Demographic Dynamics and Economic Growth in Tanzania: An Error Correction Model Analysis

Abstract

This study examines how Tanzania’s economic growth, as indicated by Gross Domestic Product (GDP), has been impacted by demographic factors such as population size, birth rate, and death rate between 1990 and 2023. The study applies the Augmented Dickey-Fuller (ADF) test to evaluate stationarity using yearly time series data obtained from the World Bank. The results demonstrate that the variables are non-stationary at the level but stationary in first differences. A long-term equilibrium link between the demographic factors and economic growth is revealed by Johansen’s cointegration test, with one substantial cointegrating vector. To account for both long-term modifications and short-term dynamics, an Error Correction Model (ECM) is estimated. The findings show that whereas mortality rates hurt economic growth over time, birth rates have a favorable influence. Long-term economic growth and population size have a positive, but statistically negligible, relationship. While death rates have a considerable negative influence on economic growth, population size has a significant beneficial impact in the near run. In the near run, birth rates have little effect on economic growth. The residuals are confirmed to be normally distributed by the Jarque-bera normality test, and parameter stability is shown by the Cumulative Sum (CUSUM) test over the course of the sample period. The Granger Causality Wald tests reveal significant causal relationships, with death rates significantly Granger-causing economic growth, and the combined effects of demographic variables showing strong causality. Based on these findings, policy recommendations include enhancing human capital through education and vocational training, implementing family planning initiatives, and improving healthcare infrastructure to reduce mortality rates. These measures aim to leverage demographic changes for sustainable economic growth in Tanzania.