST 1892 673 0 N.AFRICA 705 227 0 N.EUROPE 4790 372 235 NA /CARR 0 0 235 RS 0 0 0 S. EUROPE 0 448 0 SING 258 0 0 VENEZ 0 0 0 W.AFRICA 0 0 0 **
19887 YEAR 1988 OBOS AND TANKERS:
AG 43 62 18 35 375 98 103 734 CEYHAN 0 5 0 0 0 . 0 0 5 FE/AUST 46 33 82 119 544 3786 1095 5705 N.AFRICA 508 853 42 6 8 14 12 1443 N.EUROPE 14152 594 178 2 3 34 15 14978 NA/CARR 562 156 7073 48 299 83 8 8229 RS 45 90 16 3 43 58 57 312 S.EUROPE 543 4079 44 4 9 22 21 4722 SING 27 22 15 41 252 1026 152 1835 VENEZ 63 13 409 0 5 3 0 493 W.AFRICA 28 25 7 0 0 0 0 60 **) (Subtotal **
16017 5932 7884 258 1538 5124 1463 38216 ** Size: 60,000 - 99,999 dwt AG 30 72 13 14 256 92 168 645 CEYHAN 3 63 3 0 0 0 0 69 FE/AUST 6 1 56 69 811 1178 413 2534 N.AFRICA 346 486 88 x 9 2 3 935 N. EUROPE 2060 98 21 1 2 L 2 2235 NA/CARR 285 75 3110 20 28 38 14 3570 RS 9 69 15 4 9 3 25 134 S.EUROPE 41 467 31 0 5 2 0 546 SING 1 1 17 17 130 417 64 647 VENEZ . 96 20 374 0 0 0 2 491 W.
** Subtotal ++ 2915 1371 3797 126 1250 1734 690 11883 YEAR 1988 OBOS AND TANKERS:
AG 17 30 10 19 25 61 31 193 CEYHAN 47 92 23 0 0 0 0 162 FE/AUST 39 6 37 46 95 . 257 152 632 N.AFRICA 107 304 9 2 1 0 1 424 N.EUROPE 1788 42 70 i 1 4 3 1909 NA/CARR 163 37 971 6 17 16 30 1240 RS 24 55 4 8 6 9 9 115 S.EUROPE 55 312 ib 0 0 2 3 383 SING 1 0 40 15 79 139 24 298 VENEZ 11 9 6 0 0 0 1 27 W.AFRICA 131 110 140 3 2 0 4 390 ** Subtotal +"
AG 165 16 144 60 381 42 100 908 CEYHAN 31 4 44 0 0 0 0 79 FE/AUST 9 3 2 3 7 14 47 84 N.AFRICA 65 9 1 0 0 0 0 75 N. EUROPE 327 23 15 x 2 0 0 367 NA/CARR 16 9 244 i 3 1 8 282 RS 5 0 24 6 34 5 14 88 S.EUROPE 12 59 0 0 0 1 0 72 SING 2 0 3 10 17 36 31 99 VENEZ 2 0 0 0 0 0 0 1 W.AFRICA 6 32 9 0 0 0 0 26 + Subtotal"
xx Total xx 21954 8434 13487 565 3457 7445 2611 57953 YEAR 1988 OBOS AND TANKERS: TOTAL DEADWEIGHT ('000)
AG 1435 2030 778 1498 17120 3501 3157 29519 CEYHAN 0 263 0 0 0 . 0 0 263 FE/AUST 1074 812 2523 3031 22384 101343 31104 162271 N.AFRICA 13717 23744 1642 83 362 389 447 40384 N.EUROPE 326046 15834 4874 54 160 718 410 348096 NA/CARR 175891 5655 233945 1054 9424 2535 303 270507 RS 1335 2979 705 144 1711 1630 2071 10575 S.EUROPE 14172 99330 1463 53 346 496 582 116442 SING 761 514 543 1160 9164 28926 4844 45912 VENEZ 2516 536 13650 0 173 81 0 16956 W.
AG 2342 5435 1093 992 18888 7931 14325 51006 CEYHAN 253 5284 269 0 0 0 0 5806 FE/AUST 504 87 4661 5289 57044 99422 33314 200321 N.AFRICA 27237 40811 6870 62 617 129 205 75931 N.EUROPE 176731 8052 5860 70 136 90 194 191133 NA/CARR 22993 6065 240547 1710 2245 3149 1148 277857 RS 730 5724 1151 282 583 243 2023 10736 S.EUROPE 3309 36742 2552 0 406 159 0 43168 SING 85 90 1398 1327 9472 33771 5214 51357 VENEZ 8025 1613 27366 0 0 0 90 37094 W.
++ Subtotal "+ 245555 111534 293419 9732 89391 144993 56513 951137 OBOS AND TANKERS: TOTAL DEADWEIGHT ('000)
Europe Europe Carr From: ** Size: 100,000 - 199,999 dwt AG 2352 4341 1337 CEYHAN 6569 13822 3213 FE/AUST 5969 821 5010 N.AFRICA 14645 42190 1119 N. EUROPE 228093 5856 9024 NA/CARR 20082 4357 136702 RS 3255 7006 521 S. EUROPE 7519 43255 1299 SING 161 0 5128 VENEZ 1210 1105 661 \«.AFRICA 17012 14511 18414 **' Subtotal **
306867 137264 182428 ** Size: +200,000 dwt AG 47009 4592 46154 CEYHAN 8501 1070 12048 FE/AUST 2156 673 261 N.AFRICA 17928 2394 274 N. EUROPE 90681 6106 4221 NA/CARR 4930 2732 63685 RS 1454 0 7235 S.EUROPE 3038 17116 0 SING 523 0 807 VENEZ 284 0 0 W.AFRICA 1660 3052 2391 **
9551)
7409 .
563499 Europe From: ** Size: 10,000 -AG 48 CEYHAN 0 FE/AUST 72 N.AFRICA 485 N. EUROPE 14501 NA /CARR 607 RS 47 S.EUROPE 570 SING 22 VENEZ 50 W.AFRICA 39 ** Subtotal ++ 16441 ** Size: 60,000 -AG 9 CEYHAN 5 FE/AUST 1 N.AFRICA 282 N.EUROPE 1940 NA /CARR 118 RS 13 S.EUROPE 40 SING 2 VENEZ 70 W.AFRICA 24 **
656 46 2514 774 2052 3724 147 440 658 378 47 Europe Europe From: ** Size: 100,000 - 199,999 AG 35 27 CEYHAN 40 65 FE/AUST 0 0 N.AFRICA 109 284 N. EUROPE 1508 48 NA/CARR 44 4 RS 18 72 S.EUROPE 38 290 SING 1 1 VENEZ 12 8 W.AFRICA 118 82 **. Subtotal ** 1923 881 ** Size: +200,000 dwt AG 185 18 CEYHAN 45 5 FE/AUST 0 0 N.AFRICA 74 31 N. EUROPE 311 30 NA/CARR 11 7 RS 2 0 S. EUROPE 7 47 SING 3 0 VENEZ 3 0 W.AFRICA 7 13 *
N.AFRICA 13133 N.
NA/CARR 18932 RS 1682 S.EUROPE 14700 SING 611 VENEZ 2021 W.AFRICA 1381 "+ Subtotal 386242 ** Size:
N.AFRICA 22293 N.
NA/CARR 9773 RS 1052 S.EUROPE 3141 SING 148 VENEZ 5819 W.AFRICA 2136 **
51712 3868 199359 63858 176450 293031 11978 34439 52972 28990 4136 TANKERS: TOTAL DEADWEIGHT ('000)
Europe Europe From: ** Size: 100,000 - 199,999 AG 4841 3987 CEYHAN 5675 9850 FE/AUST 0 0 N.AFRICA 15276 39440 N. EUROPE 192161 6599 NA/CARR 5956 574 RS 2453 9645 S.EUROPE 5069 41852 SING 140 112 VENEZ 1444 1005 W.AFRICA 15476 11087 **
248491 124151 ** Size: +200,000 dwt AG 50703 4896 CEYHAN 12184 1333 FE/AUST 0 0 N.AFRICA 19818 8412 N. EUROPE 84200 8024 NA/CARR 2944 2105 RS 2183 0 S.EUROPE 1719 12825 SING 808 0 VENEZ 270 0 W.AFRICA 1807 3398 ** Subtotal **
0 10828 56170 622440 185175 3274474 Europe From: ** Size: 10,000 -AG 1 CEYHAN 0 FE/AUST 0 N.AFRICA 7 N.EUROPE 100 NA/CARR Å 46 RS i S.EUROPE 5 SING 1 VENEZ 4 W.AFRICA 1 ** Subtotal ** 166 ** Size: 60,000 -AG 3 CEYHAN 0 FE/AUST 2 N.AFRICA 28 N. EUROPE 216 NA/CARR 151 RS 5 S.EUROPE 9 SING 1 VENEZ 15 W.
32 Europe Europe From: ** Size; 100,000 - 199,999 AG 3 9 CEYHAN 0 3 FE/AUST 29 10 N.AFRICA Ti 7 N. EUROPE 250 6 NA/CARR An 23 RS 3 2 S.EUROPE 7 26 SING å 0 VENEZ 12 0 W.AFRICA 26 17 **' Subtotal *+ 453 103 ** Size: +200,000 dwt AG 2 1 CEYHAN 0 0 FE/AUST 9 0 N.AFRICA 1 0 N. EUROPE 14 2 NA/CARR 0 0 RS 0 0 S.EUROPE 0 1 SING 3 0 VENEZ 0 0 W.AFRICA 0 0 **
Amer/ Korea Japan F.
