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When Is Growth Pro-Poor? Evidence from a Panel of Countries
- Gregory Garrison
- 2 years ago
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1 Forhcoming, Journal of Developmen Economics When Is Growh Pro-Poor? Evidence from a Panel of Counries Aar Kraay The World Bank Firs Draf: December 2003 Revised: December 2004 Absrac: Growh is pro-poor if he povery measure of ineres falls. According o his definiion here are hree poenial sources of pro-poor growh: (a) a high growh rae of average incomes; (b) a high sensiiviy of povery o growh in average incomes; and (c) a povery-reducing paern of growh in relaive incomes. I empirically decompose changes in povery in a sample of developing counries during he 1980s and 1990s ino hese hree componens. In he medium- o long-run, mos of he variaion in changes in povery can be aribued o growh in average incomes, suggesing ha policies and insiuions ha promoe broad-based growh should be cenral o he pro-poor growh agenda. Mos of he remainder of he variaion in changes in povery is due o poveryreducing paerns of growh in relaive incomes, raher han differences in he sensiiviy of povery o growh in average incomes. Cross-counry evidence provides relaively lile guidance as o he policies and insiuions ha promoe hese oher sources of propoor growh. The World Bank, 1818 H Sree N.W., Washingon, DC, 20433, This paper has been prepared in he conex of he pro-poor growh program sponsored by he World Bank s PREM-Povery group. I am graeful o Louise Cord, Robera Gai, Francisco Ferreira, Tamar Manuelyan-Ainc, Marin Ravallion, and an anonymous referee for helpful commens; and o Shaohua Chen and Diane Seele for providing daa. I would also like o hank he research deparmen a he Inernaional Moneary Fund for is hospialiy while pars of his paper were wrien. The opinions expressed here are he auhor s, and do no reflec hose of he World Bank or he IMF, heir Execuive Direcors, or he counries hey represen.
2 1. Inroducion The erm pro-poor growh has recenly become pervasive in discussions of developmen policy. Despie widespread use of he erm, here is much less consensus as o wha exacly pro-poor growh means, le alone wha is deerminans are. According o one view, growh is pro-poor if he accompanying change in income disribuion by iself reduces povery (Kakwani and Pernia (2000)). However, his definiion is raher resricive, as i implies ha, for example, China s very rapid growh and dramaic povery reducion during he 1980s and 1990s was no pro-poor because he poor gained relaively less han he non-poor. A broader and more inuiive definiion is ha growh is pro-poor if he povery measure of ineres falls. Ravallion and Chen (2003) propose his definiion and apply i o a paricular povery measure, he Was index. In his paper, I adop he broader definiion, and hen apply sandard povery decomposiion echniques o idenify hree poenial sources of pro-poor growh: (a) a high growh rae of average incomes; (b) a high sensiiviy of povery o growh in average incomes; and (c) a povery-reducing paern of growh in relaive incomes. I implemen his decomposiion for several povery measures, using household survey daa for a large sample of developing counries in he 1980s and he 1990s. I hen use variance decomposiions o summarize he relaive imporance of hese differen sources of pro-poor growh. Finally, I invesigae he correlaes of he sources of pro-poor growh in his panel of observaions on changes in povery. The main resuls of his paper are he following. Firs, regarding he relaive imporance of he hree poenial sources of pro-poor growh, I find ha mos of he variaion in changes in povery is due o growh in average incomes. In conras, changes in relaive incomes accoun for only 30 percen of he variance of changes in he headcoun measure of povery in he shor run, and only hree percen in long run. Growh in average incomes accouns for virually all of he remaining 70 percen of he variance in he shor run, and 97 percen of he variance in he long run, while crosscounry differences in he sensiiviy of povery o growh are very small. The share of he variance of changes in povery due o relaive income changes in somewha larger 1
3 for more boom-sensiive povery measures, reflecing he fac ha changes in hese measures place less weigh on growh in average incomes. Second, I find some evidence ha growh in average household survey incomes is correlaed wih several of he usual deerminans of growh from he empirical growh lieraure, including insiuional qualiy, openness o inernaional rade, and size of governmen. The evidence documened here for he cross-counry correlaes of growh in household survey incomes is no especially compelling, given various limiaions of he daase. However, I find almos no evidence ha povery-reducing paerns of growh in relaive incomes are significanly correlaed wih a se of explanaory variables ha he empirical growh lieraure has idenified as significan deerminans of growh in per capia GDP. The same is rue for a number of oher variables, ha while no generally significan for growh, have been suggesed in he lieraure as poenially reducing inequaliy. Taken ogeher, hese resuls underscore he imporance of growh in average incomes for povery reducion. This in urn suggess ha a policy package focusing on deerminans of growh in average incomes, such as he proecion of propery righs, sound macroeconomic policies, and openness o inernaional rade should be a he hear of pro-poor growh sraegies. Moreover, he absence of compelling cross-counry evidence ha hese facors are sysemaically correlaed wih he changes in income disribuion ha maer mos for povery reducion suggess ha here are no obvious radeoffs policies ha lead o growh in average incomes are unlikely o sysemaically resul in adverse effecs on povery hrough heir effecs on relaive incomes. This does no mean ha growh in average incomes is sufficien for povery reducion. Raher, he resuls presened here sugges ha cross-counry evidence is unlikely o be very informaive abou he policies and insiuions ha are likely o lead o povery-reducing paerns of growh in relaive incomes. This suggess ha more micro-level and casesudy research may be useful in shedding ligh on he deerminans of povery-reducing disribuional change. This paper is relaed o a growing empirical lieraure on growh, inequaliy, and povery. Mos immediaely, his paper builds on Dollar and Kraay (2002). In ha paper, we defined he poor as hose in he boom quinile of he income disribuion, and 2
4 empirically invesigaed he deerminans of growh in incomes of he poores quinile. In a large panel of counries, we found ha growh in incomes of he poor racked growh in average incomes roughly one-for-one. Since he growh rae of average incomes of he poor is he sum of he growh rae of average incomes and he growh rae of he firs quinile share, our paper showed ha neiher average incomes, nor a large se of oher conrol variables, were significanly correlaed wih changes in he firs quinile share. Tha paper conribued o a growing lieraure on he deerminans of inequaliy, including Li, Squire and Zhou (1998), Gallup, Radele and Warner (1998), Spilimbergo, Londono and Szekely (1999), Leamer, Maul, Rodriguez and Scho (1999), Easerly (1999), Barro (2000), Foser and Szekely (2001), and Lundberg and Squire (2003). This paper differs from Dollar and Kraay (2002), as well as much of he exising lieraure on deerminans of inequaliy, in wo respecs. Firs, insead of looking a relaive povery measures or inequaliy, here I focus on changes in absolue povery measures as he dependen variable. 1 As is well undersood, changes in absolue povery measures are complicaed non-linear funcions of underlying changes in average income and measures of income inequaliy. The second conribuion of his paper is o empirically consruc he exac measures of disribuional change ha maer for changes in various povery measures for a large sample of counries, raher han simply looking a common summary saisics of inequaliy such as he Gini coefficien or quinile shares. This means ha I can empirically sudy he conribuions of growh and disribuional change o changes in povery, wih less resricive assumpions abou he shape of he underlying income disribuion. 2 Despie hese differences, he main conclusions of his paper are similar o hose in Dollar and Kraay (2002). In paricular, boh papers find ha growh in average incomes maers a grea deal for reducions in boh relaive and absolue povery. Boh papers also find lile evidence ha common deerminans of growh, as well as a 1 A noable early excepion is Ravallion and Chen (1997), who esimae regressions of changes in absolue povery on changes in mean incomes using a panel of household surveys from developing counries. 2 For example, Lopez (2003) invesigaes he deerminans of growh and change in he Gini coefficien, and hen draws conclusions regarding he likely effecs on povery by assuming ha he disribuion of income is lognormal, so ha here is a one-o-one mapping beween he Gini coefficien and he Lorenz curve. In his paper I use a more flexible hree-parameer approximaion o he Lorenz curve, raher han he one-parameer approximaion implici in he lognormal assumpion. 3
