Dynamic impacts of economic growth, energy use, urbanization, agricultural productivity, and forested area on carbon emissions: New insights from Kazakhstan

Abstract

The study aims to investigate the dynamic impacts of economic growth, energy use, urbanization, agricultural productivity, and forested area on carbon dioxide (CO2) emissions in Kazakhstan. Time series data from 1996 to 2020 were utilized by employing the Dynamic Ordinary Least Squares (DOLS) approach. The Autoregressive Distributed Lag (ARDL) bounds test revealed evidence of cointegration among the variables in the long run which has been verified by the Johansen cointegration test and Engle-Granger cointegration test. The empirical findings revealed that a 1% increase in economic growth, energy use, and urbanization cause an increase in CO2 emissions by 0.14%, 0.81%, and 1.28% in Kazakhstan. Conversely, a 1% increase in agricultural productivity and the forested area may lead to CO2 emissions reduction by 0.34% and 2.59%, respectively in the long run. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test was utilized to capture the causal linkage between the variables. This article put forward policy recommendations in the areas of low-carbon economy, renewable energy, sustainable urban development, climate-smart agriculture,