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Nonlinear Trend and Purchasing Power Parity

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  • Yinghao LUO

    (Dushiwangjing, China)

Abstract

After the collapse of the Bretton Woods system, the evidence on the purchasing power parity (PPP) in the long run is still a matter of debate. The difficulties of the problem are the possible nonstationarity of relative price indices and nominal exchange rates. The traditional ways to deal with nonstationarity such as unit root model and cointegration have some problems. In this paper, to deal with nonstationarity, we apply the Hodrick-Prescott (HP) trend-cycle filter in real business cycle literature (Hodrick and Prescott, 1981) which can give a nonlinear smooth-trend, and we find that after the 1970s float, the monthly HP trends of US dollar/UK sterling and Deutsche marks/US dollar have certain relevance with their corresponding HP trends of relative consumer price indices. This result indicates that there is no strong evidence to directly deny that the PPP is valid in the long run. In this sense, it is not reliable to directly deny the belief of monetary neutrality.

Suggested Citation

  • Yinghao LUO, 2016. "Nonlinear Trend and Purchasing Power Parity," Journal of Economics Bibliography, KSP Journals, vol. 3(3), pages 490-497, September.
    • Handle: RePEc:ksp:journ6:v:3:y:2016:i:3:p:490-497
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    References listed on IDEAS

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    Cited by:

    1. Yinghao LUO, 2017. "Communism, Value Neutrality And Monetary Neutrality," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 8(2), pages 149-152.

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    More about this item

    Keywords

    HP filter; Purchasing power parity; Monetary neutrality;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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