5 number of oher variables, are robusly correlaed wih paerns of disribuional change ha maer for povery reducion. The res of his paper proceeds as follows. Secion 2 reviews sandard povery decomposiion echniques and uses hem o illusrae he channels hrough which growh and disribuional change maer for changes in a number of povery measures. Secion 3 describes he daase of changes in povery in a large sample of developing counries on which he empirical analysis is based. Secion 4 provides evidence on he relaive imporance of he sources of pro-poor growh, as well as evidence on some of he correlaes of hese sources. Secion 5 concludes. 4
6 2. Empirical Framework In his secion I use sandard echniques o decompose changes in povery ino hree componens: (a) growh in average incomes; (b) he sensiiviy of povery o growh in average incomes; and (c) changes relaive incomes. Le y (p) denoe he income of he p h percenile of he income disribuion a ime. This can be wrien as a funcion of average income, µ, and he Lorenz curve, L (p), i.e. y P denoe he following generic addiive povery measure: dl (p) (p) = µ. Le dp H (1) P = f(y (p)) dp 0 1 where H = y (z) denoes he fracion of he populaion below he povery line, z. This noaion capures a number of differen povery measures. For example, if θ z y (p) f( y (p), θ) = we have he Foser-Greer-Thorbecke class which includes he z headcoun (θ=0), he povery gap (θ=1), and he squared povery gap (θ=2). If f ( y ) (p) = ln y (p) z, we have he Was povery index. Nex, differeniae his povery measure wih respec o ime o obain he following expression for he proporionae change in povery: 3 dp 1 (2) = η (p) g (p) dp d P H 0 Equaion (2) expresses he proporional change in povery as he average across all perceniles of he income disribuion of he growh rae of each percenile muliplied by he sensiiviy of he povery measure o growh in ha percenile. In paricular, 3 Differeniaing under he inegral sign in Equaion (1) requires he applicaion of Leibniz s rule. Noe ha he erm involving he derivaive of he upper limi of inegraion is zero, since he povery measures are zero when evaluaed a he povery line. 5
7 df(y (p)) y (p) η ( p) is he elasiciy of he povery measure wih respec o he dy (p) P income of he p h percenile. This erm capures he effec on povery of a small change in incomes of individuals a he p h percenile of he income disribuion. This sensiiviy dy (p) 1 is muliplied by he growh rae of each percenile, g (p), which d y (p) Ravallion and Chen (2003) refer o as he growh incidence curve. The overall proporional change in povery hen consiss of he average across all perceniles of he produc of hese wo erms. In order o separae ou he effecs of growh in average incomes, re-wrie Equaion (2) as: H H dp µ 1 d 1 dµ (3) = η (p) dp + η (p) g (p) d P d µ 0 d 0 1 dp µ Equaion (3) idenifies he hree sources of pro-poor growh discussed above: (a) growh in average incomes; (b) he sensiiviy of povery o growh in average incomes; and (c) growh in relaive incomes. The firs erm in Equaion (3) capures he firs wo sources dµ 1 of pro-poor growh. I consiss of growh in average incomes,, muliplied by a d µ erm summarizing he sensiiviy of he povery measure o changes in average incomes, H η 0 ( p) dp. This is simply he average across all perceniles of he sensiiviy of povery o growh in each percenile of he income disribuion. The second erm in Equaion (3) capures he remaining source of pro-poor growh: changes in relaive incomes. This hird source of pro-poor growh is he average across all perceniles of he income disribuion of he produc of (a) he growh rae of income in he p h percenile relaive o average income growh, and (b) he sensiiviy of povery o growh in ha percenile. For example, if he povery measure of ineres is very sensiive o growh among he poores, and if he income of he poores grows faser han average incomes, hen povery will fall faser. 6
8 Equaion (3) is useful for hinking abou he various definiions and sources of pro-poor growh. The Kakwani and Pernia (2000) definiion of pro-poor growh saes ha growh is pro-poor if and only if he second erm in Equaion (3) is negaive, i.e. he paern of growh in relaive incomes is such ha he povery measure falls. A broader definiion of pro-poor growh suggesed by Ravallion and Chen (2003) is ha growh is pro-poor if he povery measure of ineres falls. According o his definiion, here are hree poenial sources of pro-poor growh: (a) rapid growh in average incomes; (b) a high sensiiviy of povery o growh in average incomes; and (c) a povery-reducing paern of growh in relaive incomes. In he empirical secion of his paper, I will use daa on income disribuions and average incomes for a large sample of developing counries o consruc hese hree sources of pro-poor growh, documen heir relaive imporance, and invesigae heir deerminans. Before doing so, however, i is useful o examine he key ingrediens in Equaion (3) in more deail: he paern of growh in relaive incomes, dµ g (p) d povery o growh in each percenile, η (p). 1, and he funcion summarizing he sensiiviy of µ Figure 1 graphs wo examples of he paern of growh in relaive incomes, for China over he period , and for Indonesia over he period In China, according o he household survey average incomes grew a 14 percen per year, and he dollar-a-day headcoun measure of povery fell from 51 percen o 33 percen of he populaion. However, here was also a sharp increase in inequaliy during his period, wih he Gini coefficien rising from 34 o 40. The paern of relaive income growh raes shown in he relaive growh incidence curve highlighs his paern of increased inequaliy. Growh in he poores 80 perceniles of he populaion was below average, while only he riches 20 percen of he populaion saw above-average growh. In Indonesia, survey mean income fell dramaically beween 1996 and 1999 a nearly 9 percen per year during he Eas Asian financial crisis. Ye during his period, he paern of growh in relaive incomes was povery-reducing. Inequaliy as measured by he Gini coefficien fell from 36.5 o The relaive growh incidence curve is downward sloping, indicaing ha incomes of he richer perceniles of he income disribuion fell faser han incomes of poorer perceniles. In fac, below-average growh was recorded only for he riches 20 percen of he populaion. Despie his pro-poor paern of relaive 7
