Economic growth and unemployment linkage in a developing economy: a gender and age classification perspective
This paper examined the growth and unemployment linkage from a gender-classification perspective using the Nigerian economic environment. The autoregressive distributed lag model in its baseline form, the bound test, and error correction representation were used as the estimation approach. Annualize...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
LLC "CPC "Business Perspectives"
2021-01-01
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Series: | Problems and Perspectives in Management |
Subjects: | |
Online Access: | https://businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/14566/PPM_2020_04_Kalu.pdf |
Summary: | This paper examined the growth and unemployment linkage from a gender-classification perspective using the Nigerian economic environment. The autoregressive distributed lag model in its baseline form, the bound test, and error correction representation were used as the estimation approach. Annualized time series spanning 1981 to 2017 were used for the variables of interest. Generally, it was found that female unemployment has a positive significant influence on GDP growth rate in Nigeria, while youth unemployment negatively and significantly influences GDP. It was also found that male unemployment does not significantly affect the GDP growth rate in Nigeria. In the long run, the main variables influencing GDP growth rate within the context of this study include unemployment rate, ratio of labor force size to the national population, female unemployment rate, and youth unemployment rate. The error correction representation and the bound test estimates confirm that growth adjusts to the dynamics of the studied unemployment variables. The study advocates for an increase in government capital expenditure, as this is theoretically and practically known to create new jobs. This spending should go into real and core productive sectors that would create upstream and downstream jobs opportunities. |
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ISSN: | 1727-7051 1810-5467 |