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Examining world-wide purchasing power parity

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  • Tor Jacobson

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  • Marianne Nessén

    ()

Abstract

We examine long-run PPP between Germany, Great Britain, Japan and the United States over the period 1930–1996 using multivariate cointegration techniques. Bilateral PPP between the four countries is examined in one system (as opposed to e.g. series of trivariate systems). In all of the statistical analysis, asymptotic tests are augmented by parametric bootstrap analogues, whereby we reduce, if not eliminate, the size distortion typically present in small-sample studies. The cointegration analysis provides support for the necessary conditions for PPP (i.e. cointegrating relations are found) but not for the sufficient conditions (i.e., the coefficients in the cointegrating relations are far from what PPP predicts). These results are at odds with results from other studies that also analyze long-horizon data sets. Copyright Springer-Verlag 2004

Suggested Citation

  • Tor Jacobson & Marianne Nessén, 2004. "Examining world-wide purchasing power parity," Empirical Economics, Springer, vol. 29(3), pages 463-476, September.
  • Handle: RePEc:spr:empeco:v:29:y:2004:i:3:p:463-476
    DOI: 10.1007/s00181-003-0176-2
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    File URL: http://hdl.handle.net/10.1007/s00181-003-0176-2
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    Citations

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    Cited by:

    1. Miguel Carvalho & Paulo Júlio, 2012. "Digging out the PPP hypothesis: an integrated empirical coverage," Empirical Economics, Springer, vol. 42(3), pages 713-744, June.

    More about this item

    Keywords

    Long-run purchasing power parity; multivariate cointegration analysis; bootstrap inference; F30; C15; C32;

    JEL classification:

    • F30 - International Economics - - International Finance - - - General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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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