9 income growh, he headcoun measure of povery increased from 8 percen o 13 percen of he populaion, driven by he large negaive growh effec. 4 Consider nex he sensiiviy of povery o growh in differen perceniles of he income disribuion. In he case of he Foser-Greer-Thorbecke class, θ 1 θ y (p) y (p) 1 η (p) = 1, while for he Was index, η ( p) =. Noe ha P z z P hese sensiivies in general depend no only on he povery measure of ineres, bu also on he enire disribuion of income as summarized by y (p). Figure 2 graphs hese sensiiviies, using he acual disribuion of income in China in 1990 as an example, o show how differen povery measures are sensiive o growh in differen perceniles of he income disribuion. In he case of he headcoun, his sensiiviy is zero everywhere excep jus below he povery line where i spikes down o minus infiniy. This is because he headcoun simply adds up he number of people below he povery line small increases in he incomes of inframarginal poor people ha do no bring hem above he povery line will no reduce he headcoun. The same is rue for increases in incomes of hose above he povery line, including he near-poor jus above he povery line. The case of he headcoun already illusraes he broader poin of Figure 2: he exen o which a given paern of growh is pro-poor depends crucially on he povery measure of ineres. In paricular, if he objecive of pro-poor growh is o reduce he headcoun measure of povery, hen a pro-poor growh sraegy should focus exclusively on raising he incomes of hose jus a he povery line, and should ignore everyone else. This srong -- and well-undersood o be absurd -- conclusion is driven by he choice of he headcoun as he povery measure of ineres. Consider nex he povery gap and he squared povery gap. The povery gap is mos sensiive o growh in incomes of hose a he povery line, bu is also sensiive o growh in incomes of everyone below he povery line. The inuiion for his is he following: he povery gap 4 I is imporan o noe ha he growh incidence curves here adjus only for average inflaion. In he case of Indonesia food price inflaion during he crisis was much higher han non-food price inflaion (see Suryahadi e. al. (2003) for deails). To he exen ha food represens a larger share of he consumpion baske of he poor, he paern of growh in real incomes was less propoor han depiced in Figure 1. 8
10 reflecs a social welfare funcion which is indifferen o he disribuion of income among poor people. In his case a given rae of average growh resuls in a larger absolue increase in income for a person near he povery line, and so he povery measure is mos sensiive o hose neares he povery line, bu is non-zero for all poor people. The squared povery gap is also sensiive o growh in he incomes of all hose below he povery line, bu he sensiiviy is now U-shaped. Growh in incomes of he riches and poores of hose below he povery line maers leas, and he squared povery gap is mos sensiive o growh in incomes of poor people somewhere in beween hese wo exremes. The inuiion for his again depends on he underlying social welfare funcion, which now values absolue ransfers from richer o poorer poor people. This however is offse by he fac ha a given average growh rae resuls in a larger absolue increase in income for richer poor people. This is why he sensiiviy of he povery measure o growh is a non-monoonic funcion of he income percenile. The Was index has he propery ha i is equally sensiive o growh in all perceniles below he povery line. This is why Ravallion and Chen (2003) argue ha a good measure of pro-poor growh is he average (across all perceniles) growh rae of hose below he povery line, i.e. he average growh rae of incomes of he poor. In his paper I go furher and decompose he average growh rae of incomes of he poor ino growh in average incomes and he average growh rae of he poor relaive o growh in average incomes. This allows me o disinguish beween he effecs of growh in average incomes and growh in relaive incomes on he Was measure, and all he oher measures considered here. This disincion is no rivial, as we will see in he empirical secion of he paper ha, across counries, growh in average incomes accouns for a much greaer share of he variaion in changes in povery han do changes in relaive incomes. Finally consider he average across all perceniles of he sensiiviy of povery o growh in he incomes of percenile p, η (p). Recall from Equaion (3) ha his average sensiiviy measures he effec of growh in average incomes on he povery measure. High values of his average sensiiviy of povery o growh in average incomes are one of he hree poenial sources of pro-poor growh. For he Foser-Greer-Thorbecke class of povery measures, his average sensiiviy can be expressed in erms of he povery 9
11 measure iself when θ is no equal o zero, H P ( θ 1) η =θ (p) dp 1, where P (θ) P ( θ) 0 denoes he FGT measure wih parameer θ. 5 In he case where θ is zero, he sensiiviy of he headcoun o growh in average incomes is: H 1 L '(H) η (p) dp = which can be expressed as he slope of he densiy of P ( θ) µ L ''(H) 0 income a he povery line. For he Was measure, he average elasiciy is simply minus one imes he raio of he headcoun index o he Was index. While hese resuls are useful for analyically characerizing he sensiiviy of he differen povery measures o growh in average incomes, we will see shorly ha cross-counry differences in he sensiiviy of povery o growh in average incomes are no empirically very imporan, in he sense ha hey explain lile of he cross-counry variaion in he firs erm in Equaion (3). 5 This resul can be found in Kakwani (1993). 10
12 3. Daa In he res of his paper I use he analyic framework of he previous secion o decompose observed changes in povery ino he hree erms discussed above: (a) growh in average incomes; (b) he sensiiviy of povery o growh in average incomes; and (c) changes in relaive incomes. Afer consrucing hese hree erms for a large sample of developing counries, I use hem o idenify he relaive imporance of, and facors correlaed wih, hese sources of pro-poor growh. I use household survey daa on average incomes and en poins on he Lorenz curve for a large number of surveys, as compiled by Marin Ravallion and Shaohua Chen a he World Bank. Their daa comes direcly from primary sources, and is available a hp://www.worldbank.org/research/povmonior. 6 Depending on he counry, he surveys measure eiher he disribuion of income or he disribuion of consumpion. Average income or consumpion is measured in 1993 dollars and is adjused for crosscounry differences in purchasing power pariy. Since I am ineresed in changes in povery over ime, I ake only counries wih a leas wo household surveys. This resuls in a oal of 285 surveys covering 80 developing counries. Mos of he survey daes are in he 1990s, wih some counries exending back o he 1980s. I use he World Bank s dollar-a-day povery line which in 1993 dollars is $1.08 per day, or $393 per year. Using hese surveys, I consruc wo daases of spells of changes in povery. In he firs daase, I consider all possible spells for each counry, discarding only hose few cases where he survey changes from an income o an expendiure survey or vice versa wihin a counry. This resuls in 185 spells of povery changes. The lengh of hese spells is quie shor, averaging 3.4 years and ranging from one o 13 years. In order o be able o look a changes over longer horizons, I also consruc a daase consising of one spell per counry, where he iniial and final years are chosen so as o maximize he lengh of he spell given available daa. This resuls in a se of 77 spells, wih an average lengh of 8 years, and ranging from wo o 19 years. I eliminae all spells where he headcoun measure of povery is negligible in eiher he iniial or final period, i.e. below wo percen. I also discard a small proporion of spells for which he average 6 I am graeful o Shaohua Chen for kindly providing key daa from all of he household surveys, including some ha was no a he ime available on he povery monioring websie. 11
