A Vector Error Correction Model Approach to Investigate the Causal Relationship among Energy Consumption, Real GDP, and Industry Value Added of Bangladesh - Gupta, Moumita Datta; Rahman, Md. Mahfuzur; Amin, Mohammad Mastak Al (European Scientific Journal, ESJ, 2020)
The paper focuses on investigating the casual relationship among Energy Consumption, Real GDP, and Industry Value Added of Bangladesh using the World Bank Development Indicators data set. The Granger causality approach has been applied to identify the short-run causality direction for all possible pairs of dynamic variables of the study. Results from the approach indicate the unidirectional short run causal relationship from Real GDP to Energy Consumption, while another unidirectional short-run causality has been found from Industry Value Added to Real GDP. The concept of cointegration and Vector Error Correction Model (VECM) are employed to find the long-run relationships among the variables. Our results show the existence of long run relationship between each pair of variables. Furthermore, the Variance Decomposition (VDC) techniques and Impulse Response Function (IRF) was also used to measure the extent/degree of dynamic properties of the variables. Bangladesh has an emerging economy with limited energy resources. Here, the evidence from our study would help policymakers in setting the appropriate energy consumption policies that will enhance and sustain economic growth for the welfare/development of this country.