Growth Acceleration and Demographic Structure: The Case of ECOWAS Countries Cover Image

Growth Acceleration and Demographic Structure: The Case of ECOWAS Countries
Growth Acceleration and Demographic Structure: The Case of ECOWAS Countries

Author(s): Uğur Ursavaş
Subject(s): Labor relations, Economic policy, Demography and human biology, Economic development
Published by: Ahmet Arif Eren
Keywords: Economic Growth; Growth Accelerations; Demographics; Probit Model;

Summary/Abstract: The demographic structure of countries has significant effects on economic growth. Most developing countries are passing through a demographic transition. Although African countries still have higher fertility rates than other developing countries, fertility rates show a decreasing trend, which leads to a window of opportunity for potential demographic dividend for African countries. Within this context, this paper investigates the relationship between growth accelerations and demographic structure in ECOWAS (Economic Community of West African States) countries over the period 1961-2019. To do so, first, we identify the growth acceleration episodes using the growth acceleration methodology developed by Hausmann et al. (2005). Then, we test the demographic determinants of growth accelerations employing the panel probit regression method. The results show that while urban population and life expectancy have a significant and positive impact on the likelihood of growth accelerations, the fertility rate has a negative and significant impact on the probability of growth accelerations. In other words, an increase in urban population and life expectancy at birth increases the likelihood of growth accelerations, whereas an increase in fertility rate decreases the probability. However, the results show a negative but statistically insignificant relationship between age dependency, young-age dependency, and old-age dependency ratios and the likelihood of growth accelerations.

  • Issue Year: 6/2022
  • Issue No: 3
  • Page Range: 1059-1070
  • Page Count: 12
  • Language: English
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