75 YEAR 1989 OBOS: TOTAL DEADWEIGHT ('000)
*x Size:
AG 48 96 0 0 0 237 45 426 CEYHAN 0 0 0 0 0 0 0 0 FE/AUST 0 0 48 0 0 558 96 702 N.AFRICA 352 1587 381 0 0 0 0 2320 N. EUROPE 4885 607 801 0 0 0 0 6293 NA/CARR +2331 623 4136 0 48 49 0 7187 RS 44 0 0 0 48 0 0 92 S. EUROPE 226 3805 369 0 0 48 0 4448 SING 48 0 48 43 0 96 0 235 VENEZ 199 44 48 0 0 0 0 291 W.AFRICA 50 55 0 0 0 0 0 105 få Subtotal "
8183 6817 5831 43 96 988 141 22099 ** Size: 60,000 - 99,999 åwt AG 237 690 176 0 66 236 258 1663 CEYHAN 0 85 0 0 0 0 0 85 FE/AUST 191 166 141 184 779 2058 1103 4620 N.AFRICA 2208 2130 4136 0 0 0 0 8474 N.EUROPE 16712 951 3588 0 0 0 227 21478 NA/CARR 11686 4385 11591 191 212 382 0 28447 RS 385 548 538 0 0 76 0 1547 S.EUROPE 683 7588 1225 0 0 0 68 9564 SING 78 0 79 0 218 1003 148 1526 VENEZ 1159 225 239 0 0 0 0 1623 W.
£X Subtotal' x 35177 17586 21713 375 1273 3755 1804 81683 OBOS: TOTAL DEADWEIGHT ('000)
Europe Europe Carr From: ** Size: 100,000 - 199,999 dwt AG 365 1022 345 CEYHAN 0 357 0 FE/AUST 4581 1567 756 N.AFRICA 1305 755 337 N.EUROPE 32268 746 3092 NA/CARR 12815 2696 4115 RS 376 251 205 S.EUROPE 910 3063 744 SING 105 0 1499 VENEZ 1366 0 226 W.AFRICA 3068 1992 526 *% Subtotal **
57159 12449 11845 ** Size: +200,000 dwt AG 507 249 235 CEYHAN 0 0 306 FE/AUST 2099 0 0 N.AFRICA 249 0 0 N. EUROPE 3406 249 0 NA/CARR 0 0 470 RS 0 0 0 S.EUROPE 0 249 0 SING 740 0 291 VENEZ 0 0 0 W.AFRICA 0 0 0 ** Subtotal **
18117 From:
PF. East/ Aust.
677 47 2573 884 2330 4089 167 565 678 399 79 OBOS AND TANKERS:
From: ++ Size: 100,000 - 199,999 åwt AG 38 36 li 24 CEYHAN 40 68 8 0 FE/AUST 29 10 27 54 N.AFRICA 120 291 16 2 N.EUROPE 1758 54 80 0 NA/CARR 155 27 1110 10 RS 21 74 2 2 S.EUROPE 45 316 14 0 SING 2 i 33 2% VENEZ 24 8 13 0 W.AFRICA 144 99 163 0 ** Subtotal **
2376 984 1477 113 ** Size: +200,000 dwt AG 187 19 192 85 CEYHAN 45 5 52 0 FE/AUST 9 0 6 5 N.AFRICA 75 31 2 0 N.EUROPE 325 3) 16 0 NA/CARR ål 7 293 0 RS 7 0 7 1 S.EUROPE 7 48 2 2 SING 6 0 3 7 VENEZ 1 0 0 0 W.AFRICA 7 13 20 0 ** Subtotal "
2367 From:
få Size: AG CEYHAN FE/AUST N.AFRICA N.EUROPE NA/CARR RS S.EUROPE SING VENEZ W.
53375 3953 203979 72332 197928 321478 13525 44003 54498 30613 6792 OBOS AND TANKERS: TOTAL DEADWEIGHT ('000)
Europe Europe Carr From: ** Size: 100,000 - 199,999 dwt AG 5206 5009 1414 CEYHAN 5675 10207 1207 FE/AUST 4581 1567 3537 N.AFRICA 16581 40195 2047 N. EUROPE 224429 7345 10261 NA /CARR 18771 3270 157786 RS 2829 9896 205 S.EUROPE 5979 44915 1701 SING 245 112 4545 VENEZ 2810 1005 1310 W.
305650 136600 205641 ** Size: +200,000 dwt AG 51210 5145 64577 CEYHAN 12184 1333 14184 FE/AUST 2099 0 1479 N.AFRICA 20067 8412 545 N. EUROPE 87606 8273 4284 NA/CARR 2944 2105 81502 RS 2183 0 2166 S.EUROPE 1719 13074 661 SING 1548 0 847 VENEZ 270 0 0 W.AFRICA 1807 3398 5353 ** Subtotal **
PUBLISHED PAPERS:
"Oil Prices Less Than 15 USD/bbl to the Year 2000 - is it Possible ?"
Economists) Conference in Bergen. Norwav, October 1986.
"Kan oljeprisene være under 15 USD/fat frem til år 2000 ?" (Oil Prices Less Than 15 USD/bbl to the Year 2000 ?) Paper published in "Sosialøkonomen". Norway, Vol. 40. No. 9 (1986).
"Lave oljepriser frem til 1990, moderate konsekvenser på etterspørselssiden?"
(Low Prices of Oil to the Year 1990, Moderate Consequences on the Demand Side?)
Paper published in "Ekonomisk Debatt". Sweden, No. 7, 1986.
TO THE YEAR 2000, IS THIS POSSIBLE?
Presented at the IAEE (International Association for Energy Economists)
Bergen, Norway October 1986 During discussions concerning the development of oil prices up to the turn of the century, it is generally felt that the relatively low oil prices prevalent in the first half of 1986 will be temporary.
It is generally expected that the actual prices for crude oil will be in the range of 25 - 40 US$/barrel around the year 2000.
In this article we will briefly go through the historic development on the energy market prior to tackling the basic conditions governing supply and demand of oil.
The conclusion is that the prices of oil may stay below 15 US$/bbl in a near free market situation up to year 2000. This is based on the assumption that the oil market will not be cartellized during this period.
The sharp increases in oil prices during 1973/74 and 1979/80 lead to a reversal of the prevalent trend in the sixties. The total oil consumption in World Outside Communist Areas (WOCA) peaked in 1979 with an average consumption of 50.9 md. For 1985 the average was 45.1 mbd.
The high oil prices stimulated non-OPEC producers to increase their exploration and production activities, and non-OPEC output increased from 19.8 mb/d in 1979 to 25 mbd in 1985.
OPEC, in order to protect the high prices (administered prices), had to curtail production from 31.5 mbd (Incl. NGL) in 1979 to 17.2 mbd in 1985 (incl. NGL).
The total energy consumption within WOCA remained practically unchanged from 1979 to 1985. This was the result of structural changes, efficiency gains and substitution. Energy intensity dropped at a rate of 2.2 per cent/year. During this period there was a fall in oil consumption from a share of 52.3% to 44.6%, while the use of coal increased from 18.9% to 22.3%, nuclear energy from 2.9% to 6% and hydro-electrical power from 7.2% to 8.2%. Natural gas maintained its share of the market.
The switch was mainly to coal and nuclear energy. This development particularly affected the consumption of heavy fuel oil which plunged with nearly one half in the industrialized countries within WOCA, while less developed countries in the west experienced a drop of only 4% in heavy fuel oil consumption.
Except in the transport sector, oil products have reduced their share of the market due to increased prices of oil. This has resulted in an upward pressure also on other forms of fuel. The comparatively high energy prices meant that it was more economical to replace production equipment with more energy-efficient equipment and processes. At the same time there has been a switch to less energy-intensive sectors of the economy, particularly in the OECD countries.
An important consequence of the generally higher energy prices is long-term processes which have started, and which are difficult to stop. This applies particularly to the implementation of more energy-efficient technologies in all areas, but also generally restructuring from energy-intensive activities. The impact of these processes will not be seen till some time in the near future.
Generally we notice the following trends:
- a continued (switching or)
- a change in the composition of industrial production from energy-intensive activities (based on raw materials) to high-technology activities/processes (based on competence).
The above applies particularly to developed countries.
But the trend is the same in all non-communist countries.
industries than in other activities).
and when capital equipment is replaced.
Up to 1973 (the 1950's and 60's) the relationship between the growth in energy consumption and the growth in GNP within the OECD was approx. 1.0. However, oil consumption increased somewhat faster, and the ratio between growth in oil consumption and GNP growth was around 1.5. During the period 1973 - 84 the average GNP growth in OECD countries was around 2.3% a year, and the growth in energy consumption was slightly lower than 0.2% a year, while oil consumption dropped by 1.5% a year. Between 1974 and 1980 demand for both energy and oil grew by approx. two thirds of the GNP growth rate, and after the price increases in 1979/80 the corresponding ratios became negative. Franssen (1985).
Oil demand will be influenced by a possible long period with low oil prices through increased economic growth and a return to oil.
energy-intensive activities.
There will more than likely be a relative increase in the level of economic activities as a result of the low oil prices. Data Resources Inc. (DRI March 1986) estimates that the impact on GNP of a sustained price level of US$15/bbl of oil will be approximately 0.5% in 1986, about 1.5% in 1987 and 0.1% in 1988. In other words, DRI estimates that the strongest impact will come in the second year, i.e. 1987. Furthermore, in their opinion this stimulance is only of a temporary nature. The general level of industrial activity will increase on a global scale, but the economic growth rate will soon revert to what it would have been prior to the increase.
IEA has tentatively estimated that GNP in OECD countries will be 5% higher in 1990 with a sustained reduction in crude oil prices to US$ 10/bbl, and this is in conformance with estimates from DRI.
A survey carried out by OECD (1983) concludes that a 25% reduction in the price of oil will result in an increase in GNP for the first year of 0.6%, the second year of 0.9% and the third year of 1.2%. DRI has also completed studies earlier where they have estimated the effects to be at the same level or higher than the OECD forecast.
