Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This paper sheds new light on the role of inflation regime in explaining the extent of exchange rate pass-through (ERPT) into import prices. In order to classify his sample of 24 developing countries by regimes of inflation, Barhoumi [(2006), "Differences in long run exchange rate pass-through into import prices in developing countries: An empirical investigation", Economic Modeling, 23 (6), 926-951.] chose an arbitrary threshold of 10% to split sample between high and low inflation regimes. For more accuracy, our study proposes to use a panel threshold framework where a grid search is used to select the appropriate threshold value. In a larger panel-data set including 63 countries over the period 1992-2012, we find that there are two thresholds points that are well identified by the data, allowing us to split our sample into three inflation regimes. When estimating the ERPT for each group of countries, we point out a strong regime-dependence of pass-through to inflation environment, that is, the class of countries with higher inflation rates experiences the higher degree of ERPT.
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AbstractThis paper sheds new light on the role of inflation regime in explaining the extent of exchange rate pass-through (ERPT) into import prices. In order to classify his sample of 24 developing countries by regimes of inflation, Barhoumi [(2006), "Differences in long run exchange rate pass-through into import prices in developing countries: An empirical investigation", Economic Modeling, 23 (6), 926-951.] chose an arbitrary threshold of 10% to split sample between high and low inflation regimes. For more accuracy, our study proposes to use a panel threshold framework where a grid search is used to select the appropriate threshold value. In a larger panel-data set including 63 countries over the period 1992-2012, we find that there are two thresholds points that are well identified by the data, allowing us to split our sample into three inflation regimes. When estimating the ERPT for each group of countries, we point out a strong regime-dependence of pass-through to inflation environment, that is, the class of countries with higher inflation rates experiences the higher degree of ERPT.J.E.L classification: C23, E31, F31, F40
