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Analyzing Core Inflation in India: A Structural VAR Approach

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  • Ashima Goyal
  • Ayan Kumar Pujari

Abstract

Effective inflation targeting requires careful selection of inflation target. It is necessary to leave out noisy elements, which the monetary policy cannot control. However, this exclusion should not be done in an ad hoc basis. Rather, core inflation should be determined from the structure of the economy. This paper estimates core inflation for India, using Structural Vector Autoregression (SVAR) method. This method is based on both theory and the structure of the economy. Monthly data for Wholesale Price Index (WPI) and Index of Industrial Production (IIP) has been used, covering a long time span from January 1971 to July 2004. We analyze the impulse responses of inflation and output, test for several time series properties of core inflation and carry out a number of Granger causality tests between headline inflation, core inflation, output and a monetary aggregate.

Suggested Citation

  • Ashima Goyal & Ayan Kumar Pujari, 2005. "Analyzing Core Inflation in India: A Structural VAR Approach," The IUP Journal of Monetary Economics, IUP Publications, vol. 0(2), pages 76-90, May.
    • Handle: RePEc:icf:icfjmo:v:03:y:2005:i:2:p:76-90
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    References listed on IDEAS

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    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Marianne Nessén & Ulf Söderström, 2001. "Core Inflation and Monetary Policy," International Finance, Wiley Blackwell, vol. 4(3), pages 401-439.
    3. Michael F. Bryan & Stephen G. Cecchetti, 1994. "Measuring Core Inflation," NBER Chapters, in: Monetary Policy, pages 195-219, National Bureau of Economic Research, Inc.
    4. repec:bla:intfin:v:4:y:2001:i:3:p:401-39 is not listed on IDEAS
    5. Quah, Danny, 1995. "Misinterpreting the dynamic effects of aggregate demand and supply disturbances," Economics Letters, Elsevier, vol. 49(3), pages 247-250, September.
    6. Hilde Christiane Bjørnland, 2001. "Identifying domestic and imported core inflation," Applied Economics, Taylor & Francis Journals, vol. 33(14), pages 1819-1831.
    7. Freeman, Donald G., 1998. "Do core inflation measures help forecast inflation?," Economics Letters, Elsevier, vol. 58(2), pages 143-147, February.
    8. Michael F. Bryan & Stephen G. Cecchetti, 1999. "The Monthly Measurement of Core Inflation in Japan," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 17(1), pages 77-101, May.
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    Cited by:

    1. Ashima Goyal & Arjun Singh, 2007. "Through a Glass Darkly," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 1(2), pages 139-166, April.
    2. Sujata Kar, 2010. "A Periodic Autoregressive Model of Indian WPI Inflation," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 4(3), pages 279-292, August.
    3. Ashima Goyal & Arjun Singh, 2006. "Through a Glass Darkly - Deciphering the Impact of Oil Price Shocks," Macroeconomics Working Papers 22374, East Asian Bureau of Economic Research.
    4. Pami Dua & Upasna Gaur, 2010. "Determination of inflation in an open economy Phillips curve framework: the case of developed and developing Asian countries," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 3(1), pages 33-51.

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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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