Naturally, great uncertainty prevails with such estimates, since we are talking about drastic changes in the prices of oil, and it is doubtful whether the models can Furthermore, political decisions in the various countries cannot be predicted with any certainty at all. Another question is whether it is possible to take advantage of the redistribution of income, from oil producer to oil consumer. Will there be a better growth potential in the world if the oil-consuming countries get hold of this income rather than the oil-producing countries? At least, in OECD's opinion, this is so.
our conclusion, based upon this brief discussion, is that the effect upon the GNP growth rate in the OECD countries is temporary. The GNP-level is increased in relation to a certain situation without a change in the price of oil, and is likely to be 2 - 3% higher in 1990 with a price of US$15/bbl of oil, and 5% higher with a price of US$10/ bbl.
Another consequence of declining oil prices and a resultant increase in GNP, is a temporary reduction in the inflation rate in the OECD countries. This in turn, will lead to a reduction in the general interest rate. For the developing countries and the so-called NIC (Newly Industrialised Countries) countries, which have previously had small hard currency reserves, the income redistribution resulting from low oil prices, together with low interest rates will improve their balance of payment. This may lead to an increase if the import of oil so that an important barrier to economic growth is reduced.
more energy-intensive sectors of the economy.
The substitution of gas, coal and nuclear energy for oil would more than likely have continued with real oil ing rate).
An interesting consideration is whether this trend will be turned with prevailing low oil prices.
The contract prices for gas are directly linked to oil product prices, and to some extent to crude oil prices. Gas prices will therefore follow the crude oil prices after a certain time lag. In the Southern States of the U.S.A. a spot market for gas has emerged. In order to retain market share, the spot price for gas has followed the oil prices downward during the first half of 1986 without any time lag.
One factor which has been emphasized in energy discussions, is the price level at which oil regains market shares on behalf of coal.
Table 1 illustrates break-even prices applicable to coal fired power stations with the possibility of shifting to heavy fuel oil. As we can see, this corresponds to oil prices (1985 currency) ranging from US$ 12 - 16/bbl, depending on the region. The figures in table 1 apply to existing power stations. For new installations the break-even prices will be around 5 - 6 US$/bbl higher.
It should be emphasized that these figures are based on a price of coal of 50 - 60 US$/ton, which were the prices obtained for coal during the autumn of 1985, in other words before the drastic fall in prices during winter/ spring 1986.
It has turned out that spot prices for coal have followed the crude oil prices downwards.
favour of coal, but is somewhat reduced.
Table 1 Break-even oil prices for existing coal-burning electric utilities with oil-burning capabilities (1985 US$/bb1).
Usa 13.46 (10.14-16.11)*
EEC 15.12 (12.40~17.70)*
Japan 14.
(13.46-16.44)* Source: Calarco (1985)
*) The intervals are CIF-prices for coal in the region indicated.
Table 2 is a breakdown of short- and medium term (0 - 3 years) substitution possibilities in favour of oil as compared to gas and coal. The figures are based on oil prices ranging from 15 - 17 US$/bbl. As can be seen, the potential is fairly high, - between 3.2 - 4.5 mbd, but the limit is probably much lower, between 0.7 - 1.2 mbd.
The reason for this, is a political will to keep some of the coal industry (in England and West-Germany). Also, coal and gas prices are likely to follow oil prices in the long run, so these fuels will remain competitive with oil.
OECD for oil, gas and coal, in mbd.
Increase: Increase: SOURCE: Technical Maximum Probable Limit US gas-fired electric power : 0.8 - 0.9 0.2 - 0.3 US coal based elec. power generation 0.3 = 0.5 negligible US industrial boilers 1.0 - 1.5 0.2 - 0.
Japan dual fuel capacity 0.7- 1.0 0.2 - 0.
Japan industrial boilers 0.4 - 0.6 0.1 - 0.2 Sum 3.2—-4.5 0.7 - 1.
Source: CERA (1986)
During the first half of 1986 these substitution effects had little impact. Up until June 1986 (Dwyer (1986) the substitution effects in the USA have only lead to an increase in oil consumption of 100,000 bbl/d.
In Fig. 1 we have made a diagram with demand curves representing short term (1 yr.), medium term (3 - 5 yr.) and long-term (10 - 15 year). These curves are based on studies by several international organizations; DRI (March 1986), DRI (spring 1986), Wharton Econometric well as being based on conversations with analysts with the IEA. In addition, the authors have evaluated these studies in the light of previously publicized studies on price and income elasticities, Bohi (1981), Verleger (1982) and IEA (1982).
For the short term, the above literature indicates a variation in historical elasticities for crude oil, between -0.05 and -0.2. For the longer term, "the corresponding figures are indicated to be between -0.3 and>-1.0.
For the long-term demand curves in Fig. 1, we have collected information from a variety of areas to estimate the impact of GNP growth on oil demand. With a GNP growth of 10%, oil consumption is estimated to increase by 2 to 7.5%.
As far as price elasticity is concerned, we have also chosen to take into consideration a substantial degree of uncertainty. We have chosen to place the long-term price elasticity between -0.5 and -0.85.
An important aspect which should be emphasized with regard to price elasticities, is that historically calculated elasticities apply to increasing prices. They are probably much greater than if prices are falling. A rule of thumb which came to light in conversations with IEA analysts is that the ratio is minimum 3 to 2. This is mainly due to the technological changes resulting from increased oil prices.
new capital investments are made.
prices of crude are reflected in consumer prices. In World Energy Outlook, IEA (1982) it is reckoned that approx. 40% of the changes in crude oil prices are passed through in the transport sector, where as the proportion is 70 - 80% in other sectors. At the present time these proportions will probably be lower due to changes in policies concerning taxation on oil and oil products. The changes in crude oil prices during the past year have only led to a reduction in the price to end users of 10-20% for fuels related to transportation while the reduction was 30 - 40% (varying from 10% to 60% from country to country) for products for other purposes (heating oils and heavy fuel oil), IEA (1986). In the corresponding period, the crude prices dropped 60%.
Demand curves in the short term, DS (1 year), medium term, DP (3 - 5 years) and long term pl (10 - 15 years) for WOCA (1985 US$).
0 10 20 30 40 50 60 70 80 90 100 MILLION BARRELS/DAY The supply side of the international oil market has been dominated by OPEC since 1973. From 1973/74 the organization has behaved like a price cartel, where members have agreed on "posted prices" for the various types of crude oil.
The market situation in the 1980's forced OPEC to alter its strategy to securing a market share for its members, where members agreed on production quotas within a total OPEC quota as a means of maintaining a high price level.
The high oil prices have induced non-OPEC producers to increase exploration and production in high-cost areas.
In principle, oil producers have two basic criteria for their decisions. In the short term, production will continue so long as the variable costs are met (short term marginal costs). For a very short period producers may go below this level if the prices cover maintenance costs necessary to keep wells and production equipment in operation. In the longer term producers must have both fixed and variable costs covered (long term marginal costs) before new investments can be made.
By preparing a breakdown of oil fields according to increasing costs, it is possible to draw marginal cost curves. In a competitive free market the supply curve and the marginal cost curve will be identical.
In a cartellized market it is possible to move the supply curve to the left in the diagram.
In Fig. 2 the short term marginal cost curve (SS) is illustrated the way it appeared at the turn of the year situation, Texas Eastern Corp. (1985).
At the turn of the year 1985/86 the supply curve was moved 10 mbd to the left in the diagram. This was due to OPEC's. reduction. of its total production in order to maintain the price level. This represented 10 mbd of spare capacity within OPEC. The marginal cost for this surplus capacity is less than 6 US$/bbl. OPEC may offer this spare capacity on the market at a short notice (0-3 months). The supply curves indicate production from WOCA.
The supply of oil in the beginning of 1986 was influenced by the fact that OPEC with its low-cost production only used 60 - 70% of the capacity which could be used in the short term, while non-OPEC producers used their full capacity.
The extremes in the oil market can best be illustrated by the following two examples: 0il production from socalled "Stripper wells" in the U.S.A., defined as fields with an average production of less than 10 bbl/day, have moved ahead at full steam in spite of production costs of around 20 USS/bbl. At the same time Saudi Arabia used only 45% of her capacity. In the latter case the marginal costs are around 0 - 4 US$/bbl.
The available short term production capacity within OPEC is about 27.5 mbd in 1986, PIW (1986). In a somewhat longer term this capacity may be substantially increased. By 1990 the countries in the Middle East may increase their capacity by approx. 10 mbd. This increase represents production from existing oil fields which today are subjected to logistic limitations (pipeline capacity). (The installed production capacity from existing fields is 41.4 mbd, but the available capacity is 90% - 95% of this figure, CIA (1986)).
East may raise their capacity further by increasing development of their well known low cost fields with total production costs under 4 US$/bbl. Table 3 shows future proved reserves and future discoveries in various production cost categories. As a comparison, the oil consumption in 1985 was 45.1 mbd or 2.15 milliard. tonnes per year, BP (1986).
Total production costs for global crude oil reserves, broken down according to type of reserves (excl. cumulative production to date). In milliard tonnes.
Total production costs (1983 USD bbl)
Source: Desprairies et al (1985)
SE (1 year)
5 situation.
ucti c i w ovided elds with the lowest cost. In spite of the fact that oil is a depletable resource, the reserves are so vast that there is no limitation on the supply side within the periods considered. Only low-cost oil fields will be economically viable with low oil prices.
Supply curves for crude oil for WOCA in the short term (SS), medium term (SM) and long term (Sl) in a free market situation (1985 US$ prices). (Excl. net exports from Communist countries).
In Fig. 3 we have combined the supply and demand curves from Fig.
equilibrium levels.
Under the existing conditions, the main conclusion is that real prices of crude oil may remain below 15 US$/bbl until the year 2000, even with a substantial increase in demand.
