Several academic scholars prove that there is a negative relationship between the energy plus commodity price and Gross Domestic product (GDP). The last decade’s energy efficiency policies and tendency to go greener across the world have reduced the oil consumption. Therefore, the investigation of probable impacts of current oil shocks in short run GDP growth across the countries has been chosen for the research . The volume along with the product composition of a nation’s commodity trade uses to determine the country’s vulnerability to the volatility of the commodity price. The key challenge for the nation is to deal with two probably offsetting forces. During the short run, the positive effects of trade shocks will always lift up the GDP, and the practical issue is to measure the impact on the GDP .
In order to analyze the data, the linear regression paradigm by Mark and Olsen (1994) has been chosen for this research study because paradigm provides great emphasis on the bivariate correlation between the GDP growth and commodity price. Additionally, it recommends setting up many lags as usually, an oil shock does not have any immediate effect. The data for the regression has been collected from the statistics of several developing and developed country.
The data analyses improve the acceptability of the research study and improve the value of the research. For this particular research, the data has been collected from the statistics of different countries. After data collection, the linear regression model has been applied to analyze the data as it put great emphasis on identifying the relationship between the variable: commodity price volatility and GDP growth.