Nexus between economic growth, energy use, urbanization, agricultural productivity, and carbon dioxide emissions: New insights from Bangladesh

Abstract

• Improving environmental quality through reducing emissions is the central pillar of climate change mitigation and achieving sustainable development goals. • The empirical findings reveal that economic growth, energy use, urbanization, and reduced agricultural productivity increase CO 2 emissions in Bangladesh. • Several unit root tests (ADF, DF-GLS, and P-P), cointegration test (ARDL bounds test, Johansen cointegration test, and Engle-Granger cointegration test), and cointegration models (DOLS, FMOLS, CCR) have been utilized to confirm the accuracy of the results. • The findings of the study offer policymakers more detailed and helpful information for establishing successful policies in the areas of low-carbon economies, renewable energy, sustainable urban development, and climate-smart agriculture that would reduce emissions in Bangladesh. Greenhouse gases (GHGs) emissions, notably carbon dioxide (CO 2 ) emissions are causing global climate change, which poses enormous hazards to human life, the environment, development, and sustainability. Bangladesh is predominantly an agricultural country experiencing continuous economic growth and rapid urbanization which is causing higher energy consumption and CO 2 emissions. The present study empirically explores the nexus between economic growth, energy use, urbanization, agricultural productivity, and CO 2 emissions in Bangladesh. Time series data from 1972 to 2018 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 reveal that economic growth, energy use, urbanization, and reduced agricultural productivity increase CO 2 emissions in Bangladesh. 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 is utilized to capture the causal linkage between the variables. This study adds to the current body of knowledge by shining light on the factors that contribute to environmental degradation in Bangladesh. This article put forward policy recommendations aimed at sustainable development by establishing strong regulatory policy instruments to reduce environmental degradation.