In the short and medium term oil prices may vary between 6 and 10 US$/bbl, while in the long term it may be in the order of 8 - 16 US$/bbl in a market with close to free competition. This means that there are no real constraints on the supply side which may render it impossible to accomodate increases in demand brought about by lower oil prices. Furthermore, net export from communist countries, which in 1985 exceeded 1.8 mbd, will exert a further downward pressure on crude oil prices, and could force the crude oil prices below 15 USS$/bbl. It is widely believed that the oil export from communist countries is inelastic to price, and that they will sell any volume which is available due to their hard currency requirements. Therefore, it is more likely for them to increase than reduce their export even with generally lower oil prices. Net export will probably stay between 1 and 2 mbd. in the years ahead.
Total OPEC production may exceed 40 mbd in the year 2000.
Market equilibrium levels in a free oil market (WOCA)
until the year 2000 (1985 US$ prices).
policies within the different consumer countries with respect to oil and oil products. If the reduction in the prices of crude oil (and products) is offset by taxes, oil demand will only be influenced by the GNP-effect resulting from an increase in public revenues and the use of such revenues. This will exert a further downward pressure on crude oil prices.
From the autumn 1985 until summer 1986 the oil market has in principal moved in a direction towards a free market. What would the most probable developments have been if OPEC were able to cooperate fully for a longer period of time (beyond December 1985)?
The role of Saudi Arabia as a swing producer within OPEC resulted in a drop in Saudi Arabia's oil production from a peak of 10.2 mbd in August 1981 to 2.2 mbd in August 1985. The corresponding reduction in other OPEC countries was only 41%.
It was only a question of time before Saudi Arabia had to change her policy. With a continued increase in non-OPEC production, lack of dicipline within OPEC and prospects for only a marginal increase in demand, a likely scenario would have been a reduction by Saudi Arabia to less than 1 mbd, and perhaps down to zero in the next one or two years in order to maintain high prices.
In light of this, Saudi Arabia had no choice. Sooner or later the country had to change her policy. More than likely, the loss in income would have been greater if they had adhered to their former policy.
obtain.
There is a basic conflict within OPEC between the countries with comparatively large reserves and a small population, and those with relatively small reserves and a large population.
Sauda Arabia and Kuwait with a relatively limited ability to absorb increased oil revenues, have a much longer time horizon when maximizing their oil revenues. Iraq, Libya and Algier have a much shorter time horizon when they want to maximize the net present value (NPV) of their oil revenues. This is due to relatively low estimates of proved oil reserves, large populations and the fact that they have a high absorptive capability for oil revenues within their economies. These countries would therefore favour a rapid increase in oil prices.
Should the OPEC countries reach an agreement to cancel their policy targeted towards a certain market share, in order to get oil prices back to the 1985 level, this level would probably only last for a short period of time. The reason for this is that within such a scenario OPEC countries would have to continue reducing their production. This again is due to the fact that if oil prices remain at the 1980-85 level, only a very limited increase in demand is likely to occur in the forseeable future, and at the same time the non-OPEC production would have increased further.
A "new" cartellization of the market is necessary in order to rapidly achieve and maintain higher prices than those obtained during the first half of 1986, when Brent Blend fell from 27 US$/bbl January 1 to under 10 US$/bbl by the end of July.
In order to maintain stable and relatively high prices in the longer term, this new cartel should have a larger share of the market than OPEC held in the autumn of 1985 (38.3% for the second half of 1985, incl. NGL).
Mexico, Egypt, Malaysia, Angola and Brunei were observers at the OPEC meeting in April 1986. Together with Oman they are potential partners of OPEC. The production capacity of the first five countries is approx. 4.6 mbd, while their production in the first half of 1986 was approx. 3.7 mbd. The oil from these countries, together with OPEC's production, represented a 46% share of the market in 1985. This would be a stronger group than if OPEC were alone, but even this figure may be on the small side concerning obtaining a sustained market stability with prices in excess of what could be obtained in a free market.
If, on the other hand, the North Sea producers should cooperate with OPEC, the market share would exceed 50%, and the negotiated price could be kept at a high level for a longer period of time.
Bohl, .D.R.. (T9811): % emand Behavior -of Energy Elasticities"
Press, Baltimore, USA, 1981.
BP (1986): "BD statistica eview of world ene ", London June 1986.
Calarco, J.V. (1985): "
to Falling Oil Prices", The Coal Situation, Vol. 5 - No. 4, September 1985.
CERA (1986): "Oil Prices at S$15-17: Reignitin emand?", Decision Brief, Cambridge Energy Research Associates, Massachusetts, USA, 1986.
CIA (1986): "International Ener Statistical Review", Central Intelligence Agency, USA, June 1986.
Desprairies P. et al (1985): "Progressive Mobilization of Oil Resources", Energy Policy, December, 1985.
DRI (March 1986): "DRI Europe Special Report:
of the Oil Price Collapse", Data Resources Inc., London, March 1986.
DRI (spring 1986): "International Oil Market Status and Forecast", International Oil Bulletin, Data Resources Inc., Massachusetts, USA, spring 1986.
DRI (1985): "European Energy Forecasting Report"
Resources Inc., Paris, France, June 1985.
Dwyer, D. (1986): Private communication, IEA, Paris, France, June 1986.
Franssen, H.T. (1985): "North sea Petroleum Developments o e O o 5, OFFSHORE GØTEBORG '85, Gothenburg, Sweden, February 1985.
IEA (1986): "Oil Market Report", Paris, July 1986.
IEA (1982): "World Energy Outlook", Paris, 1982.
OECD (1983): "
Fall in oil Prices". Working Papers no. 8. OECD, Economics and Statistics Department, June 1983.
PIW (1986): Petroleum Intelligence Weekly, No. 32, New York, USA, Aug. 11, 1986.
Purvin & Gertz (1986): "Weste uropea e Petroleum Product Pricing Analysis", Purvin & Gertz Inc.
London, June 1986.
Texas Eastern Corp. (1985): in Petroleum Intelligence Weekly (PIW) New York, USA, December 9, 1985.
Verleger, P.K. (1982): "Oil Market in Turmojl", Ballinger Publishing Company, Massachusetts, 1982.
Wharton Econometric Forecasting Associates (1986)
Middle East Economic Digest, May 1986.
15 USD /fat frem til år 2000?
I diskusjoner omkring oljeprisens utvikling frem til år 2000 er det en vanlig oppfatning at de relativt sett lave oljeprisene man har sett i første del av 1986 vil være midlertidige.
Forventningene går i retning av realpriser for råolje i området 25 — 40 USD/fat rundt år 2000.
AV GUNNAR MYHR OG MORTEN H.
De store oljeprisøkningene 1 1973/1974 og 1979/1980 medførte at trenden i oljekonsumveksten som man så i 1960-årene snudde. Det globale oljekonsum 1 vesten (verden ekskl. sentralstyrte land) hadde sitt maksimum i 1979 med gjennomsnittlig dagsforbruk på 50.9 millioner fat. For 1985 var det tilsvarende tall 45.1.
Det høye prisnivået ga (høykostnads-) produsentene 1 vesten utenfor OPEC et sterkt incitament til økt letevirksomhet og produksjon, med det resultat at ikke - OPEC produksjonen økte fra 19.8 millioner fat/dag i 1979 til 25 mill. fat/dag i 1985.
Opec som ønsket å opprettholde høye priser (avtale prismål), måtte redusere sin produksjon fra 31.5 mill. fav dag (inkl. NGL) i 1979 til 17.2 mill. favdag i 1985 (inkl. NGL).
Den vestlige verdens totale energikonsum var omtrent uendret fra 1979 til 1985.
ad av 'energieffektivisering.
3 2.2%/år i gjennomsnitt. Oljeandelen sank i perioden fra 52.3% til 44.6%, mens kullandelen steg fra 18.9% til 22.3%, kjernekraftandelen fra 2.9% til 6% og hydro-elektrisitet fra 7.2% til 8.2%. Naturgass opprettholdt sin markedsandel.
Det skjedde altså en betydelig substitusjon først og fremst til kull og kjernektaft. Dette gikk spesielt på bekostning av tungoljeforbruket som sank til omtrent det halve i de industrialiserte vestlige land. I de mindre utviklete land i vesten sank tungoljeforbruket bare med ca. 4%.
2. Energietterspørsel i relasjon til økonomisk vekst, teknologisk utvikling og næringsstrukturutvikling.
De økte oljepriser har ført til at oljeproduktene har tapt markedsandeler, med unntak av transportsektoren. Dette medførte at prisen på andre energibærere også ble presset oppover. De høye energiprisene førte til at det ble lønnsomt å erstatte gammelt produksjonsutstyr med mindre energikrevende utstyr og prosesser.
I denne artikkelen går vi kort gjennom den historiske utviklingen på energimarkedet før vi gjennomgår de fundamentale forhold på tilbuds- og etterspørselssiden i oljemarkedet.
Konklusjonen er at oljeprisene kan bli under 15 USD/fat i en tilnærmet frikonkurransesituasjon frem mot år 2000.
fra mer til mindre energikrevende sektorer : økonomien. Dette har særlig funnet sted innenfor OECD-området.
De høye energiprisene har altså satt igang langsiktige prosesser som ikke er så lette å stoppe. Det gjelder først og fremst nyutvikling til mindre energikrevende teknologier på alle områder, men også forsterkningen av den generelle næringsstrukturendring i retning av mindre energikrevende næringer. Virkningene av disse prosessene vil vi først virkelig se effekten av fremover.
Generelt ser vi følgende trender fremover:
* Mindre energikrevende næringsstrukturer.
- fortsatt overgang til tjeneste-sektorer.
- forandring i industriproduksjonssammensetningen fra meget energi-intensive aktiviteter (råvarebaserte) til mer høyteknologiske industrier /prosesser (kompetansebaserte). (Dette gjelder spesielt 1 1-landene, men også totalt sett vil energitung industri vokse saktere enn øvrige aktiviteter).
