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Forecasting Inflation in India: An Application of ANN Model

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  • Rudra P. Pradhan

    (Indian Institute of Technology Kharagpur, India)

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.

Suggested Citation

  • Rudra P. Pradhan, 2011. "Forecasting Inflation in India: An Application of ANN Model," International Journal of Asian Business and Information Management (IJABIM), IGI Global, vol. 2(2), pages 64-73, April.
    • Handle: RePEc:igg:jabim0:v:2:y:2011:i:2:p:64-73
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    Cited by:

    1. Haroon Mumtaz & Nitin Kumar, 2012. "An application of data-rich environment for policy analysis of the Indian economy," Joint Research Papers 2, Centre for Central Banking Studies, Bank of England.
    2. Pijush Kanti Das & Prabir Kumar Das, 2024. "Forecasting and Analyzing Predictors of Inflation Rate: Using Machine Learning Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 22(2), pages 493-517, June.

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