Investigating the Predictive Power of Google Trend and Real Price Indexes in Forecasting the Inflation Volatility

Abstract

The goal of this study is to examine the predictive power of real price indexes and Google Trend in forecasting the inflation volatility in three nations (the USA, Japan, and the UK). The AIC, BIC, and RMSE are used to select the best GARCH-type models with the most appropriate predictors. The overall result shows that the GARCH model with the skew-student distribution is the most effective model in capturing the inflation volatility. Furthermore, this study reveals that the commodity price index is the strongest predictor variable of the inflation volatility. We also find that the financial crisis and health crisis decisively affect the inflation volatility in the United States of America and Japan.