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A General Refutation of the Law of One Price as Empirical Hypothesis

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  • Carsten Herrmann-Pillath

    ()
    (Witten/Herdecke University)

Abstract

The Law of One Price (LOP) is of prime importance for modern international economics, in particular in the monetary theory of forward exchange, or in the theory of international trade, as in the analysis of dumping. As a general proposition about arbitrage, the LOP underlies every core proposition in neoclassical trade theory, e.g. the factor price equalization theorem. However, the empirical tests conducted in recent times have not led to conclusive results. There are methodological problems arising from the indeterminacy whether the LOP is a law or an implicit definition, e.g. of the "identity of goods". Paradoxically, progress in econometrics has enlarged the degrees of freedom of interpretation of data. However, this paper argues that the LOP cannot hold in principle, if there are positive costs of inter-regional trade for final goods, and if sunk costs are to be incurred for intra-regional trading. If knowledge about market opportunities has not dispersed completely, sunk costs result from the need to provide locally specific entrepreneurial knowledge as a service input into trading. This knowledge is non-tradable and even non-contractible, so that arbitrage is limited or impossible. Therefore, the LOP can be refuted unless the conditions of perfect general equilibrium are fulfilled. Many empirical observations support this hypothesis, for example as regards "pricing to market".

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Bibliographic Info

Article provided by Justus-Liebig University Giessen, Department of Statistics and Economics in its journal Journal of Economics and Statistics.

Volume (Year): 221 (2001)
Issue (Month): 1 ()
Pages: 45-67

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Handle: RePEc:jns:jbstat:v:221:y:2001:i:1:p:45-67

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Keywords: Arbitrage; law of one price; integration; non-traded goods and services; distributed local knowledge; entrepreneurship;

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Cited by:
  1. Robin Cross & Rolf Färe, 2008. "Farrell efficiency under value and quantity data," Journal of Productivity Analysis, Springer, vol. 29(3), pages 193-199, June.

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