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Why Did the Sign of the Price-Output Correlation Change? Evidence from a Structural VAR with GARCH Errors

Author

Listed:
  • James Peery Cover

    (Department of Economics, Finance & Legal Studies, University of Alabama)

  • C. James Hueng

    (Department of Economics, Western Michigan University)

Abstract

It is generally agreed that the price-output correlation in the United States was positive prior to the Second World War, but became negative during the postwar period (at least by 1972). This paper offers evidence that the price-output correlation changed signs because of a decrease in the variability of aggregate demand. A structural VAR with bivariate GARCH (1,1) errors is used to estimate a times series of price-output correlations as well as of the conditional variances of the structural shocks to AD and AS. It is found that during the postwar period the price-output correlation is negative and significantly different from zero only when the standard deviation of the AD shock is less than that of the AS shock.

Suggested Citation

  • James Peery Cover & C. James Hueng, 2006. "Why Did the Sign of the Price-Output Correlation Change? Evidence from a Structural VAR with GARCH Errors," Working Papers 200602, Ball State University, Department of Economics, revised Mar 2006.
    • Handle: RePEc:bsu:wpaper:200602
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    References listed on IDEAS

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    Cited by:

    1. Mauro Gallegati & Antonio Palestrini & Milena Petrini, 2008. "Cyclical Behavior Of Prices In The G7 Countries Through Wavelet Analysis," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 119-130.

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    More about this item

    Keywords

    Price-Output Correlation; Structural VAR; Supply and Demand Shocks; Blanchard-Quah Decomposition;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • 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

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