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Determinants and Forecast of Price Level in India: a VAR Framework

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  • Cindrella Shah
  • Nilesh Ghonasgi

Abstract

The theoretical association of money supply and exchange rates with prices has been empirically established and shown to be dominant in explaining changes in price levels in India. However, post liberalisation, studies have shown price levels to be impacted by several other factors as also, weakened influence of the traditional factors established by theories. This study aims to find the determinants of price level for the period 1994–2008 using a Vector Autoregression model and test the predictive ability of the model. Our results show shorter and smaller impact of change in money supply and nominal effective exchange rate on price levels. Both money supply and nominal effective exchange rates are found to Granger-cause Consumer Price Index. But, impulse response functions show that the impact of shocks from money supply and nominal effective exchange rates on consumer prices peaks after two lags and is short-lived. Forecast error variance decomposition shows that these demand side factors contribute only 6 % of the forecast error variation in Consumer Price Index.

Suggested Citation

  • Cindrella Shah & Nilesh Ghonasgi, 2016. "Determinants and Forecast of Price Level in India: a VAR Framework," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 57-86, June.
    • Handle: RePEc:spr:jqecon:v:14:y:2016:i:1:d:10.1007_s40953-015-0019-y
    DOI: 10.1007/s40953-015-0019-y
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    References listed on IDEAS

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    1. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    2. repec:zbw:bofitp:2008_002 is not listed on IDEAS
    3. N. Kundan Kishor, 2012. "Modeling Inflation In India: The Role Of Money," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 57(04), pages 1-19.
    4. Partha Ray & Jorge Somnath Chatterjee, 2001. "The role of asset prices in Indian inflation in recent years: some conjectures," BIS Papers chapters, in: Bank for International Settlements (ed.), Modelling aspects of the inflation process and the monetary transmission mechanism in emerging market countries, volume 8, pages 131-150, Bank for International Settlements.
    5. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian VAR Models for Forecasting Irish Inflation," MPRA Paper 11360, University Library of Munich, Germany.
    6. Michael Debabrata Patra & Partha Ray, 2010. "Inflation Expectations and Monetary Policy in India: An Empirical Exploration," IMF Working Papers 2010/084, International Monetary Fund.
    7. Ankita Mishra & Vinod Mishra, 2010. "A VAR Model of Monetary Policy and Hypothetical Case of Inflation Targeting in India," Monash Economics Working Papers 15-10, Monash University, Department of Economics.
    8. P., Srinivasan & M., Kalaivani, 2013. "On the Temporal Causal Relationship between Macroeconomic Variables: Empirical Evidence from India," MPRA Paper 46803, University Library of Munich, Germany.
    9. Anuradha Patnaik, 2010. "Study of Inflation in India: A Cointegrated Vector Autoregression Approach," Journal of Quantitative Economics, The Indian Econometric Society, vol. 8(1), pages 118-129, January.
    10. Mr. Tim Callen & Dongkoo Chang, 1999. "Modeling and Forecasting Inflation in India," IMF Working Papers 1999/119, International Monetary Fund.
    11. Anca Tanasie & Cosmin Fratostiteanu, 2008. "Forecasting inflation and its determinants," Revista Tinerilor Economisti (The Young Economists Journal), University of Craiova, Faculty of Economics and Business Administration, vol. 1(10), pages 110-116, April.
    12. Caesar Lack, 2006. "Forecasting Swiss inflation using VAR models," Economic Studies 2006-02, Swiss National Bank.
    13. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    14. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    15. Pankaj SINHA & Sushant GUPTA & Nakul RANDEV, 2011. "Modeling & Forecasting Of Macro-Economic Variables Of India: Before, During & After Recession," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 6(1(15)/ Sp), pages 43-60.
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    3. Ciarreta, Aitor & Martinez, Blanca & Nasirov, Shahriyar, 2023. "Forecasting electricity prices using bid data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1253-1271.

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    More about this item

    Keywords

    Forecasting; Inflation; VAR;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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