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.

中文翻译：

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移民、失业和人口趋势：COVID-19 后冈比亚能力发展预测

作为一个发展中经济体，冈比亚面临的三大经济问题是失业率上升、导致城市人口增长的移民（移民和城乡流动）以及面对失业的半熟练劳动人口不断增长。本研究旨在通过技术上有计划的能力发展来回答冈比亚经济如何计划克服这些问题以及 COVID-19 后全球经济冲击的问题。在本文中，使用自回归综合移动平均 (ARIMA) 模型研究了代表冈比亚能力发展指标、移民、失业和工作人口的变量趋势。为了在冈比亚规划这些变量之间的相互关系系统，该研究采用了 1990 年至 2019 年期间的向量自回归 (VAR) 预测分析，然后生成了五年预测。调查结果证实，对发展中经济体教育部门的投资必将在未来五年内产生越来越大的规模回报。如果对教育、培训和技能获取进行投资，将吸引技术和管理技能和技术的转移，以在这样一个发展中的经济体中建立总体国家能力。