13 annual growh rae of mean income exceeds 15 percen in absolue value, or for which he average annual growh rae of he headcoun exceeds 30 percen in absolue value. 7 Finally, for he daase of long spells, I discard hose counries for which he longes possible spell is shorer han five years. This reduces he firs daase o 110 spells covering 49 counries wih an average lengh of 3.5 years, and he second daase o 41 spells wih an average lengh of 9.6 years. These spells are lised in Appendix 1. In order o consruc he differen povery measures and heir decomposiions discussed in he previous secion, I need he full Lorenz curve and no jus he 10 poins provided in he Ravallion-Chen daa. To obain his, I assume ha he Lorenz curve has he following funcional form: α (4) L(p) = p ( 1 (1 p) ), α 0, 0 < β 1, γ 1 β γ This paricular parameerizaion is a member of a family of ordered Lorenz curves proposed by Sarabia, Casillo, and Sloje (1999). In Appendix 2, I discuss in more deail he qualiy of his parameric approximaion o he Lorenz curve, using record-level daa from Ghana as an example. The appendix shows ha his approximaion o he Lorenz curve is quie good, bu ha he associaed quanile funcion ends o undersae incomes of he poores. This means ha povery measures based on his approximaion are likely o be biased upwards, and more so for more boom-sensiive povery measures. I also show ha hese biases will lead o an underesimaion of he sensiiviy of povery o growh in average incomes. I esimae he hree parameers of he Lorenz curve for each survey using an algorihm suggesed by he same auhors. This involves selecing all possible combinaions of hree poins on he Lorenz curve, and hen for each combinaion finding values of α, β, and γ such ha he Lorenz curve passes hrough hese hree poins. The final esimaes of α, β, and γ are hen found by averaging across all he resuling esimaes of hese parameers, discarding hose for which he parameer resricions 7 This cuoffs roughly correspond o he 5 h and 95 h perceniles of he disribuion of growh raes of mean income and he headcoun. In a leas some of hese cases growh raes of variables are sufficienly exreme as o be implausible, and likely reflec problems of comparabiliy in surveys over ime. Appendix 1 liss he discarded observaions and summarizes some of he key resuls including hese exreme observaions. 12
14 indicaed in Equaion (4) ha are required for he Lorenz curve o have posiive firs and second derivaives do no hold. I hen obain he quanile funcion by analyically differeniaing he Lorenz curve and muliplying by average income. Using his, I can consruc η (p) for each povery measure of ineres, as well as he growh incidence y (p) curve over he observed discree inerval, g (p) = 1. y (p) 1 13
15 4. Resuls I begin by consrucing four povery measures of ineres (he headcoun, he povery gap, he squared povery gap, he Was index) for he iniial and final years of each spell. I hen compue he average annual growh raes of each of hese measures over each spell. Table 1 repors he simple correlaions of he levels and average annual growh raes in hese povery measures wih he corresponding log-levels and growh raes of survey mean income. These simple correlaions are all negaive, and are large in absolue value, especially hose in levels and hose for he long spells. Figure 3 graphs he proporional change in he headcoun agains he growh rae of average incomes, using he sample of long spells. There is a srong and highly significan negaive relaionship beween changes in povery and change in average incomes. Table 1 and Figure 3 confirm he widely-undersood empirical regulariy ha povery on average falls as average incomes increase. In he res of his secion I go beyond his basic observaion o documen he relaive imporance of he differen sources of pro-poor growh discussed above, and heir correlaes. The Relaive Imporance of Sources of Pro-Poor Growh I firs decompose he change in povery in each spell ino a growh componen and a disribuion componen using he decomposiion suggesed by Da and Ravallion (1992), which is he discree analog of he infiniesmal decomposiion in Equaion (3). Le (, ) P µ denoe a povery measure based on mean income a ime, µ, and he L Lorenz curve a ime, L. The proporional change in he povery measure over he discree inerval beween ime and -1 is: (5) P ( µ,l ) P( µ 1,L 1 ) P( µ,l ) 1 1 P = ( µ,l 1 ) P( µ 1,L 1 ) P( µ,l ) 1 1 P + ( µ 1,L ) P( µ 1,L 1 ) + ε P( µ,l ) 1 1 The firs erm on he righ-had side is he growh componen of he change in povery, and is consruced as he proporional difference beween he iniial povery measure and a hypoheical povery measure compued using he second period mean bu he firs period Lorenz curve. The second erm is he disribuion componen which is compued as he proporional difference beween he iniial povery measure and a 14
16 hypoheical povery measure consruced using he firs period mean bu he second period Lorenz curve. These wo componens are he discree-ime analogs of he wo erms in Equaion (3). Unlike Equaion (3), however, here is also a residual erm because he decomposiion is done over a non-infiniesmal inerval. Empirically however hese residuals will urn ou o be unimporan on average. I measure he proporional changes on he lef- and righ-hand side of Equaion (5) as log differences and normalize by he lengh of he inerval o obain average annual percen changes in povery and he growh and disribuion componens for each spell. I also divide he firs erm in Equaion (5) by growh in average incomes o obain he sensiiviy of povery o growh in average incomes. Tables 2 and 3 repor he resuls of applying his decomposiion o he wo daases of spells. Throughou hese wo ables, I use he following variance decomposiion o summarize he relaive imporance of he various sources of pro-poor growh. For wo correlaed random variables X and Y, I define he share of he variance of X+Y due o variaion in X as VAR(X) + COV(X, Y). 8 The op panel of VAR(X) + VAR(Y) + 2 COV(X, Y) each able documens he imporance of he residual relaive o he sum of he growh and disribuion componens of he change in povery. The firs column shows he variance of he sum of he growh and disribuion componens, he second column he variance of he residual, and he hird he covariance beween he wo. The final column repors he share of he variance of changes in povery due o he growh and disribuion componens, which is virually one for all povery measures. This simply reflecs he fac ha he variance of he residual erm is iny relaive o he variance in measured changes in povery. This can also be verified visually from he op panel of Figure 4, which graphs he change in he headcoun measure of povery on he horizonal axis, and he sum of he growh and disribuion componens on he verical axis, using he daase of long spells. The slope of he OLS regression line is he share of he variance in povery changes due o he growh and disribuion componens, and one minus he slope is he share due o he residual erm. I is clear from his graph ha changes in povery are 8 When X and Y are normally disribued, his variance decomposiion has a very naural inerpreaion. I measures how much he condiional expecaion of X increases for each uni ha he sum (X+Y) is above is mean value. See Klenow and Rodriguez (1997) for deails. 15
17 largely accouned for by he sum of he growh and disribuion componens, wih very lile of he variaion due o he residual. The middle panels of Tables 2 and 3 repor he same variance decomposiion, bu now o assess he imporance of he growh componen relaive o he disribuion componen of changes in povery. For he sample of all spells, beween 43 and 70 percen of he variaion in changes in povery is due o he growh componen, wih he remainder due o changes in relaive incomes. For he long spells, beween 69 and 97 percen of he variaion in changes in povery is aribuable o he growh componen, depending on he povery measure of ineres. In boh ables, he growh componen is relaively less imporan for boom-sensiive povery measures such as he povery gap and he squared povery gap. The middle panel in Figure 4 graphically summarizes his second decomposiion for he long spells sample, ploing he growh componen of changes in he headcoun on he verical axis, and he sum of he growh and disribuion componens on he horizonal axis. Again, he slope of he OLS regression line can be inerpreed as he share of he variaion on he horizonal axis due o he growh componen. Visually inspecing his graph, i is clear ha if he headcoun declines subsanially, i is mosly because he growh componen of povery reducion is large. The boom panels of Tables 2 and 3 furher disenangle he growh componen ino growh in average incomes, and he sensiiviy of povery o growh in average incomes, i.e. hey separae he firs erm in Equaion (3) ino is wo componens. Since he variance decomposiion used here applies o sums of random variables, I ake he logarihm of he absolue value of he growh componen, which hen becomes he sum of he logarihm of he absolue value of growh, and he logarihm of he absolue value of he average sensiiviy of povery o growh, and apply he decomposiion o his sum. Tables 2 and 3 show ha around 90 percen of he variaion in he growh componen of changes in povery is due o differences in average income growh, and very lile is due o differences in he sensiiviy of povery o average income growh. The boom panel of Figure 4 illusraes his, bu wihou he log ransform required o do he variance decomposiion. On he horizonal axis I graph he growh componen of he change in povery, while on he verical axis I graph growh in average incomes. While he slope of his regression canno be inerpreed as a variance share, i neverheless is very clear ha cross-counry differences in he growh componen of changes in povery are 16
