Impacts of public debt remains unclear in Africa due to some heterogeneous macroeconomic fundamentals. Hence, this study focuses on a highly indebted nation, Nigeria, and Botswana, with a relatively low debt profile. The study utilizes the dual gap theoretical framework and deploys the Autoregressive Distributed Lag (ARDL) model to study external debt, and its influence on sectoral performance in Nigeria and Botswana between 1981 and 2019. The study focuses on the following three sectors; service, agriculture and industry with data from World Development Indicators (WDI). Findings reveal that only agricultural sector is influenced positively by external debt in Botswana, while external debt in the long run has a significantly detrimental impact in the Nigerian agricultural sector. We therefore, recommend both governments to be prompt in monitoring of loans, right from when it is acquired to how it is being spent.
This study examined inequality and regional poverty in Nigeria using the Nigeria Living Standard Survey – NLSS (2019), and adopted decomposition analysis of the Foster-Greer-Thorbecke Index. It was therefore found by the study that in this regard, inequality and regional poverty is more in the Northern Nigeria with North West having the greatest head count ratio or poverty incidence, poverty gap or poverty intensity and poverty severity. This is followed by the North East, and North Central. Going southern part of the country, it was found by the study that inequality and regional poverty is more in South West, followed by South-South, and least in the South East. The study therefore recommends that there is urgent need for national policies geared towards reduction of poverty incidence in all the geopolitical regions of the country. This could come through employment creation, increased investment in infrastructure, increased development and support of informal sector businesses, among other social investments that could increase incomes through increased employment.
This study offers an analytical evaluation of the effects of Free Trade Area (FTA) agreements on trade, revenue, and welfare in Nigeria. The study applied World-Integrated Trade Solution/Software for Market Analysis and Restrictions on Trade (WITS-SMART), anchored on a partial equilibrium model (PEM) for its simulations. The study simulated 100% tariff elimination on selected products under Harmonized System (HS)-2 classification code sourced from Trade Analysis Information Systems (TRAINS) and Common Format for Transient Data Exchange (COMTRADE). The study’s findings show that the African Continental Free Trade Area (AfCFTA) agreement will benefit Nigeria’s economy from trade creation estimated at US$8,860.419 million, including a favorable welfare gain to the value of US$740.571 million. Nevertheless, Nigeria will sustain losses in trade revenue, valued at US$6,142.061 million. The study recommends proficient revenue management and well-diversified revenue collection sources, such as improvement in Value Added Tax and Ad-Valorem duty, to cushion the effects of the revenue loss resulting from tariff elimination in the FTA.
This study examines the drivers of households’ off-the-farm income diversification patterns using four waves of the Nigeria General Household Survey panel data. The study further investigates the motives for households’ off-the-farm income diversification patterns. The Simpson Income Diversification index and count index were used to measure income diversification. The results of heteroscedastic fractional probit correlated random effects and Poisson fixed effects indicate that the level of diversifying off-the-farm income is driven by attributes of household such as assets value, household size, female headship, level of education, dependency ratio, access to credit, distance to tarred road and geographical location of household at the national level. The study found that the motive for accumulation drives households’ off-the-farm income diversification rather than the motive for survival. Specifically, non-poor households in the urban sector seem more probable to expand into off-the-farm income enterprises than poor rural households. A major finding is that the choice of off-the-farm income diversification proxy has a great influence on the drivers.
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