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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)

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    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.

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    Bibliographic Info

    Article provided by IGI Global in its journal International Journal of Asian Business and Information Management (IJABIM).

    Volume (Year): 2 (2011)
    Issue (Month): 2 (April)
    Pages: 64-73

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    Handle: RePEc:igg:jabim0:v:2:y:2011:i:2:p:64-73

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    Web page: http://www.igi-global.com

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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.

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