Abstract
This article describes the data for examining the influence of government expenditure and revenue on Nigerian economic growth.
a b s t r a c t
This article describes the data for examining the influence of government expenditure and revenue on Nigerian economic growth. Data were extracted from the World Bank database and Central Bank of Nigeria (CBN) Statistical bulletin. The data are available with this article. The data is related to the research article "Newly proposed estimator for ridge parameter: an application to the Nigerian economy" (Lukman and Arowolo, 2018) but not discussed in detail. This data article will assist economists in identifying factors that will affect the economy of a country, especially in the African region. 
Value of the data
The data will be useful for modelling purposes, especially relating to the Nigerian economic growth.
Value of the data
The data can be used to establish a relationship between capital expenditure, recurrent expenditure, and gross domestic product.
Value of the data
It can also be used to examine the impact of oil and non-oil revenue on economic growth.
Data
The data consists of real gross domestic product from the World Bank database. Recurrent expenditure on economic services, Recurrent expenditure on transfers, Recurrent expenditure on social and community services, capital expenditure on economic services, capital expenditure on transfers and capital expenditure on social and community services, oil and non-oil revenue from the CBN Statistical Bulletin for Nigeria covering a period of 1970 to 2013 (see Supplementary Table 1) . Real GDP is expressed in current US dollars while other variables extracted from the CBN bulletin are expressed in billion nairas.
Experimental design

Design
The data on the gross domestic product was obtained from the World Bank's World Development Indicators (WDI) [5] . The data that provides detail on government expenditure and revenue were extracted from the database of the Central Bank of Nigeria (CBN) Statistical Bulletin [6] . The gross domestic product was expressed as a function of government expenditure and revenue. The regression model is defined as follows:
Design
where Y t is the gross domestic product, X t1 represent Recurrent Expenditure on Economic Services X t2 represent Recurrent Expenditure on Social and Community Services, X t3 represent Recurrent Expenditure on Transfers, X t4 represent Capital Expenditure on Economic Services, X t5 represent Capital Expenditure on Social and Community Services, X t6 represent Capital Expenditure on Transfers, X t7 represent Oil Revenue and X t8 represent Non-oil Revenue.
Method of data analysis
The descriptive statistics are presented in Table 1 while Fig. 1 shows the trends each of the variables follow. Table 2 provided the unit root test for the data for the original form of the data and their first difference. Cointegration test of the all the variables is provided in Table 3 . The long-run estimates are provided in Table 4 using ordinary least squares (OLS). Articles [1] [2] [3] [4] suggested the use of a ridge estimator as an alternative to OLS. Readers can access article [1] [2] [3] [4] for further details. The ridge regression estimate is also provided in Table 4 . 

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