Relationship between Population and Economic Growth in Kenyan Counties

The debate in the literature on the relationship between population growth and economic growth is inconclusive. This study aims to fill in that knowledge gap by using panel data from 47 Kenyan county governments from 2014 to 2022. It is assumed that the effect is not homogeneous for all counties, but rather changes depending on their level of development and population growth. The study employs panel unit root, panel cointegration and Granger-Wald causality on panel vector autoregression processes in combination with estimating the general method of moments to investigate the relationship between these two variables, at a more localized level. Generally, the results of the Pedroni cointegration method show that there is a long-run relationship between county population and county-level economic growth. According to the empirical findings of the study, there is a bidirectional Granger causality relationship between population growth and economic growth. It's possible for population growth to help or hurt economic growth, and economic growth can affect population growth. The study recommends the implementation of population policies and socioeconomic development policies that are mutually reinforcing.

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Publication Details

Journal
South Asian Journal of Social Studies and Economics
Published
2025-03-20
DOI
https://doi.org/10.9734/sajsse/2025/v22i4985
Citations
1
Primary Topic
Poverty, Education, and Child Welfare
Type
article
Field-Weighted Citation Impact
2.37
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article

Relationship between Population and Economic Growth in Kenyan Counties

Joseph M. Kinuthia, Naftaly Mose, Edward Kipchirchir
1 citations
South Asian Journal of Social Studies and Economics
Poverty, Education, and Child Welfare
2.37
article

Relationship between Population and Economic Growth in Kenyan Counties

Joseph M. Kinuthia, Naftaly Mose, Edward Kipchirchir
article en
1 citations

Abstract

The debate in the literature on the relationship between population growth and economic growth is inconclusive. This study aims to fill in that knowledge gap by using panel data from 47 Kenyan county governments from 2014 to 2022. It is assumed that the effect is not homogeneous for all counties, but rather changes depending on their level of development and population growth. The study employs panel unit root, panel cointegration and Granger-Wald causality on panel vector autoregression processes in combination with estimating the general method of moments to investigate the relationship between these two variables, at a more localized level. Generally, the results of the Pedroni cointegration method show that there is a long-run relationship between county population and county-level economic growth. According to the empirical findings of the study, there is a bidirectional Granger causality relationship between population growth and economic growth. It's possible for population growth to help or hurt economic growth, and economic growth can affect population growth. The study recommends the implementation of population policies and socioeconomic development policies that are mutually reinforcing.

South Asian Journal of Social Studies and EconomicsVol. 22(4)
University of Eldoret (KE)
Openalex Percentile: Top 13%
Poverty, Education, and Child Welfare
2.37
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Relationship between Population and Economic Growth in Kenyan Counties — Joseph M. Kinuthia, Naftaly Mose, et al. · South Asian Journal of Social Studies and Economics (2025) | TGRS Research Map | TGRS