Short Run Forecast of Inflation Rate in India

Abstract

In this study, annual Wholesale Price Index (WPI) data for India from 2002 to 2022 are modelled and forecast using a univariate Autoregressive Integrated Moving Average (ARIMA) homoscedastic model in conjunction with the Box and Jenkins modelling procedure. The Reserve Bank of India provided the annual Wholesale Price Index data as secondary data from 2002 to 2022. We utilise the ACF, PACF, and Augmented Dickey Fuller (ADF) unit root tests to analyse the series' unit root and stationarity properties. The findings demonstrate that the Indian WPI data is non-stationary at the level but stationary at the first difference, making it an integrated function of order one, or I(1). After using the Box-Jenkins modelling approach to find the best model, we discovered that ARIMA (1, 1, 0) best described the WPI data series in India. The model was examined and found to be suitable and effective. We projected the future annual WPI in India for a period of 20 years, from 2002 to 2022, using this model. The predictions indicate that India's annual WPI values will continue to rise. The study asserts that India's inflation will rise beginning in 2023–24 because the forecast's confidence intervals indicate a steady rise in the annual WPI from 2023-24 to 2029–30.