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)| false Meese, Richard A., and Kenneth Rogoff, 1984, “ The Out–of–Sample Failure of Empirical Exchange Rate Models: Sampling Error or Misspecification?” Exchange Rates and International Macroeconomics, ed.by ( Jacob A. Frenkel Chicago: University of Chicago Press), pp. 67- 109.
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The authors are grateful to Ranil Salgado for helpful comments and to Jeff Gable and Susanna Mursula for research assistance.
See Table 2 in Mussa et al. (1994), which shows that the standard deviation of month–to–month changes in the real exchange rate between the U.S. dollar, the yen and the deutsche mark since 1973 has risen over threefold, from under 1 percent per annum prior to 1992 to over 3 percent subsequently.
See Meese and Rogoff (1983) and (1984), and Frankel and Rose (1995). However, it should be noted that there is now growing evidence that over longer time periods nominal and real exchange rates display a systematic relationship to fundamental economic variables. This evidence relates both to the long–run PPP, which has recently been surveyed by MacDonald (1995) and Rogoff (1996), and to changes in the real exchange rate, which has been analyzed in several papers in Williamson (1994) and by Faruqee (1995) and Stein et al. (1995). See also Mark (1995).
For a recent and comprehensive discussion and analysis of recent international currency experience, see Obstfeld (1995).
Much of the empirical evidence on departures from one price across countries has drawn from the experience of the United States in the 1980s and focused on the behavior of U.S. import prices during the period of massive U.S. dollar appreciation and subsequent depreciation. For example, Krugman (1987) finds that more than 30 percent of the real appreciation of the dollar between 1980 and 1984 was reflected in the divergence between prices of U.S. imports and the dollar prices of the same goods in other markets. See also Dornbusch (1987) and Hooper and Mann (1987) for an analysis of import prices during this episode. Goldberg and Knetter (1997) provide a useful survey of the literature on the relationship between exchange rates and prices of traded goods.
Recent empirical evidence documenting the degree of cross–sectional variation in pricing–to–market behavior across industries is reported by Knetter (1992). Examining various export prices for Germany, Japan, the United Kingdom, and the United States, Knetter (1992) finds that industry is the critical dimension explaining the variation in the pattern of pricing–to–market practices within and across countries. Much of this variation can be explained by trade pattern differences.
An important distinction is implicitly made here between supply–side considerations leading to shifts in marginal costs curves and pricing–to–market factors which are associated with movements along marginal cost curves.
Krugman (1984) finds that most countries invoice exports in terms of domestic currency when relative country-size differences are not significant. LDC exports, which are predominantly invoiced in U.S. dollars, are an exception.
Based on taste and technology parameters, the coefficients in Table 1 are given by:
where α is the exact expenditure share on home goods.
If costs were the same, producers would always choose the same price for each market. Constant differential markups could of course be introduced into this CES framework by assuming differential elasticities of substitution across markets (ϵ1 ≠ ϵ2). In that case, there would exist a constant price differential across markets.
Typically, with differential markups, demand is less convex than the constant elasticity case. See, for example, Marston (1990).
See also Krugman (1987). For a broad review of various explanations for pricing to market, see Knetter (1992).
The model in this paper assumes that prices change continuously in response to variations in the exchange rate. For an analysis that provides a rationale for sticky prices in the face of exchange rate fluctuations, see Delgado (1991), which develops a model where destination prices change only when the expected revenue is large enough to take account of menu costs and the possibility of a reversal of the exchange rate.
The analysis proceeds on the assumption that home goods prices in the home market remain unchanged in terms of home currency (full exchange rate pass–through). This would be an equilibrium response if the (separable) costs for the home good lacked the convexity assumed in the production of the export good. Otherwise, it serves an approximation to the general equilibrium case. See Faruqee (1995) for further analysis regarding general equilibrium dynamics.
In general equilibrium, identical producers in the industry choose the same export price:
In the absence of a CPI effect, the degree of pass-through —reflecting only production–side incentives—is given by
Viewing equation (1) as an optimal response function, and using its foreign counterpart, one can show that the pass–through response of prices for the home and foreign export industry are downward–sloping (monotonic declining) functions of the degree of pass–through in the other country and must cross in R2:[0, 1]x[0, 1]. The intersection of the home reaction function with the foreign one represents the Nash equilibrium outcome.
See Faruqee (1995) for analysis of pass–through in both local and export prices, and the corresponding degree of pricing to market. There it is shown that pass-through in local prices under interindustry trade is less than (but close to) one, and greater than the degree of pass-through in export prices.
As with pass–through in levels, limited variance pass–through by itself is not, in general, a segmentation. However, with a high degree of variance pass–through in local prices (we assume full variance pass–through), the variance of home prices in the home market in terms of foreign currency should be well approximated by the variance of currency fluctuations, ceteris paribus. In that case, incomplete variance pass–through, i.e., variance ratio less than unity, in export prices would indeed reflect the effects of pricing to market.
A variable X is log–normal if x = ln X is normally distributed. Assuming
The risk premium is also increasing in the degree of openness (smaller α), as the volatility of CPI fluctuations resulting from exchange rate variability increases. Note that if costs are linear (γ=l) and the domestic economy is closed to imports (α=l) then exchange rate variability does not matter (risk premium=0).
The change in variance used in Figure 4 is:
The reduced–form parameter “a” which measures the sensitivity of export prices to exchange rates, can be shown in the model to be between 0 and 1, depending on the degree of openness, α, and the degree of convexity, γ: a = 1 − α/γ.
For a description of the methodology used to construct these series, see Chapter 15, “International Price Indexes,” Bureau of Labor Statistics Handbook of Methods, U.S. Department of Labor, Bulletin 24 - 90, April 1997, U.S. Government Printing Office. The authors are indebted to William Alterman, Supervisory Economist, Division of International Prices, Office of Prices and Living Conditions, Bureau of Labor Statistics, for making these data available to them.