Study of The Indian Energy Consumption in Context to the GDP Growth: Using ARIMA and Factor Analysis

This research study developed an understanding that there is a converse relationship between GDP growth and energy consumption. Through this study, the authors represented the discussion from an international point of view, then narrowed it to Asia, and finally to the centres in India using the data from secondary sources. The energy consumption data were collected from official sources like government agencies between 1990 and 2019 to maintain authenticity. The authors used two different mathematical approaches to derive the qualitative and quantitative results. The first one was ARIMA (p,d,q), based on the Box-Jenkins methodology. RMSE, AIC, normalized BIC criteria, significance level, R2, etc. were used to identify the best forecasting model. The results show that the four ARIMA models were identical but as per the findings from ARIMA (2,3,8) model was the best forecasting model to predict the Indian GDP growth. The second one was to understand the characteristics of the eight variables, where the factor redemption technique was applied with the help of PCA and the Varimax rotation method. The KMO and Bartlett’s tests were applied for the measurement of sampling adequacy and sphericity as two different approaches. In this research work, authors studied the different parameters like AIC, Normalized BIC method, RMSE, MSE, t-test, and significance level method to find out the best suitable ARIMA model for the Indian GDP growth.