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Purchasing Power Parity and the Law of One Price: Evidence from Commodity Prices in Asian Countries

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  • Mohsen Bahmani-Oskooee

    (The Center for Research on International Economics and Department of Economics, University of Wisconsin – Milwaukee, Milwaukee, WI 53201, USA)

  • ABM Nasir

    (School of Business, North Carolina Central University, Durham, NC 27707, USA)

Abstract

Almost all previous studies that have tested the law of one price or Purchasing Power Parity theory (PPP) have used either real effective exchange rates or bilateral real exchange rates which are constructed using CPI or PPI data. Most of these studies have failed to support the PPP mostly due to aggregation bias. A few recent studies, have, therefore used commodity prices in different countries and have provided strong support for the theory. These studies have mostly used data from industrial countries. In this paper, we use individual prices of 52 retail items from 15 cities in Asia and test for stationarity of the real exchange rate and speed of adjustment. We provide support for PPP in 63% of the cases. We also find that using individual prices lead to faster convergence of real rates toward their PPP values.

Suggested Citation

  • Mohsen Bahmani-Oskooee & ABM Nasir, 2015. "Purchasing Power Parity and the Law of One Price: Evidence from Commodity Prices in Asian Countries," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., vol. 15(2), pages 231-240, July.
  • Handle: RePEc:wsi:gejxxx:v:15:y:2015:i:02:n:gej-2014-0051
    DOI: 10.1515/GEJ-2014-0051
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    More about this item

    Keywords

    PPP; commodity prices; Asian countries;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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