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Oil Price Volatility and Its Impact on Economic Growth and Food Security in Bangladesh

Mousumi Saha
Department of Agricultural Statistics, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

Seikh Mohammad Sayem
Department of Agricultural Statistics, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

A. K. M. Abdullah Al-Amin
Department of Agricultural Economics, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

Shankar Majumder
Department of Agricultural Statistics, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

Abstract/ Executive Summary:

This study empirically examines oil price volatility and the impact of oil price changes on the growth of the economy and food security in Bangladesh. The study uses yearly data of macroeconomic variables from 1991 to 2015 and global food security index (GFSI) for the period 2012 to 2015. Furthermore, data of GFSI for previous four years have been simulated using exponential model. The GARCH (2, 1) model with minimum AIC postulates that volatility was high in the previous period and it has been continued to be lower in the current period (i.e. 2015). The co-integration test and error correction model exhibit that both in short-run and long-run case the increasing oil price negatively affected the growth of the economy. The simultaneous equations regression model using three-stage least squares estimator discloses that an increase in oil price declines the economic growth and food security simultaneously and significantly. Moreover, this study suggests that oil price volatility is not a good sign for the economy of Bangladesh, since, the country is an importer of crude oil, government policy should be quick responsive in relation to international oil market to create consistent oil market and sustainable economic development in Bangladesh.

Keywords: Economic growth; Econometric modeling; Food security; Oil price volatility

Location: Department of Agricultural Statistics, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

Start Date: 00-00-2012

End Date: 00-00-2015

Program Area: Socio-economic and Policy

Non-commodity: Performance

Objectives:

Keeping in view of these reports about significant impacts of crude oil price on economic growth and food security for developing countries, it would be interesting to know the situation in the perspective of Bangladesh. Being an oil importing country, an increase of world oil price would increase the production costs of the country that retard its economic growth and food security, for that reason, our study endeavours to incorporate economist’s perceptions through the primary survey for rigorous policy guidelines to ensure consistent oil market. Moreover, our findings may help to answer various questions which are still far from consensus in the literature

Methodology:

Data The secondary data have been collected from Bangladesh Economic Review (BER), World Bank (WB), Food and Agriculture Organization (FAO) and Inflation Data.com. The data on international crude oil price, import crude oil price, Real Gross Domestic. Product (RGDP), Gross Capital Formation (GCF), Labor Force Participation Rate (LFPR), Exchange Rate (ER) and Consumer Price Index (CPI) have been taken from 1991 to 2015 whereas the value Global food security index (GFSI) has been taken for the period 2012 to 2016. Again, the data of GFSI on previous four years (2008-2011) have been simulated through an exponential model. The primary data have also been collected from economic specialists using questionnaire survey for finding out the reasons behind oil price volatility and taking appropriate suggestions to reduce possible negative effects on economic growth and food security. Model Specification: Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model Correlogram and different unit root tests especially the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) test have been adopted to test the stationarity of international oil price and import oil price. Hence, the GARCH model has been applied to measure the volatility of both international oil price and import oil price. The reasons of using GARCH model are: (i) forecast confidence intervals may be time-varying, so more accurate intervals can be obtained by modeling the variance of the errors and (ii) more efficient estimators can be obtained, if heteroscedasticity in the errors is handled properly. The GARCH (u, v) models for the international oil price is-Vector Autoregression (VAR) modeling and Johansen co-integration procedure The Johansen co-integration procedure is the extension of univariate Dickey-Fuller test to multivariate VAR framework. The estimation strategy is as follows: Firstly, the stationarity in each variable has been checked. Secondly, a Johansen co-integration test among the variables has been done to check whether a long run relation exists among the series. And finally, the shortrun dynamic behaviour among OP, GCF, LFPR and RGDP has been studied by error correction model. Simultaneous equations regression model Since global food security index (GFSI) is a multidimensional aspect, a change in oil price may not have the direct impact on it. Firstly, Granger causality test has been adopted to find out the nature of causality among OP, RGDP, CPI, and GFSI. Then, simultaneous equations regression model has been used to show the relationship between import oil price and food security as simultaneous equations model is used rather than classical linear regression model when the error term is correlated with explanatory variable. Again, if the OLS estimator is used in this situation, it will provide biased and inconsistent estimates of the population parameters. The three-stage least squares (3SLS) estimator involves the following three stage procedure. 1. Regress each right-hand side endogenous variable in the equation to be estimated on all exogenous variables in the simultaneous equation model using the OLS estimator. Calculate the fitted values for each of these endogenous variables. 2. In the equation to be estimated, replace each endogenous right-hand side variable by its fitted value variable. Estimate the equation using the OLS estimator. 3. Apply the seemingly unrelated regression (SUR) estimator.

Source of Information: J Bangladesh Agril Univ 16(3): 482–491, 2018 ISSN 1810-3030 (Print) 2408-8684 (Online)

Article Link (Online Journal): https://doi.org/10.3329/jbau.v16i3.39446

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

The history of Bangladesh in the open market is not too long but at present time, the high dependency of the food system on fuel and transport make the agri based economy more vulnerable. Therefore, our study sheds light on oil price volatility and the impact of oil price changes on economic growth and food security in Bangladesh. Although, there is a growing body of literature which focuses on the oil price volatility and the impact of oil price changes on the growth of the economy, but comparatively little is known about the impact of oil price changes on food security, indeed the existing literatures on oil price and food prices mainly point out the interdependencies. To mitigate this gap, the present paper uses relatively innovative approach and yearly data of macroeconomic variables as well as global food security index which focus on Bangladesh.

We use GARCH model to identify the oil price unpredictability. It is evident from the literature that oil price volatility has a negative impact on economic growth and food security. The findings of unit root test and correlogram test reveal that time series international oil price and import oil price are first differenced stationary. The GARCH (2, 1) model asserts that volatility was high in the previous period and it has been continued to be lower in the current period. In addition, the long-run and short-run dynamics of the relationship between economic growth and oil price have been identified by co-integration test and error correction model respectively. There is an evidence of long-run relationship among OP, GCF, LFPR and RGDP. In other words, the result shows an increase in oil price has a negative impact on economic growth in both short and long-run. The three-stage least squares regression model has been applied to show the impact of oil price changes on food security which is followed by Hausman’s specification error test. The findings reveal that an increase in oil price declines the economic growth and food security simultaneously. It is thus palpable that Bangladesh’s economy is vulnerable due to oil price volatility. These results are expected to help the policymakers for sustainable economic development and cope up with the external shocks associated with increasing oil prices.

Knowledge Management: Journal