* Høyere energieffektivitet innen ulike aktiviteter.
- fortsatt teknologiske fremskritt selv med relativt sett lavere oljepnser slik at energieffektiviteten 1 alle sektorer innen økonomien øker når kapitalutstyr gradvis blir erstattet.
Frem mot 1973 (1950-60 årene) var forholdet mellom veksten i energiforbruk og veksten i BNP innenfor OECD på omkring 1.0. Oljeforbruket vokste derimot noe raskere og forholdstallet mellom oljekonsum-vekst og BNP-vekst var omkring 1.5.
I perioden 1973-84 var den gjennomsnittlige BNP-veksten innenfor OECD området omkring 2.3% pr. år. energiveksten var i underkant av 0.2% pr. år mens oljeveksten var -1.5% pr. år. Mellom 1974 og 1980 vokste både energi - og olje-etterspørselen med omtrent 2/3 av veksttakten i BNP, og etter prisoppgangene i 1979/1980 ble de tilsvarende forholdstallene negative Franssen (1985)
Oljetterspørselen vil som resultat av vedvarende lave oljepriser påvirkes gjennom økning 1 den økonomiske veksttakt og substitusjon tilbake tl olje.
Sosialekonomen nr. 9 1986 ser for det økonomiske al sjbake ul olje.
Det økonomiske aktvitetsnivset vil trclig øke. som en konsekvens av lave oljepriser. Data Rescurces Inc. (DRI-(mars 1986)) anslår BNP virkningen av en fata reduksjon 1 oljeprisene ul 15 $ ul a være ca. 0.
1986, omkring 1.5% 1 1987 og 0 igjen 1 1988 i OECD-området. De antar altså at den største effekten vil inntreffe det andre året d.v.s. 1 1987. De har dessuten den oppfatning at denne BNP-sumulansen en midlertidig effekt Det generelle aktivitetsnivået vil bli høyere i verden men den økonomiske veksttakt kommer r ulbake ul hve den ellers ville ha vært IEA har tentative anslag på at BNP i OECD-området vil ge 5% høyere 1 1990 med en rende prisnedgang r råolje til 10S/fat.
En studie fra OECD (1983) konkluderer med at e reduksjon 1 oljepnsen vil gl 1 BNP-nivået viv første året med 0.6%.
2t med 1.2%.
urgene har vært på samme :
inntektsomfordelingen som skjer jepredusen il oljekonsumenter. ul ak: veks: ;
Gunnar Myhr har B.S-graden :s ga) fre South Dakot. School of Mines & Technology sity of California har d ! ekonomvledelse fra NT. Norsk Hydro. Rafhne.
980 trolig ligge 2-3% høyere med ann på !5 S/fat og ca. 5% høyere med oljepris på iC S:
En annen konsekvens av reduserie cliepriser og dernest økt vekst : BNP. er en midlertidig redusert inflasjonstakt innenfor C Dette igjen kunne dempe de: generelle ren For utviklingsla ndene og de såkalte NIC landene (Newly Indus sed Countries), som tidligere har mangiet hard valuta c t redusert inntekt (BNP), vil inntektsoverføringen ved lave oljepriser samt redusere rentekosinader forbecr lingsbalansen Dette vil kunne medføre økt ¢ F shk at en vikua beskrankning for okonomisk vekst blir redusert. Som udligere nevnt er økonomien ! kiuelle landene påg et mindre sofistker:
En interessan: betraktning er 0 snudd med vedvarende lavere cl;
Kontraktsprisene på gass er koblet til ol produktpriser og tildels råoljepnser Cessprisen vil derfor følge disse prisene med en ass udsforsinkelse sørstatene : USA har det forøvrig u nkl e: seg et spot ked for gass. For å beholde r spotprisen på ass fulgt client 1 n noe.
1 og kjernekraft ville 30 JSD/fat.
Morten H Ra men varen y ved Gruppen for Ressurssiudier assisteni. og I Di 1980-85.
kraftverk med oljebrenningskapasitet skal vurdere overgang til tungolje, (1985 USD/fav).
USAs ariere 13.46 (10.14-16.11) 7)
FE 15.12 (12.40-17.70) *)
Japan akan Bey Th or 14.45 (13.46-16.44) *)
Kilde: Calarco (1985) *) Intervallene er på cif pnser for kull i angitt remon.
Tabell 1 viser hvilke «break-even» priser som gjelder i.. at kullfyrte kraftverk med substitusjonsmulighet skal skifte til tungolje. Som man ser tilsvarer dette oljepriser (1985 verdi) i området 12-16 $/fat, avhengig av hvilke regioner man betrakter. Tallene i tabell 1 er for eksisterende kraftverk. For nye anlegg vil lønnsomhetsgrensen ligge omkring 5-6 $/fat høyere.
En meget viktig forutsetning som ligger til grunn for disse tallene, er en kullpris på 50-60 S/tonn, et prisnivå som kull hadde høsten 1985, altså før man fikk det dråstiske prisfallet i vinter/vår 1986.
Det har vist seg at spotprisene for kull også følger råoljeprisen nedover slik at det relative konkurranseforholdet mellom kull og olje fortsatt er tilstede i kulls favør, men dog redusert.
Tabell 2 gir en oversikt over kort- og mellomlangsiktige (0-3 år)
>kostning av gass og kull. Tallene er basert på en . ,epris i området 15-17 $/fat. Som man ser er potensialet ganske høyt, mellom 3.2-4.5 mill. faydag, mens den sannsynlige grense ligger betraktelig lavere, mellom 0.7-1.2 mill. fat/dag.
Grunner til dette er politiske ensker om & bevare en viss kullindustri (England og Tyskland), samt at kull- og gassprisene sannsynligvis vil følge oljeprisene over tid slik at disse energibærerne relativt sett vil være konkurransedyktige med olje.
I første halvdel av 1986 har disse substitusjonseffektene hatt liten gjennomslagskraft. Frem til jum: 1986 (Dwyer (1986)) har substitusjonseffekter i USA bare medført en ekning i oljekonsumet med 100.
I figur 1 har vi skissert etterspørselskurver på kort sikt (1 år), mellomlang - (3-Sår) og lang sikt (10-15 år). Disse kurvene bygger på studier fra en rekke internasjonale organisasjoner; DRI (mars 1986), DRI (våren 1986), Wharton Econometrics Forecasting Associates (1986). Purvin & Gertz (1986) samt samtaler med IEA-analytikere. I ulegg har forfatterne vurdert disse studiene 1 lys av udligere publiserte pris- og inntektselastiteter, Bom (1981). Verleger (1982), IEA (1982)
På kort sikt oppar litteraturen vanerende historiske priselastisiteter for råolje. mellom -0.05 og -C 2. Pz lengre sikt oppgis tilsvarende tall mellom -0.3 og -1.0.
I de langsiktige etterspørselskurver i figur 1, har vi valgt et betydelig variasjonsområde på BNP-vekstens innvirkning på oljeetterspørselen. Med en BNP-vekst på 10% antas oljeforbruket å øke med 2 til 7.5%. Den økonomiske vekst antas å være 3% pr. år fram til år 2000.
Når det gjelder priselastisiteten har vi også valgt å ta hensyn til en stor grad av usikkerhet her. Den langsiktige priselastisitet har vi valgt å ligge mellom -0.3 og -0.85.
Et viktig forhold som bør trekkes frem m.h.t. priselastisiteter, er at de historisk beregnende gjelder for stigende priser. Disse vil etter all sannsynlighet være betydelig større enn om prisene synker. En tommelfingerregel som framkom i samtaler med IEA-analytikere er at forholdet er minst 3 til 2. Årsaken til dette er først og fremst de teknologiske forandnnger som de høye oljeprisene medførte. Dels henger det sammen med irreversible investeringer og dels at ny teknologi for framtiden har blitt utviklet og vil komme gradvis inn ved nye investeringer.
Et annet er spørsmålet om hvor mye av råoljeprisendringene som slår gjennom på prisene til sluttforbruker. I «World Energy Outlook» IEA (1982) regnes det med at ca. 40% av råoljeprisendringene slår igjennom i transportsektoren, mens man får et gjennomslag på mellom 70-80% i andre sektorer.
Disse prosentsatsene blir trolig enda lavere 1 dag p.g.a. endringer i avgiftspolitikken på olje/oljeprodukter. De råoljeprisendringene som har skjedd det siste året har bare medført reduksjon i prisene til sluttforbruket med 10-20% for drivstoff til transportformål, mens prisreduksjonen var 30-40% (varierer fra 10% til 60% mellom land) for produkter til andre formål (fyringsoljer og tungolje), IEA (1986). Råoljeprisen sank i tilsvarende periode med 60%.
Tabell 2. Kortsiktig — substitusjonspotensiale innenfor OECD for olje på bekostning av gass og kull.
Teknisk Sannsynlig maksimal økning grense for økning (mill. fat/dag) (mill. fat/dag)
Verk... ro re iv 0.8-0.9 0.2-0.
generering ..: +. 0. + 4 0.3-0.
Aeg... J 1.0-1.5 0.2-0.4 Vest Europa.
fynngsmuligheter -....... 0.7-1.0 0.2-0.
industnelle fyringsanlegg. . 0.406 0.1-0.2 Sum vee ois man ues , 3.
Kilde CERA (1986)
Sosialøkonomen nr. 9 1986 Etterspørselskurver på kort, E" (1 år), mellomlang, E" (3-5 år) og lang sikt E' (10-15 år) for vesten (faste 1985 —USD).
Tilbudssiden 1 det internasjonale oljemarkedet har siden 1973 vær dominert av OPEC. Fra 1973/74 har markedsatferden til denne organisasjonen hatt karakter av et priskartell, hvor de avtalte faste priser på de forskjellige typer råoljer.
