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I. Introduction
In the era of floating exchange rates, the effects of currency appreciations and depreciations on trade flows have been closely studied. One particular topic of interest is the so-called "J-curve" effect, in which a country's trade balance might deteriorate in the short run after a devaluation, before improving in the long run. Because depreciation or devaluation should help increase a country's exports, while making its imports more expensive, it should in theory result in an improvement of the difference between exports and imports. Because of time lags involved in adjusting contracts, however, the quantity of exports or imports is temporarily fixed. If the country is paying in foreign currency, it must give up more units of depreciated currency before the quantity can adjust, so the trade balance might briefly deteriorate. Improvement may come only after passage of some time, hence the J-curve pattern.
This phenomenon has been elaborated upon, and the literature is reviewed in detail by [6] Bahmani-Oskooee and Ratha (2004), who explain how the 1973 breakdown of the Bretton Woods system of fixed exchange rates has led to large currency fluctuations that have at times benefited some countries' competitive positions. The authors discuss the relevant theoretical and empirical issues in the literature over the previous decades, including the modeling and econometric techniques that are designed to capture the short-run effects of devaluation - the J-curve - as well as its long-run effects. They find that various models, utilizing aggregate and bilateral data, arrive at ambiguous results. They suggest methods that might help resolve this ambiguity.
Since the publication of [6] Bahmani-Oskooee and Ratha (2004), a large body of empirical literature has arisen, testing the "J-curve hypothesis" for a large number of countries. Not only has this list of nations studied grown in the last half decade, but three main improvements have been made to the empirical methodologies. First, advances in cointegration techniques have continued to be applied, often improving upon earlier results. Second, the use of data that are disaggregated by individual industry has helped to uncover evidence of effects that were obscured by the use of more aggregated data. Finally, this method of analysis has been extended into a new domain of study: the "S-curve," in which correlations between the...