18 overwhelmingly accouned for by cross-counry differences in growh iself. Pu differenly, i is clear from his graph ha if he growh componen of povery reducion is large, i is mos likely ha growh iself was large, raher han ha he sensiiviy of povery o growh was large. 9 Two sriking feaures of Tables 2 and 3 meri furher discussion: (a) he share of he variaion in povery measures due o growh declines as he povery measures become more boom-sensiive, i.e. when we move from he headcoun o he povery gap o he squared povery gap; and (b) he share of he variance due o growh is smaller over he shor horizons represened in he daase of all spells, and is larger in he daase of long spells. Consider firs he observaion ha he variaion in changes in povery due o growh declines as he povery measures become more boom-sensiive. This finding should no be inerpreed as evidence ha he poores perceniles of he income disribuion are more likely o experience slower-han-average growh. Raher, i primarily reflecs he fac ha more boom-sensiive povery measures place relaively less weigh on changes in average incomes han hey do on changes in relaive incomes. 10 Recall ha he sensiiviy of povery o growh in average incomes is H P ( θ 1) η =θ (p) dp 1 P ( θ) 0 for he FGT family of povery measures. Differeniaing P ( ) his sensiiviy wih respec o θ and using he fac ha θ P < ( θ) 0 and < 0, i is 2 θ θ sraighforward o see ha he sensiiviy of povery o growh in average incomes is sricly declining (in absolue value) as he povery measure becomes more boomsensiive, i.e. as θ increases. This means ha when relaive incomes do no change, he proporional change in povery associaed wih a given average growh rae will be 2 9 A firs glance his resul seems inconsisen wih Ravallion (1997), who documens ha he sensiiviy of povery o growh varies significanly wih iniial inequaliy. However, using eiher sample of spells I can replicae he resul ha he ineracion of growh wih he iniial Gini coefficien is significanly correlaed wih he change in headcoun measures of povery. Alhough here are cross-counry differences in he sensiiviy of povery o growh which are significanly correlaed wih iniial inequaliy, in he daa hese differences are dominaed by he much larger cross-counry differences in growh iself, and his is wha he variance decomposiions show. 10 In Appendix 2 I also show ha he approximaion errors associaed wih he parameerizaion of he Lorenz curve reduce he sensiiviy of povery o growh in average incomes for more boomsensiive povery measures. 17
19 smaller he more boom-sensiive is he povery measure. In oher words, even for a purely disribuion-neural growh process, growh will appear o be less pro-poor (in he sense ha he proporionae change in povery is smaller) he more boom-sensiive is he povery measure. When relaive incomes also change, i is no longer possible o sign he derivaive of he change in povery wih respec o θ for an arbirary shif in he Lorenz curve. Empirically, however, in he majoriy of spells in his daase, proporional changes in povery are larger in absolue value he more boom-sensiive are he povery measures. This is rue even hough he growh componen of changes in povery is unambiguously smaller in absolue value in all spells, implying ha, on average, he disribuion componen of changes in povery becomes larger in absolue value he more boom-sensiive are he povery measures. This in urn accouns for a smaller share of he variance of changes in povery due o growh for more boom-sensiive povery measures. 11 I is also possible o documen direcly ha he incomes of he very poores on average do no grow more slowly han average incomes, using he esimaed growh incidence curves for each spell. In he daase of long spells, I calculae he average annual growh rae of incomes relaive o he survey mean, a he perceniles corresponding o 100 percen, 50 percen, and 25 percen of he iniial-period headcoun, using only he 22 spells for which he iniial headcoun is more han 10 percen. The average across spells of hese growh raes are 1.2 percen, -1.4 percen, and 1.5 percen respecively, bu wih very large sandard deviaions of 3.6 percen, 5.0 percen, and 6.6 percen respecively. Based on his I canno rejec he null hypohesis ha he growh rae of incomes a and below he povery line do no differ significanly from growh in average incomes. 11 For he paricular case of equiproporionae shifs in he Lorenz curve, Kakwani (1993) shows ha he elasiciy of povery wih respec o he Gini coefficien is µ P ( θ 1) θ 1+ 1 I is z P ( θ) sraighforward o verify by simple differeniaion ha his elasiciy is sricly increasing in θ when he povery line is below he mean, i.e. z<µ.. Thus for his special case we can unambiguously show ha he more boom-sensiive he povery measure, he growh componen of changes in povery will be smaller and he disribuion componen of changes in povery will be larger. 18
20 The second sriking feaure of Tables 3 and 4 is ha he share of he variance of changes in povery due o growh is larger in he sample of long spells. In order o undersand his finding i is useful o examine in more deail he sources of variaion in he growh and disribuion componens of changes in povery. In he long spells, he sandard deviaion of he growh componen of he headcoun is 0.88 percen, which reflecs purely cross-counry variaion in he long-run average growh componen of changes in povery. In he sample of all spells, he sandard deviaion of he growh componen rises o 1.04 percen, reflecing he addiion of he wihin-counry variaion in he growh componen. This fairly modes increase indicaes ha mos of he variaion in he growh componen of changes in povery in he sample of all spells is due o crosscounry variaion, and relaively lile reflecs wihin-counry variaion. Since we have already seen ha cross-counry differences in he sensiiviy of povery o growh are small, i is also he case in his daase ha average income growh iself varies relaively more across counries han i does wihin counries over ime. The disribuion componen of changes in povery is a weighed average of he growh raes of each percenile of he income disribuion relaive o average growh. In boh he long spells and he full sample of all spells, he relaive growh raes of each percenile are on average near zero. However, in he sample of all spells, he relaive growh raes of each percenile vary much more across spells han hey do in he sample of long spells. This is shown in Figure 5, which repors he average (across spells) of he growh rae of percenile p relaive o average growh, as well as he sandard deviaion (across spells) of his relaive growh rae. In boh samples he relaive growh raes of all perceniles are close o zero on average across spells, consisen wih he well-documened fac ha growh ends o be disribuion-neural on average. However, he variaion around his average is nearly wice as large in he sample of all spells as i is in he sample of long spells, reflecing subsanial addiional wihin-counry variaion over ime in relaive income growh raes. Puing ogeher hese observaions, we can now accoun for he difference in he relaive imporance of he growh and disribuion componens of changes in povery in he sample of long spells and he sample of all spells. In he long spells sample, relaive income changes over long periods are fairly closely clusered around zero for all perceniles of he income disribuion. The weighed average of hese relaive growh 19
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This time of year is always exciting for me, as it's the start of baseball season once again!
I'm a huge baseball fan, having played competitively as a kid and enjoyed it on radio and TV most of my life. So it's always fun when the season rolls around to start cheering again for my home-state team, the Detroit Tigers (currently one of the top teams in baseball, though it's very early in the season).
