Saturday, 4 April 2026

Sectoral Output and Employment Dynamics in Nigeria: Evidence from an ARDL Analysis (1981-2021)| Chapter 8 |Economics, Business and Management: Recent Advances Vol. 1

 

Background: In Nigeria, a country with a predominantly youthful population estimated at over 224 million, the capacity for growth to generate productive jobs is a pressing development concern.

 

Aim: This study examines the employment effects of sectoral contributions to Nigeria’s GDP and evaluates the relative labourabsorption capacity of agriculture, industry and services over 19812021. It seeks to identify which sectors are growthled in employment generation and to inform policy that aligns growth with inclusive job creation. The core problem addressed in this study is the lack of clear, long-run, sectorally disaggregated evidence showing the employment contributions of the broad sectors of agriculture, industry, or services. Existing studies have either focused on aggregate relationships, examined single sectors in isolation, or limited their analysis to shortrun dynamics.

 

Theoretical Framework: The analysis is grounded in Keynesian demand theory and Okun’s law, which link aggregate output to employment, and extends these to a sectoral perspective. The framework recognises capital intensity, technology bias, and value chain linkages as mediating mechanisms that determine whether sectoral growth translates into net employment gains.

 

Methodology: Using annual data for 1981-2021 sourced from the Central Bank of Nigeria’s statistical bulletin and Penn World Tables, the study proxies sectoral output by agricultural, industrial and services GDP and measures employment by total employed persons. After log transformation and unit root testing, an Autoregressive Distributed Lag (ARDL) bounds testing approach is employed to detect cointegration and estimate short-run dynamics and long-run elasticities. Estimated models control for inflation, public expenditure and lagged employment; diagnostic checks ensure robustness.

 

Results: Bounds tests indicate cointegration at both aggregate and disaggregated levels. Long-run elasticities indicate that agricultural GDP has the highest employment intensity, supporting a growth-led employment strategy. Industrial expansion displays characteristics of jobless growth, while servicesector growth is associated with jobloss dynamics, reflecting low labour absorption due to capital and technology intensity. Public expenditure shows a positive longrun association with employment. In the aggregate analysis, a 1% rise in GDP is associated with a 0.27% increase in employment in the short run.

 

In comparison, a 1% increase in GDP raises employment by about 0.53% in the long run, roughly double the shortrun elasticity, indicating that the employment response to growth strengthens over time. When GDP is disaggregated, shortrun dynamics reveal important heterogeneity across sectors. Agricultural output (AGRGDP) exerts a positive and significant shortrun effect on employment (approximately 0.15% per 1% AGRGDP increase), while industry and services coefficients are negative and statistically insignificant. Agricultural GDP displays a large and significant longrun elasticity (≈0.52), implying that sustained agricultural expansion is strongly employmentintensive. By contrast, industry and services show small negative longrun coefficients (statistically insignificant).

 

Conclusion: Policy should prioritise targeted support for agriculture and labourintensive industrialisation, strengthen valuechain investments, and align fiscal allocations to maximise employment outcomes. Reorienting sectoral growth toward labourabsorbing activities is essential to mitigate Nigerias persistent unemployment challenge. Future research should disaggregate services and industry to identify subsectoral employment potentials.

 

 

Author(s) Details

Ololade J. Olaniyan
Afe Babalola University, Ado-Ekiti (ABUAD) Business School - Ibadan, Nigeria.

 

Rosemary Bukola Ajala
The Federal Polytechnic, Ado Ekiti, Nigeria.

 

Please see the book here :- https://doi.org/10.9734/bpi/ebmra/v1/7319

No comments:

Post a Comment