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Modelling the Relationship between Whole Sale Price and Consumer Price Indices: Cointegration and Causality Analysis for India

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  • Tiwari, Aviral
  • Shahbaz, Muhammad

Abstract

In this study we attempted to analyze the static and dynamic causality between producers’ prices measured by WPI and consumers’ prices measured by CPI in the context of India. We did our analysis in the framework of time series and for analysis, we applied ARDL bounds testing approach to cointegration and robustness of ARDL approach is examined through Johansen and Juselius (1990) maximum likelihood approach over the period of 1950-2009. We found the evidence of bidirectional causality between WPI and CPI in both cases i.e., in the short-run and long-run. Furthermore, outside sample forecast analysis reveals that in India, WPI leads CPI. This implies that WPI is determined by market forces and also a leading indicator of consumers’ prices and inflation. This gives an indication to the Indian policy analysts to control for factors affecting WPI in order to have control on CPI since CPI is used for indexation purposes for many wage and salary earners including government employees and hence it will be helpful in cutting down the excess government expenditure.

Suggested Citation

  • Tiwari, Aviral & Shahbaz, Muhammad, 2010. "Modelling the Relationship between Whole Sale Price and Consumer Price Indices: Cointegration and Causality Analysis for India," MPRA Paper 27333, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:27333
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    References listed on IDEAS

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    1. Johansen, Soren, 1992. "Determination of Cointegration Rank in the Presence of a Linear Trend," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 383-397, August.
    2. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    3. Colclough, William G. & Lange, Mark D., 1982. "Empirical evidence of causality from consumer to wholesale prices," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 379-384, August.
    4. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    5. Perron, Pierre & Rodriguez, Gabriel, 2003. "GLS detrending, efficient unit root tests and structural change," Journal of Econometrics, Elsevier, vol. 115(1), pages 1-27, July.
    6. repec:wsi:serxxx:v:55:y:2010:i:03:n:s0217590810003882 is not listed on IDEAS
    7. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    8. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    9. Todd E. Clark, 1995. "Do producer prices lead consumer prices?," Economic Review, Federal Reserve Bank of Kansas City, issue Q III, pages 25-39.
    10. José Julián Sidaoui & Carlos Capistrán & Daniel Chiquiar & Manuel Ramos Francia, 2009. "A Note on the Predictive Content of PPI over CPI Inflation: The Case of Mexico," Working Papers 2009-14, Banco de México.
    11. Perron, Pierre & Rodriguez, Gabriel, 2003. "GLS detrending, efficient unit root tests and structural change," Journal of Econometrics, Elsevier, vol. 115(1), pages 1-27, July.
    12. Guglielmo Maria Caporale & Margarita Katsimi & Nikitas Pittis, 2002. "Causality Links between Consumer and Producer Prices: Some Empirical Evidence," Southern Economic Journal, Southern Economic Association, vol. 68(3), pages 703-711, January.
    13. PareshKumar Narayan, 2004. "Are Output Fluctuations Transitory? New Evidence From 24 Chinese Provinces," Pacific Economic Review, Wiley Blackwell, vol. 9(4), pages 327-336, December.
    14. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    15. S. Narayan, 2009. "India," Chapters,in: The Political Economy of Trade Reform in Emerging Markets, chapter 7 Edward Elgar Publishing.
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    Cited by:

    1. Phouphet Kyophilavong & Muhammad Shahbaz & Gazi Salah Uddin, 2015. "A Note on Nominal and Real Devaluation in Laos," Global Business Review, International Management Institute, vol. 16(2), pages 236-243, April.
    2. Amjad Ali & Nooreen Mujahid & Yahya Rashid & Muhammad Shahbaz, 2015. "Human Capital Outflow and Economic Misery: Fresh Evidence for Pakistan," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(3), pages 747-764, December.
    3. Wang, Minggang & Tian, Lixin & Xu, Hua & Li, Weiyu & Du, Ruijin & Dong, Gaogao & Wang, Jie & Gu, Jiani, 2017. "Systemic risk and spatiotemporal dynamics of the consumer market of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 188-204.
    4. Mujahid, Noureen & Muhammad Shahbaz, Shabbir & Shahbaz, Muhammad, 2014. "Labor Market Conditions-Female Labor Supply Nexus: The Role of Globalization in Pakistan," MPRA Paper 57179, University Library of Munich, Germany, revised 07 Jul 2014.
    5. repec:ipg:wpaper:2014-584 is not listed on IDEAS

    More about this item

    Keywords

    CPI and WPI; Granger causality; cointegration VDs; IRFs.;

    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

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