With diabetes obviously also being a big part of my life, it's always been fascinating for me when the two collide. Two seasons ago, I had the privilege of talking with MLB (major league baseball) pitcher Brandon Morrow, who was diagnosed in 2003 at age 18. And lately, it seems there's been a surge of interest in baseball players with diabetes, including:
- Sam Fuld: who now plays center field for the Oakland A's and was diagnosed as a kid with T1D. He hosts a sports camp for children in his former stomping grounds in Tampa Bay, FL, mentoring young athletes with type 1.
- Cory Vaughn: an outfielder for the New York Mets, who was diagnosed at age 11; he was recently featured on the Sanofi blog, The DX.
- Baseball legend Lou Brock: a T2 who's been on the speaking circuit for Novo recently, talking about his days playing for the St. Louis Cardinals and Chicago Cubs. He was featured in an interview on Type 2 Nation in early April. Lou was diagnosed in the 90s, but also recalls the days decades ago when he played ball with fellow Hall of Famer Ron Santos, a type 1 who didn't publicly share anything about his diabetes in those days.
- Dmitri Young: a former pro outfielder who played for St. Louis, Detroit (!), Cincinatti, and Washington before leaving baseball. He's featured in this past January's edition of Diabetes Forecast, talking about his type 2 diagnosis in 2006 and how he's recently taken a more proactive approach to managing his health.
But for me one, of the most interesting stories involves a college athlete who could make it to the pros in the next months, depending on how the MLB Draft plays out in early June.
His name is Adam Boghosian, from Cary, North Carolina.
Diagnosed in 2008 at the age of 16, Adam has been playing baseball since he was a kid and is now a hot prospect for the major leagues. He attends the University of North Greenville in South Carolina, where he's a senior working to catch the attention of pros -- especially with his 95 mph fastball! On top of that, he's raised more than $30,000 for the JDRF in the past several years by selling baseball attire online, which he says could morph into a real business at some point... if his pro baseball hopes don't materialize.
We connected with Adam recently for this Q&A about his love of baseball and life with diabetes and how they intersect.
DM) Tell us about your diagnosis?
AB) Every diagnosis story has generally the same key points. I was very thirsty, I frequently had to use the restroom, and I felt tired and weak. My symptoms became so severe that my mother and one of my friends decided to search the web for answers. Type 1 diabetes was the first result to our search. I read through the symptoms, giving each one a mental check, and I began feeling worried and confused. I have been an athlete all my life, and I've always associated diabetes with overweight older people, so I kept telling myself there must be a mistake. The last symptom on the list was weight loss, so I jumped on the scale. To my surprise, I had lost 30 pounds without even realizing it. I was 16 years old, 6'2", and 140 pounds just starting my junior year in high school.
Was it traumatic for you?
Yes. When my blood test came back confirming my diagnosis of type 1, my world was turned upside-down. I found myself thinking about my life, my health, and the great inconvenience of the incurable disease -- that became my reality rather than thinking about hanging out with friends, playing sports, and having fun like most college students. I stayed at the University of North Carolina Pediatric Hospital for a week learning to manage my new disease.
The one high note during my tragic September of 2008 was my last meal as a non-diabetic. Many type 1s remember the last meal they had before being diagnosed with diabetes, and mine was great! I chowed down on numerous chocolate chip pancakes smothered in syrup, fresh fruit, and juice (more sugar than I can even calculate).
Where are you at now, school-wise?
I am currently at North Greenville University pursuing my MBA. I'm also a member of the baseball team at North Greenville, which is the reason I ended up attending the small school in Tigerville, South Carolina. The recently hired head coach, Landon Powell, is the son of my American Legion coach when I was in high school. He called me as soon as he was hired and told me to come play for him for my final year of baseball eligibility. I had just graduated from the University of North Carolina at Greensboro and still have another year of baseball to play since I was redshirted (granted an extension) my freshman year due to Tommy John Surgery (tendon replacement in the elbow).
How long have you been playing baseball?
All of my life except for a five-year period during middle school where I decided to play football instead. After being hit in the head with a bat in second grade and requiring stitches to close the large hole in my forehead, I wanted to experience some new sports for a while. Eventually I found that baseball was my true passion and began playing competitively again. It became clear that was a good decision after throwing a perfect game in the second game I played after just returning to baseball in seventh grade. Ever since, I've played year-round.
Baseball has been a huge part of my life. I have met numerous influential people, made tons of lifelong friends, and have some of the best memories I will think of fondly of for the rest of my life. With baseball meaning so much to me and with my talent for the game, it makes hanging up the cleats difficult to think about. Baseball has given me so much and taught me even more, so I plan to play for as long as I can.
You must be excited about the draft coming up in June. But what if things don't work out?
If I am able to be drafted, my plans will be to pursue professional baseball, and ride it out as long as I can, hopefully making it to the big leagues! If professional baseball is not in the cards, I hope to work with JDRF. I have volunteered with them since 2008 and have met many great people along the way. I would love to take all of the fundraising efforts I have done through the years and make it a career rather than a hobby.
With a 95 mph fastball, many think you've got a good chance at being drafted...
Unfortunately it's not up to me, but my plan is to continue working hard and improving each day to better my chances of playing professionally and continuing my baseball career.
How do you manage diabetes while you're out there playing?
The burden of diabetes does not go away when on a baseball field. My diabetes management is ingrained into my daily routine. I have a continuous glucose monitor that helps out with blood sugar control. I like to have a small snack before practice to avoid lows during long days on the field. My goal is to keep my blood sugar between 120 - 140 while playing, although I like being slightly elevated to keep my hands steady and my legs strong when throwing. Everyone is extremely supportive and keeping my diabetes managed is truly a team effort.
What diabetes technology do you use?
I always use my continuous glucose monitor. I do not use a pump.
And do you do anything special for your diabetes during games?
I am the closer on my team, which means I pitch the last inning of games. I like a snack around the 2nd inning, I head to the bullpen around the 6th inning, to ensure perfect blood sugar by the 8th inning, and drink about 8 ounces of Gatorade right before pitching the 9th inning. It seems to be a winning recipe as my performance has shown.
Are there any athletes with diabetes you look up to, for inspiration along the lines of "You Can Do This"?
I've always been a very independent diabetic in the sense that I like to manage it relatively alone. I do not look up to any other diabetic athlete since I don't believe it's a big deal. Diabetes should never hold anyone back, so I just look at it as something I have to do. I don't need inspiration to pursue my goals. Diabetes is not holding me back in any way.
What exactly is Team BOGO and how did it get started?
Bogo is my nickname. I'm convinced that a number of my friends don't even know my real name. Bogo is short for my last name Boghosian (Bo-go-shin), and the nickname has really stuck.
Team Bogo was started almost immediately after I was diagnosed with type 1 diabetes on September 12, 2008. There was an upcoming JDRF walk in October in Raleigh, NC, that I wanted to create a team for, to be as proactive about my new disease as possible. Team Bogo consisted of about 20 people and produced about $2,000 for the JDRF that first walk, through Team Bogo T-shirt sales and donations from friends and family.
Today, Team Bogo is a fundraising team of hundreds of diabetes-hating individuals, and we provide funds for the JDRF to ultimately find a cure. Team Bogo has now also become a brand of sorts that people get really passionate about. The nature of my Team Bogo apparel caters to young adults and college-goers. The slogans on the shirts can be slightly inappropriate at times, but it's all in good fun and makes for a good laugh while striving to cure a serious disease.