Utover i 1980-årene tvang markedet OPEC til å skifte strategi til et markedsdelingskartell, hvor medlemslandene avtalte produksjonskvoter innenfor en total OPEC-kvote som er middel til å opprettholde et høyt prisnivå.
Jljeprodusenter utenfor OPEC har p.g.a. det høye tr  ivået vært stimulert til leting etter og produksjon av olje i høykostnadsområder.
Oljeprodusentene har i prinsippet to fundamentale beslutningskntener. På kort sikt vil driften opprettholdes så lenge de variable produksjonskostnadene dekkes (korttidsgrensekostnader). P& meget kort sikt vil produsentene sannsynligvis også gå under dette nivået så lenge de får dekket vedlikeholdskostnadene som kreves for at brønner og produksjonsutstyr skal være operasjonelle. På lengre sikt vil produsentene ha dekket både faste og vanable kostnader (langndsgrensekostnad) før nye investeringer gjennomføres.
Ved å sortere feltene etter stigende kostnader, kan man konstruere grensekostnadskurver. I et frikonkurransemarked vil tilbudskurven falle sammen med grensekostnadskurven.
Med en kartellisering av markedet vil tilbudskurven kunne flyttes til venstre i figuren.
I figur 2 er en angivelse av korttidsgrensekostnadskurven (T%) slik den artet seg ved årsskiftet 1985/86, eller tUlbudskurven på kort sikt 1 en frikonkurransesituasjon. (Texas Eastern Corp. (1985))
Ved årsskiftet 1985/86 var tilbudskurven forskjøvet 10 mill favdag til venstre i figuren. Dette skyldtes OPEC's innskrenkning i sin totalproduksjon for å holde prisnivået oppe. Dette representerer et fravær av ca. 10 mill favdag ledig kapasitet innen OPEC. Denne ledige kapasiteten har marginalkostnader mindre enn 6 USD/fat. Denne ledige kapasiteten kan OPEC på kort varsel igjen tilby på markedet (0—3 måneder). Tilbudskurven(e) angir produksjon innenfor vesten (eksl. nettoeksport fra sentralstyrte økonomier).
Tilbudet av olje i begynnelsen av 1986 har vært preget av at OPEC med sin lavkostnads-produksjon produserte bare omkring 60-70% av den produksjonskapasitetet de kan utnytte på kort sikt (0-3 måneder), mens ikke-OPEC produsentene produserte med tilnærmet full kapasitetsutnyttelse.
Ytterpunktene i oljemarkedet kan best illustreres ved følgende to eksempler: Oljeproduksjonen fra de såkalte «Stripper wells» i USA (felt som har en gjennomsnittlig dagsproduksjon på under 10 fat) har gått for fullt til tross for driftskostnader på omkring 20 $/fat. Samtidig produserte Saudi Arabia bare med omkring 45% kapasitets utnyttelse. Marginalkostnadene er her i området 0—4 $/fat.
Den tilgjengelige produksjonskapsiteten innenfor OPEC på kort sikt utgjør ca. 27.5 mill. fat/dag i 1986, PIW (1986). På noe lengre sikt kan denne produksjonskapasiteten øke betydelig. Allerede innen 1990 kan Midt-Østen landene øke sin kapasitet med ca. 10 mill. favdag. Denne kapasitetsøkningen representerer produksjon fra eksisterende oljefelt hvor det pr. i dag er logistikkbegrensninger (rørledningskapasitet). (Den installerte produksjonskapasitet fra eksisterende felt er 41.4 mill. fat/dag, mens den tilgjengelige kapasiteten er 90%-95% av denne, CIA (1986).
På enda lengre sikt kan (OPEC) produsentene i Midt-Østen øke sin kapasitet ytterligere ved økt utbygging av kjente lavkostnadsfelt med totalkostnader under 4 USD/ fat. I tabell 3 er det satt opp antatte fremtidige råoljereserver i ulike kostnadsklasser. Til sammenligning var oljeforbruket i 1985 45.1 mill. fat pr. dag som svarer til 2.15 milliarder tonn pr. år, BP (1986).
Tabell 3. Totale produksjonskostnader for råoljereserver i verden fordelt på typer reserver (eksl. kummulativ produksjon frem til i dag). Tallene er i milliarder tonn.
Totale produksjonskostnader Reservekategori (1983 USD/fat)
Påviste reserver ........ 10 20 5 - - 95 Fremtidige funn 20 30 20 5 - 75 Økt utvinning fra *
og påviste reserver .... - 30 35 20 5 90 * Fremtidige funn .......
Kilde. Desprairies etal (1985) 27 Tilbudskurver for råolje i vesten på kort sikt (T*), mellomlang (T") og lang sikt (T') i en frikonkurransesituasjon (faste 1985 - USD). (Eksl. nettoeksport fra sentralstyrte økonomier).
I figur 2 oppsummerer vi denne drøftingen av tilbudssiden med de mulige tilbudskurver for råolje i vesten på kort, T* (1 &r), mellomlang, T™ (3-5 ar) og lang sikt, T' (10-15 år) i frikonkurransesituasjon. En viktig forutsetning her er at ny produksjonskapasitet kommer fra felt med lavest kostnad. Til tross for at olje er en uttømbar ressurs er reservene så store at innenfor udsperspektivet vil det ikke være noen begrensning på tilbudssiden. Med lave oljepriser vil det være lønnsomt med «ny» olje bare fra lavkostnadsprodusenter.
I figur 3 har vi satt sammen tilbud- og etterspørsels- »Jdrvene fra figurene 2 og 1 for å finne mulige markedsbalanser på sikt.
Hovedkonklusjonen er, under de gitte forutsetninger, at realprisene for råolje kan holde seg under 15 USD/fat frem til år 2000, selv med en betydelig etterspørselsøkning.
På kort og mellomlang sikt kan oljeprisene ligge 1 området 6-10 USD/fat, mens de på lang sikt kan være i området 8-16 USD/fat i en tilnærmet frikonkurransesituasjon. Det er altså ingen vesentlige beskrankninger på tilbudssiden som skulle forhindre at etterspørselsøkningen ved lave råoljepnser skulle bl ulfredsult. I ullegg vil nettoeksporten fra sentralstyrte land som 1 1985 var 1.8 mill. fat pr. dag, kunne presse råoljeprisene ytterligere nedover til under 15 USD/fat. Usikkerheten i anslag for den fremtidige nettoeksporten er stor. Inntekter 1 utenlandsk valuta står i fokus og med redusert oljepns vil de heller øke sin eksport enn redusere den. Trolig vil nettoeksporten framover holde seg 1 området 1] ul 2 millioner fat pr. dag.
Totalproduksjonen fra OPEC kan 1 år 2000 komme opp 1 over 40 mill.
Markedstilpasning ved en tilnærmet fri konkurranse ! oljemarkedet frem til år 2000 (faste 1985 — USD).
Et vesentlig element som vi ikke har tatt hensyn til her er som tidligere nevnt, forbrukerlandenes avgiftspolinkk m.h.t. olje og oljeprodukter. Erstattes råoljeprisnedgangen fullt ut av avgifter, slik at sluttforbrukerne ikke ser noen prisnedgang, vil etterspørselen etter olje bare påvirkes av BNP-effekten de økte offentlige inntekter og bruken av disse gir. Dette ville kunne presse raoljepnsen enda lengre ned.
6. Et fritt vs.
Fra høsten 1985 frem til scmmeren 1986 har vi! prinsippet sett en gradvis utvikling 1 retning av et fritt oljemarked. Hva ville den mest sannsynlige utviklingen ha blitt hvis OPEC hadde klart å holde sammen enda en tid?
Saudi Arabias rolle som sving-produsent innenfor OPEC medførte at landets oljeoproduksjon falt fra en topp pa 10.2 mill. favdag 1 august 1981 til 2.2 mill. favdag 1 august 1985. Den tilsvarende reduksjonen fra de andre OPEC landene har bare vært på omkring 41%, samtidig økte ikke-OPEC produsentene i vesten sin produksjon for det 10. året på rad.
Det var et tidsspørsmål når Saudi Arabia måtte endre sin politikk. Med en fortsatt økning i ikke-OPEC produksjonen, mangelfull disiplin innad i OPEC-kartellet og ingen vesentlig etterspørselsøkning, er det ikke utenkelig at Saudi Arabia måtte redusere sin produksjon tl under | mill. favdag og kanskje helt ned til null i løpet av de neste 1-2 årene for at prisene skulle holde seg oppe på et høyt nivå.
I lys av dette hadde Saudi Arabia nesten ikke noe valg Det var bare et udsspørsmel nar skiftet 1 politikk matte komme. Inntektstapet ville kanskje blitt større dersom de fortsatte sin poltikk som tidligere.
Dette skifte : politikk. som formelt sett ble vedtatt under OPEC-møtet 8. desember 1985. innebar at OPEC med Saudi Arabia 1 spissen. skiftet fra å være prisfastsettere og kvantumsregulerende ul a definere en Større markedsandel (kvantumstilpassere)
Sosialøkonomen nr 9 1986 nasjoner med relativt sett store reserveanslag og liten befolkning, og de med forholdsvis lave reserveanslag og stor befolkning.
Saudi Arabia og Kuwait med sine relativt sett begrensete evner til å absorbere høye oljeinntekter. har en mye lengre tidshorisont når de vil maksimere inntektene av sine oljereserver. Irak, Libya og Algeri har en mye kortere tidshorisont ved en tilsvarende inntektsmaksimering av sine ressurser. Dette henger sammen med relativt sett lave reserveanslag, stor befolkning og høy absorbsjonsevne når det gjelder oljeinntekter. Disse landene ønsker derfor å få hevet oljeprisene raskt.
