Search

This study examined the relationship between labour productivity and agricultural agriculture development in Sub-Saharan Africa (SSA) from 1991 to 2021. The study is based cross-sectional data covering the period 1991-2021 on nine (9) SSA countries sourced from the World Bank Development Indicator (WDI) database. The result of the Panel Dynamic Least Squares (POLS) estimation technique utilised revealed that population growth (β = 0.0203, t-value = 2.092, & Prob. = 0.0398) exerts a significant positive effect on agricultural development while both industrial output (β = -0.8698, t-value = -2.1225, & Prob. = 0.0371) and services productivity (-1.2667, t-value = -2.6510, & Prob. = 0.0098) exert a significant negative effect at 5% level of significance. Although, the effect of labour productivity on agricultural development is negative (β = -0.2335, t-value = -0.949, Prob. = 0.3455), it is not statistically significant. Thus, the low productivity in industrial sector and the structural shift in favour of services posed adverse effect on agricultural productivity in SSA. This underscore the need to maximise the potentials of the population growth through policy options including rural infrastructural development, price supports, crop insurance and tax incentives to stabilise income and make the sector attractive to the labour force.

Purpose — This paper aims to examine the relationship between the shadow economy and income inequality in Nigeria. Method — The paper employed Autoregressive Distributed Lag (ARDL), Fully Modified Ordinary Least Square (FMOLS), and Granger causality. This methodology is used to avoid endogeneity and heterogeneity in the model. This paper gauged income inequality using two diverse indicators of the Gini coefficient: the Gini index in proportion to household disposable income and the Gini index in proportion to household market income. In accordance with the literature, our empirical analysis draws on data from the Standardized World Income Inequality Database (SWIID), the World Bank, World Development Indicators, and the International Country Risk Guide (ICRG) for Nigeria from 1991 to 2018. Result — The findings of ARDL and FMOLS suggested a positive relationship between income inequality and the shadow economy, based on both measures of income inequality. In the short term, however, the shadow economy and income inequality are negatively correlated. Furthermore, we discovered a one-way causal relationship exists in Nigeria between the shadow economy, household disposable income, institutional democracy, household market income, and corruption control (CCI). Recommendation — Shadow economy has been regarded as an avenue to create job opportunities and raise poverty-income levels. It is critical that, for the shadow economy to reduce income inequality in Nigeria, policymakers should develop much better policies aimed at addressing income inequality. Contribution — In order to understand the relationship between income inequality and shadow economy activities in Nigeria, this study employed three methodologies, namely: Autoregressive Distributed Lags (ARDL), Fully Modified Ordinary Least Squares (FMOLS), and Granger Causality. The result offers reliable recommendations for pro-poor interventions that aim to limit the growth of informality via redistributing incomes.

This paper examines the effect of exchange rate fluctuations on the capital account in Nigeria from 1980 to 2015. The data used for the study were retrieved from the Central Bank of Nigeria Bulletin. The study employed Johansen co-integration test, Error Correction Model (ECM) and Fully Modified Ordinary Least Square (FMOLS). Evidence from the study shows that exchange rate has no effect on the capital account. As a result of the study, production in the Nigerian economy must be encouraged through availability of domestic credit while market determined interest rate should be encouraged to stimulate economic growth and investment

In this paper, the way in which economic growth influences income distribution is examined with a focus on Sub-Saharan Africa (SSA). Despite considerable growth in a number of the SSA countries, the region has been slow in reversing the rising trend of income inequality. A large proportion of countries in the region globally rank among economies with extreme income inequality. The study covers a period from 1995 to 2015, due to the limited data on the measure of income inequality, the Gini index, for the largest number of the countries of the region. The Generalized Method of Moments (GMM) system was employed in examining this paradox. The findings of this research study do not only suggest the presence of an inverted-U relationship between economic growth and income inequality, but the supposition of the S-shaped curve hypothesis in the interplay of growth and inequality was also tested and confirmed. It can be concluded that in no way do spurts in economic growth bring about diminution in income disproportion in Sub-Saharan Africa.

Introduction: It is likely that enterprises and entrepreneurs will be encouraged to engage in the formal sector as economies integrate more fully into the global economy. Thus, we begin our investigation by looking at the relationship between Nigeria's shadow economy and disaggregated trade openness. Based on Nigeria's inadequate institutional quality, our second purpose is to conduct further research on the role institutional quality plays in moderating the relationship between its shadow economy and disaggregated trade openness between 1991 and 2018. Methods: The fully modified ordinary least squares (FMOLS) and Granger causality methods are used in this paper to investigate the nexus and causal effect in time-series analysis. Results: The coefficients of institutional quality, import-to-GDP ratio, government expenditure, and financial development all have an adverse impact on Nigeria's shadow economy. The inflation proxy with the consumer price index, economic growth, and the export-to-GDP ratio all improve Nigeria's shadow economy. The findings of interaction between the import-export ratio and the quality of institutions positively affect the Nigerian shadow economy. The pairwise Granger causality exercise comes after the regression analysis. Conclusion and suggestion: The study concludes that the size of Nigeria's shadow economy is influenced by institutional quality, import trade, government expenditures, and financial development. Similarly, we find no causal relationship between disaggregated trade openness in Nigeria and institutional quality. As a result, policymakers and the country's government must act quickly and decisively to reduce the impact of informal activities on the country's economy.