What kind of inappropriate?
Our shirts have highlighted slogans such as: "Kicking Diabetes in the Pancre-ass," "Get Insulin Pumped!," "Helping to Eliminate Pricks Since 2008," "Diabadass," and many more. Team Bogo shirts and accessories such as wristbands, shorts, pullovers, hats, stickers, koozies, and other accessories have been spread all over thanks to dedicated friends selling my brand at their own colleges and to friends.
Sounds like the team's been incredibly successful...
Team Bogo has raised over $30,000 through merchandise sales, donations, and events. Team Bogo would be nothing without the continued support of friends and family, and I cannot thank those dedicated people enough!
Are you starting a business, or is this simply a fundraising project for JDRF?
As it stands, Team Bogo is a fundraising project for JDRF, although with its exponential growth, it very well could become something much bigger. I plan to continue working on and improving Team Bogo, and we'll see where it can go.
Any thoughts on establishing a baseball or sports camp for kids with diabetes, as may D-athletes have done?
That is something I want to do. As a student-athlete who has gone through college and played a sport day-in and day-out, I have a lot of insight I want to share with the younger generation and their parents. I know my mom was very worried about me going off to college and being more independent with my life, including my diabetes. I have provided a great deal of help and information to young people diabetes who've connected me with. I would love to do that for more people out there!
Thanks for everything you do, Adam, and whether you want to be or not, you're definitely an inspiration for so many! Good luck with the upcoming MLB draft -- we'll be cheering for you!

subset: commoncrawl


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|[jira] [Commented] (OPENMEETINGS-93) Create Openmeetings plug-in
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[ https://issues.apache.org/jira/browse/OPENMEETINGS-93?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13558616#comment-13558616 ] Terence Mill commented on OPENMEETINGS-93: ------------------------------------------ Hi Artyom, i juts sav you uploaded a zip. Can u give some backgorund about status and roadmap. Please opensource ur code via github, thetre you will get free community support for bug reporting, code contribution and testing. Furthermore publish ur works as registering a new redmine plkugin on redmine.org. Click this urls and first register yourself. http://www.redmine.org/plugins/new Tx for ur job. > Create Openmeetings plug-in > --------------------------- > > Key: OPENMEETINGS-93 > URL: https://issues.apache.org/jira/browse/OPENMEETINGS-93 > Project: Openmeetings > Issue Type: Improvement > Reporter: Alexei Fedotov > Labels: gsoc2012 > Attachments: redmine_openmeetings.zip > > Original Estimate: 2,016h > Remaining Estimate: 2,016h > > There is a number of different systems which would benefit from Openmeetings integration, including Zimbra, Typo 3, Redmine and Trac, and different popular SaaS systems. > The participant is to create the plug-in integrating Openmeetings re-using authorization system. Then other requirements can be completed, please take a look on Joomla plug-in for inspiration. > http://code.google.com/p/openmeetings/wiki/JoomlaIntegration -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira
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Bear trap
Creative Director: Carsten Kaag
Art Director: William Stahl
Copywriter: Anne-Marie Mygind
Producers: Mette Stuhr & Rasmus Sanko
Director: William Stahl
tanning can kill you so let's show a tanning bed LITERALLY killing you.... WTF?
I agree with you. It will work better short.
"Don't ever believe that you are better than anybody and don't ever believe that anybody is better than you." A quote from my mother.
This is phenomenal! Scared the crap out of me. Still laughing.
Hurray! Scare-tactics legitimized by an ends-justifies-the-means mindset!
Lacking positive approach... and this ad also falls in the wdf category ? Looked like the ad for a tanning machine which wouldn't fall...
I don't consider this a creative ad. It's just a nice model and a shocking end.
My question is, if I got the message, and I'm going to remember it for a long time. Is it a bad ad?
Terrible ad--repulsive tactic--no sale-- remember the basics—shock therapy only works on those needing a lobotomy--target audiences will be insulted not enlightened—after all look at what you just told them about what you think of them—convince them don't convict them! --Don't indict them-- Inspire them!
Sweeet. I certainly get the point. Total guy ad though..I had no idea guys were big on tanning.
Sweeet. I certainly get the point. Total guy ad though..I had no idea guys were big on tanning.
wayyyyyyyyyyy tooooooooooooo long! I see the ones who love this are lovin it for an entirely different reason :) and now I'm terrified of tanning beds.
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DISCLAIMER: No copyright infringement intended.
The Angelic Version of Small Talk
by wave obscura
Cas leaves Dean alone for what seems like a long time, lying face down on the Impala's hood, not really sleeping, not really awake, just kind of floating on sea of booze and ache. The angel grips the liquor bottle and holds it for just a moment and then tugs it from Dean's hand. With nothing to hold on to, Dean's fingers curl flaccidly into a fist.
"I've rendered him unconscious," Cas says, "You can come inside. His screaming won't cause you pain."
The truth makes Dean twitch. He opens his mouth to deny having feelings, which is just another auto-twitch, really, and then closes his mouth again because there's no point in saving face, not when he's already snotty and red.
"I'm good," Dean says, and through the snot only half his voice emerges.
"You're upset," Cas states. "While I understand your desire for solitude, the human body cannot withstand these temperatures, especially not while intoxicated."
Dean mumbles something not even he understands, and drags himself off the hood of the car. Now that the haze is starting to crisp up again, he takes a moment to wonder what the hell he was thinking, coming out here to cry to God, angels, Mommy, Daddy, whatever.
As he stumbles inside, Cas rests a hand on the small of his back-- an awkward, touchy-feely gesture that he probably learned from Sam.
They let themselves in, just like they let themselves in earlier, using the spare key Dean keeps in his wallet. Bobby had long been passed out drunk when they got there, had tipped himself from the wheelchair to the sofa in the study and was lying face down, snoring.
"You should rest," Cas says, as Dean is heading to the basement door. "I can make sure he doesn't harm himself."
Rest would be nice. But even after all of it--Ruby, the demon blood, everything--it's still Dean's job and no one else's.
Cas follows him down the steps. He wants to turn around, tell the angel to go the fuck away, leave he and his brother to wallow in their own mess like he used to, like when he used to disappear and reappear when they needed him the least. But the truth is, he doesn't want Cas to leave. If he's left alone with Sam in the panic room, he doesn't know what he'll do, what he'll say.
He'll probably just start bawling again, like the irreparably broken little baby that he is.
He looks into the little peep door to make sure Sam is still passed out. He's spread-eagle on the concrete floor like someone or something discarded him there, quiet except little whimpering noises with each exhale.
"If he's bloodied or has urinated on himself," Cas says, "I can cleanse him using very little of my power."
It's intended as a reassurance, a show of support-- something Cas obviously hasn't mastered yet. Dean looks at his brother and sees that thank god, he hasn't shit or pissed himself, not yet. So he says "thanks."
He kneels on the floor, then sits. Sam looks so fucking uncomfortable. He takes off his jacket, pillows it underneath Sam's head. Then he tosses the jacket aside and pulls Sam's head into his lap.
