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Temporal aggregation of an ESTAR process: some implications for purchasing power parity adjustment

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  • David A. Peel

    (Lancaster University Management School, Lancaster LA1 4YX, UK)

  • Ivan Paya

    (Departamento Fundamento Analisis Economico, University of Alicante, 03080 Alicante, Spain)

Abstract

Nonlinear models of deviations from PPP have recently provided an important, theoretically well motivated, contribution to the PPP puzzle. Most of these studies use temporally aggregated data to empirically estimate the nonlinear models. As noted by Taylor (2001), if the true DGP is nonlinear, the temporally aggregated data could exhibit misleading properties regarding the adjustment speeds. We examine the effects of different levels of temporal aggregation on estimates of ESTAR models of real exchange rates. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • David A. Peel & Ivan Paya, 2006. "Temporal aggregation of an ESTAR process: some implications for purchasing power parity adjustment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 655-668.
  • Handle: RePEc:jae:japmet:v:21:y:2006:i:5:p:655-668
    DOI: 10.1002/jae.860
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    Cited by:

    1. I Paya & D Peel, 2005. "Temporal aggregation of an ESTAR process," Working Papers 565938, Lancaster University Management School, Economics Department.
    2. Ivan Paya & David A. Peel, 2004. "Nonlinear Ppp Under The Gold Standard," Working Papers. Serie AD 2004-24, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    3. Ivan Paya & David Peel, 2005. "The process followed by PPP data. On the properties of linearity tests," Applied Economics, Taylor & Francis Journals, vol. 37(21), pages 2515-2522.
    4. Yamin Ahmad & Ivan Paya, 2014. "Temporal Aggregation of Random Walk Processes and Implications for Asset Prices," Working Papers 14-01, UW-Whitewater, Department of Economics.
    5. Ivan Paya & David A. Peel, 2006. "Temporal aggregation of an ESTAR process: some implications for purchasing power parity adjustment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 655-668, July.
    6. Boutahar, Mohamed & Mootamri, Imène & Péguin-Feissolle, Anne, 2009. "A fractionally integrated exponential STAR model applied to the US real effective exchange rate," Economic Modelling, Elsevier, vol. 26(2), pages 335-341, March.
    7. Ivan Paya & David A. Peel, 2011. "Systematic sampling of nonlinear models: Evidence on speed of adjustment in index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(2), pages 192-203, February.
    8. Pavlidis, Efthymios G. & Paya, Ivan & Peel, David A., 2011. "Real exchange rates and time-varying trade costs," Journal of International Money and Finance, Elsevier, vol. 30(6), pages 1157-1179, October.
    9. Juvenal Luciana & Taylor Mark P., 2008. "Threshold Adjustment of Deviations from the Law of One Price," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-46, September.
    10. Yamin Ahmad & Stuart Glosser, 2011. "Searching for nonlinearities in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1829-1845.
    11. Derek Stimel, 2010. "Choice of Aggregate Demand Proxy and its Affect on Phillips Curve Nonlinearity: U.S. Evidence," Economics Bulletin, AccessEcon, vol. 30(1), pages 543-557.
    12. repec:ebl:ecbull:v:30:y:2010:i:1:p:543-557 is not listed on IDEAS
    13. Ivan Paya & David A. Peel, 2005. "A New Analysis Of The Determinants Of The Real Dollar-Sterling Exchange Rate: 1871-1994," Working Papers. Serie AD 2005-16, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    14. Ahmad Yamin S & Paya Ivan, 2020. "Temporal aggregation of random walk processes and implications for economic analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-20, April.
    15. Mohamed Boutahar & Imene Mootamri & Anne Peguin-Feissolle, 2007. "An exponential FISTAR model applied to the US real effective exchange rate," Working Papers halshs-00353836, HAL.

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    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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