Impact of Energy Price Adjustments on Bangladesh Economy: A Macro-Econometric Modeling Approach

Abstract

The domestic price of energy products including electricity, oil and natural gas has long been administered in Bangladesh. The government provides subsidy to all these energy products in various forms. The government of Bangladesh incurs a large amount of expenditures in the form of subsidies every year for the energy sector. Against the backdrop of an overwhelming burden of subsidies, the Bangladesh government has intensified its reforms of energy prices in recent times in order to bring fiscal discipline. This study thus, aims to assess the impact of energy price adjustments under a macro-econometric modeling framework. Though this is a model of the macro-economy of Bangladesh, it has been extended to link up the macroeconomic consequences of the changes in the government energy expenditures. The effect of energy price changes on macroeconomic outcomes has been predicted with alternative scenarios of deregulations of domestic energy prices, particularly to the outcomes for growth, inflation, fiscal balances and external balances. The prediction has been done for the period 2015-16 to 2020-21 in line with Seventh Five Year Plan period (2015-2019) and Perspective Plan, 2021. Within sample (1985-2011) predictive accuracy (or validity) of the model is checked by the mean percentage error (MPE) and the root mean square percentage error (RMSPE). We run stochastic simulations to know the out of sample (2012-2021) performance of the model. Under these simulations, the bootstrap method is used to give random shocks into individual endogenous variables but for out of sample period. Random shocks are generated from individual residuals of variables for within sample period. 1000 stochastic simulations/replications are run through bootstrapping. 100 quintiles are computed to compare the magnitudes out of sample forecasts, because within the sample uncertainty captured by residuals, it makes variations out of sample forecasts. Overall, the out of sample performance of the model seems quite good. The model initially analyses macroeconomic data for the period 1980-2011. The sample validation and out of sample prediction imply that the model fit was good and it can be used for policy simulations through assumed shocks. Considering the current gap between subsidised and government’s buying price of energy, reasonable alternative scenarios of price shocks were derived and subsequently applied. The simulated results are drawn for the period 2015-2021 making it consistent with the Seventh Five Year Plan and the Perspective Plan. The results suggest that any upward revision of energy prices will be slightly inflationary and as a result the real GDP growth rate will fall slightly during the predicted period. A note of caution in explaining the result is that it is based on the assumption that other variables will remain as usual. The GDP growth and inflationary situation might improve if changes in other macroeconomic indicators take place along with energy price adjustments.