And then there's nothing to do but sit and be glad he can be near Sam at all. It's too dangerous to be in the room when Sam is seizing, or hallucinating, or screaming in pain. He gets strong. He bites, his teeth snap at nearby flesh. Dean learned that the first time. The hard way.
"Would you like to drink more alcohol?" Cas says, holding out the bottle.
Dean takes it gratefully. His forehead is feeling tight; a sobering headache. He kinda wishes he could chug and chug and just pass out here, on the floor.
"The alcohol," Cas says. "Does it make you feel... better?"
"No. It makes you feel nothing."
Cas nods knowingly, and says rather cheerfully, "nothing is what I feel, when I drink alcohol. I don't understand the appeal. The taste is not good, and you feel nothing. Why drink it at all?"
Dean rolls his eyes at this angelic version of small talk. "Not nothing. It... it makes you have no feelings."
"But you have already drank yourself to intoxication."
Dean takes a long pull from the bottle. "Yeah. And?"
"And yet you remain in agony. From your posture and facial expression, I would liken it to physical pain."
Dean snorts. "I wish it were physical pain."
"Shut up. You're gonna wake him up."
Cas cocks his head. "I have induced what you humans would call a 'coma.' He will not wake until the blood--"
"Your mouth," Dean snaps. "Shut it."
Christ. Sometimes it's like hanging out with a three-year-old. A three- year-old with throat cancer and no fashion sense.
"I wish it was physical because then it would go away, okay? Now shut up."
Cas laces his fingers, considering this for a moment. "This... emotional pain. It persists? Always?"
Sam's head jerks in Dean's lap, snapping from one side to another. He bears his teeth and moans.
"Easy, Sammy," Dean says under his breath. Then louder, to Cas: "I thought you said he was in a fucking coma. Why is he hurting?"
"Some agony is untouchable," Cas says.
Dean knows the angel's not much for symbolism, and that he wasn't drawing a connection, and that his statement had nothing at all to do with Dean's agony being untouchable. But it makes his heart thump in his chest anyway, because what if Cas and the goddamn horseman are right? What if it is?
"He listens, you know. He can hear you," Cas says. Dean hadn't noticed him move, but there he is, knelt on the floor behind him and his brother. "God can hear you."
"I wasn't talking to God. I wasn't... I wasn' t talking to anybody. Just being drunk and stupid."
"I see." Cas closes his mouth, after he says this, and Dean is silently relieved that the angel didn't elect to tell him the truth this time, that yes, he was talking to God, begging God, saying God we're never gonna find you so show yourself, help us saves us save me.
"What perplexes me," Cas says, "is the origin of your pain. It took tremendous strength, for Sam to say no to Famine, to resist the demon blood. It proves that he is still human, that his soul is intact. There is no reason to be upset. You should feel proud."
Dean looks down at Sam, at Sam's stupid floppy hair, hanging in his stupid face. He takes a lock of his bangs and moves it, studies his little brother's squinty eyes and pointy nose.
"This is what I raised, Cas. This is what I raised. This is what I did."
He wishes Cas had something stupid to say, right then. But Cas is quiet so Dean has no choice but to let it all burn hot, what he brought back with him from hell, burn until he's rocking himself and his brother back and forth like some kind of fucking lunatic, wishing it would just hurry up and swallow him already, eat him right up.
"Your brother has many admirable qualities," Cas says finally. "He wishes to be good and do good things. At the outset, it was his love for you that led him down the wrong path. There is no sin in that."
Cas's mouth curves into an awkward, unpracticed smile, like the statement is going to fix everything.
"No sin?" Dean spits. "Look where the fuck we are, Cas."
Because Dean knows what happens when people love him. And that? That is where the agony comes from.
The end.


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Students from Ocean City, Mainland Regional and Oakcrest high schools took the top honors in the third annual Mathematical Mayhem competition held at Richard Stockton College on Saturday.
The event challenged 48 students from nine high schools in individual and team exams. The exams were created and graded by Stockton's math faculty. Members of the Stockton Math Club proctored the exams.
Dr. Chia-Lin Wu, associate professor of mathematics at Stockton and founder of the competition, said the experience is meant to reduce test anxiety, increase student confidence and provide high school students with an inside view of college life.
Competitors came from Absegami High School, Atlantic City High School, Atlantic County Institute of Technology, Cedar Creek High School, Egg Harbor Township High School, Mainland Regional High School, Oakcrest High School, Ocean City High School and Southern Regional High School.
Team Exam winners were:
First place: Ocean City High School — Maham Ahmad, Carolyn Previti and Isabel Benvenuti.
Second place: Atlantic County Institute of Technology — Stanimir Genov, Matthew Schwenger and Myra Bhatti.
Third place: Ocean City High School — Alec Helm, Ben Fischer and Matt Unsworth.
Individual Exam winners were:
First place, tie: Evan Heyman, of Mainland Regional High School, and Emily Hanna, of Oakcrest High School.
Third place: Jordan White, of Cedar Creek High School.
Contact Diane D'Amico:


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Beyonce Knowles, Idris Elba and Ali Larter star in Obessed. Due out in theaters April 24th, 2009.
But you could have a chance at watching the movie before it hits theaters at a special screening of Obsessed on April 23, 2009 in Hollywood, Florida (by I-95).
RULES: All you need to do is tell us what YOU are or have been "obsessed" with and you could qualify to be 1 out of 10 people that will win TWO free tickets. Keep it clean. But keep it funny and original. The best stories will win.
HOW TO ENTER: Write an email to email@example.com and send your story, along with your name and "mailing address" (so we could mail you the tickets if you win) to .
DEADLINE FOR ENTRIES: Friday, April 17, 2009 @ 5:00PM ***no exceptions***
Thanks and good luck…\


text:
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Adoption requests → Retailers Wiki
What is your username? Viller the Great
Please link to the wiki here: retailers.wikia.com
How many edits have you made on that wiki? 70
How many days/months have you been editing there? Since May 1st, 2012 (about one year and 18 days)
On the Special Pages → Special:ListUsers when was the last time an admin edited, and who was it? FastLizard4
Any other information: I really want to build up this wiki. It really needs to start fresh new.


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whos knows the band blue oyster cult..
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French fox Sophie Bonnet may have only made two films, but she certainly knew how to make an impression. Though she only played a small role in her debut film Vengo (2000), her second film, the controversial The Exterminating Angels (2006), gave her a much meatier role in every sense of the word! Although Sophie doesn't get nude, she looks positively scintillating in a sexy black bra as she and a guy get hot and heavy! It might be her shyness that did her in, but we certainly hope she gets...Join Mr. Skin for the full bio >>
The Exterminating Angels (2006) - as La femme de François


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Imagine sitting around a French farmhouse table waiting for dinner to be served--this would
be the bread they'd bring out. This loaf has a thick crust and soft white chewy interior with a
flavor that tastes of toasted wheat. We like it best when it's baked to a nice dark crust.
Frank's favorite bread! Farm loaves are $4.50 this month (regular $6.29).
Say [doh-bosh] This traditional Hungarian coffeehouse torte was created in 1887 by well known
chef and confectioner József C. Dobos (1847–1924). It's five thin layers of vanilla sponge
cake and espresso dark chocolate butter cream, all topped with pieces of crispy dark
caramel. Taste one of Hungary's most famous tortas! All dobos torta, whole and slices, are 20% off this month.


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