TRENDS IN MIGRATION, UNEMPLOYMENT AND POPULATION: A POST-COVID-19 FORECAST OF CAPACITY DEVELOPMENT IN THE GAMBIA
Raphael Kolade Ayeni () and
Emmanuel Oluwatobi Shaib
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Raphael Kolade Ayeni: Department of Economics, School of Business and Public Administration, University of the Gambia, Banjul, The Gambia
Emmanuel Oluwatobi Shaib: #x2020;Department of Economics, College of Education and Social Sciences Legacy University, Banjul, The Gambia
Global Economy Journal (GEJ), 2020, vol. 20, issue 04, 1-21
Abstract:
As a developing economy, three major economic problems witnessed in the Gambia are the growing unemployment rate, migration (immigration and rural–urban drift) leading to urban population growth and the growing semi-skilled working population in the face of unemployment. This study seeks to answer the question of how the Gambian economy can plan to overcome these problems, coupled with post-COVID-19 global economic shocks, through a technically planned capacity development. In this paper, the trends in variables representing capacity development indicators, migration, unemployment and working population in the Gambia are studied using the Autoregressive Integrated Moving Average (ARIMA) model. To project a system of interrelationship among these variables in the Gambia, the study employs the Vector Autoregressive (VAR) forecast analysis for the period between 1990 and 2019, thereafter generates a five-year forecast. The findings confirm that investment into the educational sector in developing economies is bound to yield increasing return to scale in the next five years. Investment into education, training and skill acquisition, if done, will attract the transfer of technical and managerial skills and technology for the purpose of building up general national capacity in such a developing economy.
Keywords: ARIMA; capacity development; forecast; migration; population; the Gambia; unemployment; VAR (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:gejxxx:v:20:y:2020:i:04:n:s2194565920500189
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DOI: 10.1142/S2194565920500189
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