Cyclical and seasonal patterns of India’s GDP growth rate through the eyes of Hamilton and Hodrick Prescott Filter models

Abstract

The paper endeavours to analyse the cyclical fluctuation, seasonal movement and trends of Indian GDP growth rate by applying both Hodrick-Prescott filter and Hamilton filter models taking St.Louisfred quarterly data from 2011Q4 to 2019Q4.The paper concludes that the seasonal adjustment and actual GDP growth rate of India have been merged with each other and they are identical in both the models. But the cyclical trend in H.P.Filter showed one upward humped but Hamilton filter showed cyclical fluctuations with two peaks and troughs and the seasonal variations are v shaped and highly volatile. Hamilton seasonal variations have been verified by applying residual test of correlogram which explained that autocorrelation and partial autocorrelation functions moved around both the sides significantly. Hamilton regression filter model is extended to forecasting ARIMA (1,0,0) model for 2030 which confirmed stationarity and stability. Even, the final trend cycle of GDP growth rate of India converges towards stationary process for 2025. Countercyclical fiscal and monetary policy including financial management strategies have been incorporated.