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Inflation regimes, core inflation measures and the relationship between producer and consumer price inflation

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  • Willie Belton
  • Usha Nair-Reichert

Abstract

To date, an overwhelming majority of the literature has addressed mean relationships between producer and consumer price inflation. Granger et al. (1986) represent the only attempt to investigate second moment relationships. We examine the consumer--producer price relationship employing a multivariate GARCH-M framework that allows simultaneous estimation of the bivariate system along with providing explicit times series estimates of the variances of consumer and producer price inflation. This research also breaks new ground in the use of core and over-all inflation variance measures as well as examining state dependent mean and variance relationships. We find that mean relationships are generally sensitive to the measure of inflation used. Food and energy prices play an important role in transmitting changes in aggregate input prices to aggregate output prices. When food and energy prices are eliminated from consumer and producer price inflation measures, mean relationships break down irrespective of whether the economy is experiencing a high or low inflation regime. Variance relationships appear to be more robust in general and input price relationships in particular appear to respond to inflation regime shifts.

Suggested Citation

  • Willie Belton & Usha Nair-Reichert, 2007. "Inflation regimes, core inflation measures and the relationship between producer and consumer price inflation," Applied Economics, Taylor & Francis Journals, vol. 39(10), pages 1295-1305.
  • Handle: RePEc:taf:applec:v:39:y:2007:i:10:p:1295-1305
    DOI: 10.1080/00036840500447682
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    References listed on IDEAS

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    1. Awudu Abdulai, 2002. "Using threshold cointegration to estimate asymmetric price transmission in the Swiss pork market," Applied Economics, Taylor & Francis Journals, vol. 34(6), pages 679-687.
    2. Lombra, Raymond E. & Mehra, Yash P., 1983. "Aggregate demand, food prices, and the underlying rate of inflation," Journal of Macroeconomics, Elsevier, vol. 5(4), pages 383-398.
    3. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    4. McGarvey, Mary G, 1985. "U.S. Evidence on Linear Feedback from Money Growth Shocks to Relative Price Changes, 1954 to 1979," The Review of Economics and Statistics, MIT Press, vol. 67(4), pages 675-680, November.
    5. 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.
    6. Hilde Christiane Bjørnland, 2001. "Identifying domestic and imported core inflation," Applied Economics, Taylor & Francis Journals, vol. 33(14), pages 1819-1831.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    9. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    11. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
    12. Richard Tiffin & P. J. Dawson, 2000. "Structural breaks, cointegration and the farm-retail price spread for lamb," Applied Economics, Taylor & Francis Journals, vol. 32(10), pages 1281-1286.
    13. Grier, Kevin B. & Perry, Mark J., 1996. "Inflation, inflation uncertainty, and relative price dispersion: Evidence from bivariate GARCH-M models," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 391-405, October.
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    Cited by:

    1. Zerihun Gudeta Alemu, 2012. "Causality links between consumer and producer price inflation in South Africa," Applied Economics Letters, Taylor & Francis Journals, vol. 19(1), pages 13-18, January.
    2. Kwon, Dae-Heum & Koo, Won W., 2013. "Price Transmission Mechanism among Disaggregated Processing Stages of Food: Demand-Pull or Cost-Push?," Journal of Rural Development/Nongchon-Gyeongje, Korea Rural Economic Institute, vol. 35(5), pages 1-17, January.

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