Forecasting Inflation in India: An Application of ANN Model

Rudra P. Pradhan
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Rudra P. Pradhan: Indian Institute of Technology Kharagpur, India

International Journal of Asian Business and Information Management (IJABIM), 2011, vol. 2, issue 2, 64-73

Abstract: This paper presents an application of Artificial Neural Network (ANN) to forecast inflation in India during the period 1994-2009. The study presents four different ANN models on the basis of inflation (WPI), economic growth (IIP), and money supply (MS). The first model is a univariate model based on past WPI only. The other three are multivariate models based on WPI and IIP, WPI and MS, WPI, and IIP and MS. In each case, the forecasting performance is measured by mean squared errors and mean absolute deviations. The paper finally concludes that multivariate models show better forecasting performance over the univariate model. In particular, the multivariate ANN model using WPI, IIP, and MS resulted in better performance than the rest of other models to forecast inflation in India.

Date: 2011
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