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This paper is an empirical analysis of the impact of economic growth on poverty reduction while controlling for inflation and employment over the period 1997-2019. The study seeks to provide insights into the process of alleviating poverty in Kenya. Empirical analysis is done using Autoregressive Distributed Lag (ARDL) model approach. The time series was first transformed into logarithmic form before contacting unit root test for stationarity using the Augmented Dickey-Fuller (ADF) test. According to the ADF test results, the dependent variable is integrated of order one while the explanatory variables are integrated of different orders. None of the variables is integrated of order above one. As a result, bounds test was used to test for cointegration. The bound’s test null hypothesis of no levels relationship was rejected. Due to the presence of long-run relationship, Error Correction (EC) model was specified for estimation. The coefficient of the error correction term was negative as expected and statistically significant at 5% level. The error terms were free from serial correlation and their variance was constant. Multicolinearity was not a problem and the model was very stable thus valid for forecasting. The results provide evidence that economic growth fosters poverty reduction in Kenya.
Maundu et al. (Mon,) studied this question.