The rising incidence of youth unemployment, especially in emerging economies, calls for prompt attention of development experts and policy makers given its effect on sustainable growth. This challenge has worsened in recent times in Nigeria, hence, making it crucial to understand the factors driving youth employment. We analyzed the differential impact of sectoral growth on youth employment across rural and urban areas through a gender lens and identified the specific conditions needed for investment in sectors with potentials for job creation in the Nigerian economy. Data were analyzed using descriptive statistics, revealed comparative advantage (RCA), employment elasticity, and Logit regression model. It was observed that Nigeria has demonstrated a comparative advantage in the export of 17 products. Our findings also revealed that all the economic sectors in Nigeria have potential for creating employment at different levels with financial services contributing the highest (0.734) and manufacturing the lowest (0.056). The increase in education influenced employment and a higher likelihood of male youths’ employment in the services, construction, and industry sectors as compared to more female youths in the trade sector. Some common conditions that could aid firms’ production scale-up and increase job creation across all sectors include: increased access to finance, improved infrastructure (road, water, air, power, and rail), and favorable interest rates and exchange rates. We recommend that concerted effort be targeted at mainstreaming gender in all sectoral policies and key sectors be strengthened through targeted welfare reforms aimed at enhancing the capacities of the youths for sectoral relevance.

This study sought to explore empirically the impact of an Automated System for Customs Data (ASYCUDA) on customs revenue performance at the Liberia Revenue Authority (LRA). We used monthly time series data sourced from the LRA, the Central Bank of Liberia, and various series of the Harmonized Tariff of Liberia. The data spans from January 2015 to December 2018. We employed the bounds testing approach to the Cointegration and Error Correction Model that is established within the Autoregressive Distributed Lag framework. The results revealed that total trade (Import*Export), goods and services tax (GST) and ASYCUDA positively impact customs revenue performance in both the short and long run while export and inflation were found to negatively affect customs revenue performance in both the short and long run. In addition, an error correction term of -0.837 was found, indicating that 83.7 per cent of the deviation created by shocks in the short run will be corrected in the long run; thus, confirming the existence of a long-run relationship among the variables used. For policy purposes, these findings suggest that ASYCUDA be rolled out to other ports of entry and exit to boost the efficiency of customs revenue generation. Moreover, capacity building should be carried out to complement the effective use of ASYCUDA. We also recommend that policies to reduce inflation be prioritised.