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Does CPI Granger-Cause WPI? New Extensions from Frequency Domain Approach in Pakistan

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  • Muhammad, Shahbaz
  • Kumar, A.T.K.
  • Mohammad, Iqbal Tahir

Abstract

The present study significantly contributes to the economic literature by investigating the direction of causality between WPI and CPI by applying frequency domain causality approach developed by Lemmens et al. (2008) based on spectral approach. We use monthly frequency data covering the period of 1961-2010 in case of Pakistan. Our results provide evidence of cointegration between the variables. Furthermore, we find unidirectional causal relationship running from CPI to WPI that varies across frequencies i.e., CPI Granger-causes WPI at lower, medium as well as higher level of frequencies reflecting long-run, medium and short-run cycles. This implies that CPI should be a leading indicator for important policy decisions pertaining to monetary or fiscal policies in Pakistan.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 38816.

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Date of creation: 07 May 2012
Date of revision: 14 May 2012
Handle: RePEc:pra:mprapa:38816

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Keywords: WPI; CPI; Frequency Domain Approach;

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References

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  1. 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.
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  3. Schwert, G William, 1989. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 7(2), pages 147-59, April.
  4. Lemmens, Aurélie & Croux, Christophe & Dekimpe, Marnik G., 2008. "Measuring and testing Granger causality over the spectrum: An application to European production expectation surveys," International Journal of Forecasting, Elsevier, vol. 24(3), pages 414-431.
  5. 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.
  6. Hakan Berument & Seyit Mümin Cilasun & Yýlmaz Akdi, 2006. "The Relationship Between Different Price Indices : Evidence from Turkey," Departmental Working Papers, Bilkent University, Department of Economics 0603, Bilkent University, Department of Economics.
  7. Helmut Lütkepohl, 2006. "Structural vector autoregressive analysis for cointegrated variables," AStA Advances in Statistical Analysis, Springer, vol. 90(1), pages 75-88, March.
  8. Stephen G. Cecchetti & Marion Kohler & Christian Upper, 2009. "Financial crises and economic activity," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, Federal Reserve Bank of Kansas City, pages 89-135.
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  12. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
  13. Tiwari, Aviral Kumar, 2012. "An empirical investigation of causality between producers' price and consumers' price indices in Australia in frequency domain," Economic Modelling, Elsevier, vol. 29(5), pages 1571-1578.
  14. Todd E. Clark, 1995. "Do producer prices lead consumer prices?," Economic Review, Federal Reserve Bank of Kansas City, issue Q III, pages 25-39.
  15. Paresh Kumar Narayan, 2005. "The saving and investment nexus for China: evidence from cointegration tests," Applied Economics, Taylor & Francis Journals, vol. 37(17), pages 1979-1990.
  16. Rao, Nasir Hamid & Bukhari, Syed Kalim Hyder, 2010. "Asymmetric Shocks and Co-movement of Price Indices," MPRA Paper 28723, University Library of Munich, Germany.
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Cited by:
  1. Tiwari, Aviral Kumar & Suresh K.G., & Arouri, Mohamed & Teulon, Frédéric, 2014. "Causality between consumer price and producer price: Evidence from Mexico," Economic Modelling, Elsevier, vol. 36(C), pages 432-440.
  2. Tiwari, Aviral Kumar & Oros, Cornel & Albulescu, Claudiu Tiberiu, 2014. "Revisiting the inflation–output gap relationship for France using a wavelet transform approach," Economic Modelling, Elsevier, vol. 37(C), pages 464-475.
  3. Tiwari, Aviral Kumar & Mutascu, Mihai & Andries, Alin Marius, 2013. "Decomposing time-frequency relationship between producer price and consumer price indices in Romania through wavelet analysis," Economic Modelling, Elsevier, vol. 31(C), pages 151-159.

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