Dynamic relationships among non-oil revenue, government spending and economic growth in an oil producing country: Evidence from Nigeria

This paper investigated the dynamic relationships among non-oil revenue, government spending and economic growth in Nigeria for the period of 1981 to 2015. After establishing a long run relationship among the variables, the error correction model, impulse responses were estimated as well as the granger causality test among the variables. The results of the short run and long run showed negative effects of government spending on economic growth while non-oil revenue showed positive effect on economic growth. We also found non-oil revenue to have negative shocks on economic growth while the government spending shock was positive. The Granger causality revealed that government spending granger caused both non-oil revenue and economic growth supporting the Keynesian and spend-tax hypothesis in Nigeria over the period of the study. We recommend that the economy of Nigeria should be diversified into non-oil sector rather than relying solely on revenue from oil export. JEL codes: O23, Q28, O47, Keywords: Non-oil revenue, Government spending, Cointegration, Short run and long run, Impulse response, Nigeri

Poverty status of arable farm households in Akinyele Local Government Area of Oyo State, Nigeria

The study assessed the poverty status of arable farm households in Akinyele Local Government Area of Oyo State. Ninety (90) respondents were randomly selected using the multistage sampling technique while data was collected using structured questionnaire. The data generated from the survey were analysed using descriptive statistics, poverty measures and a logistic regression model. The descriptive analysis shows that majority of the rural households were headed by males (76.67%), most of them (82.22%) were married and had a mean age of 54.5  years with 84.45% of them having a formal education. The mean household size of about 7 persons was obtained with a mean farm size of 6.66 hectares in the study area. The mean farming experience was 13.63 years, and the majority (86.67%) of the respondents did not receive any credit for their farming activities at a time or the other. The poverty status indicated that 54.44% of the respondents are poor while 45.56% are non-poor. The result of the factors influencing the poverty status using logistic regression analysis reveals that being married (p<0.05) and household size (p<0.1) were positive and significant predictors of the probability of being poor while access to credit (p<0.1) and per capita income (p<0.01) were negative and significant predictors of the probability of being poor. The study, therefore, recommended thatquality credit accessibility and participation in skills acquisition programmes through diversification should be encouraged due to their capability of improving the household income of the poor