Dersom dagens OPEC virkelig blir enige om å forlate målsettingen om økte markedsandeler for igjen å heve prisene raskt til 1985-nivå, er det meget trolig at dette nivået bare vil vare en kort periode, fordi OPEC-produksjonen ville måtte fortsette å synke. Det skyldes at om oljeprisene fortsatte på det nivå vi hadde i perioden 1980-85 ville oljeetterspørselen trolig ikke vokse de nærmeste årene.
Om oljeprisene raskt skal komme opp og vedvare på e'
.- — 86, hvor spotprisen for Brent Blend falt fra 27 $/fat pr. 1. jauar til under 10 $/fat i slutten av juli, må man reelt sett få en «ny» kartellisering av markedet.
Dette nye kartellet bør trolig ha en større markedsandel enn hva OPEC hadde høsten 1985 (38.3% for 2. halvdel -85 inkl. NGL) for at det nye kartellet skal kunne holde stabile og relativt sett høye priser over en lengre tidsperiode.
Mexico, Egypt.
Oman potensielle samarbeidsland med OPEC. De fem .
første landenes produksjonskapasitet er ca. 4.6 mill. fav dag, mens produksjonen i første del av 1986 var omkring 3.7 mill. fat/dag. Disse landenes produksjon sammen med OPEC-produksjonen utgjorde en markedsandel : 1985 på omkring 46%. Dette ville være en sterkere enhet enn om OPEC var alene, men selv dette tallet kan være 1 minste laget for varig stabilitet med priser over markeds-klareringen ved frikonkurranse.
landene også med i samarbeidet med OPEC vil markedsandelen komme godt over 50%. og den politisk bestemte pris kan holdes på et høyere nivå lengre. Dette avhenger selvsagt av bl.a. det interne konfliktnivå i et slikt utvidet kartell.
Bon.D R (1981) «Analyzing Demand Behavior - A Study of Energy Elasticines»= The John Hopkins University Press. Baltimore. USA.
BP (1986) «BP staustcal review of world energy» London.
Calarco J V (1985). «Sensitivity of World Coal Markets to Falling Oil Prices» The Coal Situation. Vol. 5 - No. 4. September 1985.
CERA (1986) «Oil Prices at 815-17 Reigniung Demand?». Decision Bnei. Cambndge Energy Research Associates, Massachusetts, USA.
CIA (1986) «international Energy Stausucal Review». Central Intelhgence Agency. USA. jum 1986.
Despraines P et al (1985). «Progressive Mnbilization of Oil Resources». Energy Policy. Desember.
DRI (mars 1986). «DRI Europe Special Report The Impact of The Oil Price Collapse» Data Resources Inc. London. mars 1986.
DR! (våren 1986): «/nternauonal Oil Market Status and Forecast». Internauonal Oil Bulleun. Data Resources inc.. Massachusetts. USA. våren 1986.
DRI (1985) «European Energy Forecasting Reports, Data Resources inc. Paris. Frankrike. jun:
Dwyer. D (1986) Pnvat kommunikasjon. IEA. Pans. Franknke. jun: 1986.
Franssen. H. T. (1985) «North Sea Petroleum Developments in the Context of the Global Outlook for Oi! and Gas».. OFFSHORE GØTEBORG '85. Gøteborg. Svenge. februar 1985.
IEA (1986) «Oil Market Report». Pans. juli 1986.
IEA (1982): « World Energy Outlook» Pans. 1982.
OECD (1983): «Syumulated Macroeconomuc Effects of a Large Fall in ou Prices» Working Papers no 8 OECD. Economics and Statistics Department.
PIW (1986). Petroleum Intelligence Weekly. No. 32. New York. USA.
Purvin & Gertz (1986): «Western European Refining and Petroleum Product Pncing Analysis», Purvin & Gertz Inc: London. jum 1986.
Texas Eastern Corp. (1985) 1 Petroleum Intelligence Weekly (PIW). New York. 9. desember 1985.
Verleger. P K. (1982): «Qiu Market in Turmoil». Ballinger Publishing Company. Massachusetts, 1982.
Wharton Econometric Forecasting Associates (1986) : Middle East Economic Digest. Ma:
KONTINGENT 2.
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29 Lave oljepriser frem til 1990, moderate konsekvenser på etterspørselssiden?
gan av de låga oljepriserna.
I denne artikkelen vurderes etterspørselsutviklingen for olje frem til utgangen av 1990 for den ikke kommunistiske delen av verden (Vestverden) ved vedvarende lave oljepriser (realpriser [1985-verdi] i omradet 15 USD/fat).
Konklusjonene som trekkes er basert på en gjennomgang av de senere års utvikling på energimarkedene. vurdering av fremtidig substitusjonspotensiale olje vs kull og gass. teknologisk utvikling. inntektseffekter av lavere oljepriser. relasjoner mellom BNP-vekst og oljeforbruk. forskjellige policy-messige tiltak etc.
Konsekvensene blir kanskje mindre enn hva man på forhånd skulle anta. For OECD-områdene vil veksten i oljekonsum sannsynligvis begrense seg til omkring 6 prosent. mens den for utviklingslandene (egentlig de såkalte NICs ["Newly Industrialized Countries™]) sannsynligvis vil bli en del storre. kanskje helt opp til 15-17 prosent. Grunnen til dette er at økonomiene innenfor denne NICs - grupperingen er mindre sofistikerte slik at økonomisk vekst vil finne sted i energi (olje) krevende sektorer av økonomien.
+ Fortatteren vil takke Morten Raaholt, Norsk Hydro. for svært mange nyttige kommentarer og råd.
Den ikke kommunistiske delen av verdens totale energikonsum i 1979, toppåret når det gjelder energikonsum, var på 4732.4 millioner tonn oljeekvivalenter (mtoe). De relative andeler for olje, gass og kull var henholdsvis 52.2. 18,8 og 18.9 prosent. Kjernekraft og vannkraft utgjorde henholdsvis 2.9 og 7,2 prosent av energikonsumet.
I 1985 hadde det totale energikonsumet bare økt marginalt. til 4823,2 mtoe (økning på 1,9 prosent). Den relative fordelingen var derimot sterkt forskjøvet. Oljens andel var sunket til 44.6 prosent. mens gass' andel var omrent opprettholdt med 18,9 prosent. Kull derimot hadde økt sin markedsandel til 22.3 prosent.
Det hadde også vært en sterk økning for kjernekraft som hadde økt sin ande! av energikonsumet til 6.0 prosent. For vannkraft hadde denne økningen vært mindre, til 8.2 prosent. (Basistall: BP [1986])
De store oljeprisokningene i 1973/1974 og 1979/1980 medforte at trenden i oljekonsumveksten som man så i 1960- og 1970-årene ble snudd.
USA OECD-Europa*
Tungoljekonsum Konsum av alle andre (olje)
* Tallene er justert for kullstreiken i England.
Kålla:
konsum innenfor Vest verden nådde også sitt maksimum i 1979 med gjennomsnittlig dagsforbruk på 52.4 millioner fat. For 1985 var det tilsvarende tall 45,6.
Det høye prisnivået ga (høvkost)produsentene utenfor OPEC et sterkt incitament til økt utforskning og produksjon. med det resultat at ikke-OPEC produksjonen økte fra 21,0 millioner favdag i 1979 til 26,8 millioner fat/dag i 1985.
OPEC som residualtilbyder i dette markedet, måtte se sin produksjon bli redusert fra 31,6 mill favdag (inkl NGL) i 1979 til 17,2 mill fat/dag i 1985 (inkl NGL) for å kunne holde sitt prismål. (Basistall: IEA [1986])
Ser en på oljekonsumutviklingen noe mer detaljert, får en et klarere bilde av hvilke effekter som har gjort seg gjeldene.
Substitusjon til gass. kull og kjernekraft spesielt på bekostning av tungolje var den mest dominerende faktor når det gjelder reduksjon i oljekonsumet for USA og andre OECD land i 1980-årene.
I 1980 var det totale tungoljeforbruket i USA og OECD-Europa pa 6.7 mill fat/- dag. I 1985 var dette tallet redusert til 4.25 mill favdag, en reduksjon på 36.6 prosent. Konsumet av alle andre (olje)produkter i USA og OECD-Europa falt fra 24.4 mill fat/dag i 1980 til 23,6 mill fat/dag i 1985. altså en reduksjon på bare 3.5 prosent.
2,51 1.15 4.18 3,10 14,59 14,45 9,82 9,10 17,10 15.60 14.00 12.
Oljeprodukter har. med unntak i transportsektoren, redusert sine markedsandeler pga økte oljepriser. Som en konsekvens av dette har prisene på andre energibærere som kull og gass også fulgt oljeproduktprisene. Resultatet av disse generelt sett høye energiprisene, har vært et meget sterkt incitament for å erstatte produksjonsutstyr generelt med mindre energikrevende utstyr og prosesser, samtidig som det primært innenfor OECD har funnet sted og sannsynlig vil finne sted en strukturendring fra mer til mindre energikrevende sektorer i økonomiene.
Uavhengig av eventuelt lave oljepriser vil det trolig være momentum i følgende trender innenfor industrilandene (OECD):
- forandring i industriproduksjonssammensetningen fra meget energi-intensive aktiviteter (råvarebaserte) til mer høyteknologiske industrier/prosesser (kompetansebaserte)
fortsatt teknologiske fremskritt slik at energieffektiviteten i alle sektorer innen økonomiene øker når kapitalutstyr gradvis blir erstattet.
holdet mellom veksten i energiforbruk og veksten i BNP innenfor OECD på omkring 1. Oljeforbruket vokste derimot noe raskere og forholdstallet mellom oljekonsum-vekst og BNP-vekst var omkring 15.
Etter den sterke prisoppgangen i 1973/1974 ble de tilsvarende tallene negative. Mellom 1974—1980 vokste både energi- og olje-etterspørselen med omtrent 2/3 av veksttakten i BNP, og etter prisoppgangene i 1979/1980 ble de tilsvarende forholdstallene negative igjen, Franssen [1985].
Totalt for hele perioden 1973-84 var den gjennomsnittlige BNP-veksten innenfor OECD området omkring 2.3 prosent pr år. energiveksten var i underkant av 0,2 prosent pr år mens oljeveksten var -1,5 prosent pr år.
1979 1980 1981 1982 1983 1984 1985 (est)
" Tallene er justert m h t kullstreiken i England i 1984/1985.
Källa: IEA [1985].
Den underliggende konsumtrenden viser her en klar tendens i retning av fallende oljeintensitet. dog med en avtagende prosentvis reduksjon.
Realprisen for olje i det aktuelle tidsrommet har ven relativt stabil i lokal valuta.
For utviklingslandene generelt.
mer presist de såkalte "Newly Industrialized Countries" (NICs), er de samme utviklingstendensene ikke til stede. Her ses en klar trend i at økonomisk vekst i stor grad skjer innenfor de tradisjonelle tungindustriområdene (den råvare-baserte industri). Denne tendensen bæres først og fremst ved de fundamentale lønns- og kostnadsforskjellene som gjør seg gjeldene mellom de industrialiserte land og utviklingslandene.
Som tidligere nevnt har de relativt sett høye oljeproduktprisene medført en sterk substitusjonseffekt i favør av kull og gass, spesielt på bekostning av tungolje.
Med realpriser på olje frem til 1990 i området 25-30 USD/fat, ville sannsynligvis denne trenden ha fortsatt, dog med en avtagende rate. En interessant betraktning er om denne trenden vil bli snudd med vedvarende oljepriser under 20 $/fat.
Kontraktsprisene på gass er direkte koblet til produktpriser og tildels råoljepriser. Gassprisen vil derfor følge råolje- og produktprisene med en viss tidsforsinkelse.
I sørstatene i USA har det utviklet seg et spotmarked for gass. For å beholde markedsandeler har denne spotprisen på gass fulgt oljeprisene nedover i første halvdel av 1986 uten noe tidsforsinkelse.
Et element som har blitt trukket frem i energidebatten er på hvilke prisnivåer olje begynner å frata kull markedsandeler:
Tabell 3 viser hvilke breakeven-priser som gjelder for olje for at kullfyrte kraftverk med oljebrenningskapasitet ("dual fired") skal skifte føde til tungolje. Som man ser tilsvarer dette oljepriser (1985 verdi) i området 12-16 $/fat. avhengig av hvilken region man betrakter. Tallene i Tabell 3 er for eksisterende kraftverk. For nye anlegg vil breakeven-prisene ligge omkring 5-6 USD/fat høyere.
Tabell 3 Breakeven oljepriser for eksisterende kullfyrte kraftverk med oljebrenningskapasitet ("dual fired""), (1985 USD/fat).
13.16 (10.14-16.11)
15.2 (12.40-17.70)
14.45 (13.46-16.44)
() Range basert på cif priser for kull i angitt region.
"forholdstall mellom tungoljepris og råoljepris. Kålla:
En meget viktig forutsetning som ligger til grunn for disse tallene. er en kullpris på 50-60 $/tonn. et prisnivå som kull hadde høsten 1985 altså før man fikk det drastiske prisfallet vinter/vår 1986.
Det har vist seg at spotprisene for kull har falt med fallende oljepris slik at det relative konkurranseforholdet mellom kull og olje fortsatt er tilstede i kulls favor. men dog redusert.
Tabell 4 gir en oversikt over kort- og mellomlangsiktige (0-3 år) substitusjonsmuligheter i favør av olje på bekostning av gass og kull. Tallene er basert på en oljepris i omradet 15-17 $/fat.
Som man ser er potensialet ganske høyt. mellom 3.2—.5 mill fat/dag. mens den sannsynlige grense ligger betraktlig lavere, mellom 0.7-1.2 mill favdag. Grunner til dette er politiske ønsker om å bevare en viss kullindustri (England og Tyskland). samt at kull- og gassprisene sannsynligvis vil følge oljeprisene over tid slik at disse energibærerne relativt sett vil være konkurransedyktige med olje.
I forste halvdel av 1986 har disse substitusjonseffektene hatt liten gjennomslagskraft. Frem til juni 1986 (Dwver [1986]) har substitusjonseffekter i USA bare medført en økning i oljekonsumet med 100 000 favdag.
0.90% | 1,10" 14.96 | 12.24 (11.27-17.90) (9.22-14.65) 16.80 13.75 (13.78-19.67) (11.27-16.09) 16.
(14.96—18.27) (12.24-14.95)
Vedvarende lave oljepriser vil medføre en kraftig stimulans for det økonomiske aktivitetsnivået. "The Economist" [1986] vurderer at en reduksjon på 10 USD/fat i oljeprisene vil medføre en økning i BNP for OECD-området på mellom 0,5-1.0 prosent (for 1986).
Data Resources Inc [1986] vurderer den tilsvarende BNP effekten til å være ca 0.5 prosent i 1986, omkring 1,5 prosent i 1987 og 0.1 prosent igjen i 1988. De antar altså at den største effekten vil inntreffe i 1987. De har dessuten den oppfatningen at denne BNP stimulansen er en temporær effekt.
En annen konsekvens av reduserte oljepriser og dernest økt vekst i BNP, er en redusert inflasjonstakt innenfor OECD. Dette vil igjen kunne dempe det generelle rentenivået.
For utviklingslandene og de såkalte NICs landene, som tidligere har manglet hard valuta og hatt redusert inntekt (BNP). vil inntektsoverføringen ved lave oljepriser samt reduserte rentekostnader forbedre betalingsbalansen. Dette vil kunne medføre økt oljeimport slik at en viktig beskrankning for økonomisk vekst vil bli redusert.
gass og kull | teknisk sannsylig maksimal økning grense for økning i | (mill favdag) (mill favdag) I US gassfyrte | elektrisitetsverk 0.8-0.9 0.
Med realpriser på olje i området 25-30 USD/fat frem til 1990. og moderat til lav økonomisk vekst innenfor OECD i samme tidsrom (BNP-vekst <2 prosent pr år), er det av grunner som er diskutert (avtagende oljeintensitet. strukturendringer, fortsatt substitusjon til kull og gass etc) meget troligt at veksten i oljekonsumet innenfor OECD ville ha blitt marginal.
Økonomisk empiri har ikke erfart virkningene av et raskt og dramatisk fall i oljeprisene. Hvis oljeprisene i tillegg fluktuerer meget sterkt. f eks realprisene varierer mellom 10—20 USD/fat frem til 1990, har en kanskje heller ingen økonomisk teori å støtte seg til når det gjelder BNP-effekter (og oljekonsum-vekst) ved generelt lavere oljepriser.
De nevnte BNP-effektene ved lavere oljepriser vil sannsynligvis være betydelig lavere hvis man får en sterkt fluktuerende prisutvikling.
generering 0.3—0.
fyringsanlegg 1.0-1.5 0.20.4 i Vest Europa.
"dual fire"
elkraft generering 0.7-1.0 0.2-0.
industrielle fyringsanlegg 0.40.6 0.1-0.
de energipriser vil medføre slik at aktivitetsnivået generelt og investeringslysten spesielt kan bli dempet.
På kort sikt (0-3 år) oppgir litteraturen varierende historiske priselastisiteter for råolje mellom 0,05 og 0.2. På lengre sikt (3-10 år) oppgis tilsvarende tall mellom 0.3 og 1,0. Det er rimelig å anta at de priselastisiteter som er beregnet historisk for stigende priser er betydelig større enn om prisene synker.
Slike beregninger. som ofte baserer seg på tidsserier helt tilbake til 1960-årene, vil ikke fange opp i tilstrekkelig grad de teknologiforandringene som har gjort — og som gjør seg gjeldende. En tradisjonell økonometrisk angrepsvinkel vil sannsynligvis overestimere økningen i forbruket.
Som tidligere diskutert er tyngden i teknologiforandringene og strukturendringene innenfor OECD så sterke at en økning i oljeintensiteten er lite trolig.
Policymessige tiltak vil forsterke denne effekten. For eksempel har EEC allerede vedtatt sitt energiprogram frem til 1990.
549 Her vil de prøve å fristille økonomisk vekst fra energietterspørsel. redusere oljekonsumet til rundt 40 prosent av det totale energikonsumet samt oke andelen av elkraft som er basert pa kull og kjernekraft til mellom 70-75 prosent.
Innenfor OECD - Europa er det omtrent bare Vest-Tyskland og Frankrike som ikke har økt avgiftene på petroleumsprodukter i 1986. I tillegg har storkonsumland som USA og Japan latt være a oke tilsvarende skatter.
Råoljeprisene i juni 1986 var bare omkring 1/3 av hva råoljeprisene var i juni 1985. Til tross for dette har reduksjonen i de innenlandske produktprisene vært meget begrenset.
En sammenligning av de innenlandske produktprisene mellom juni 1986 og juni 1985. gjort av IEA [1986]. viser at bensin- og dieselprisene bare har blitt redusert med omkring 15 prosent for en del større konsumentland (Frankrike. Vest-Tyskland, Italia. Spania. UK. Japan. USA). Vest-Tyskland viste den største reduksjonen med 23 prosent mens Italia bare hadde en reduksjon på 5.5 prosent.
Når det gjelder fyringsoljer var den gjennomsnittlige prisreduksjonen på omkring 26 prosent mens den var størst for tungolje. omkring 46 prosent.
En mulig videre reduksjon i de innenlandske produktprisene ved vedvarende lave oljepriser vil sannsynligvis skje sakte. Av rent fiskale grunner vil det være meget fristende for myndigheter å sette opp avgiftene ved ytterligere fall i produktprisene.
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