Research

Abstract

The exchange rate is one of the most volatile macroeconomic price variables. Fluctuations in the exchange rate generate volatility in the profits of firms and reduce incentives for firms to enter the market or expand their capacity. In response to exchange rate volatility, firms can reduce labor costs to mitigate the negative impact by firing workers. However, rigidity in the labor market restricts a firm's ability to implement this adjustment. These restrictions can amplify the negative effects of exchange rate volatility on economic outcomes. This study examines the interaction effects of exchange rate volatility and labor market rigidity on export growth using comprehensive panel data.

To quantify the interaction effects of exchange rate volatility and labor market rigidity, we employ a panel fixed effects econometric model, which is analogous to the difference-in-differences approach. We construct a source-target-industry panel for 135 source countries, a maximum of 183 targets, and 17 industries over a span of 14 years from 2005 to 2018.

Our results imply that in a country where labor market rigidity is one standard deviation higher, a one standard deviation increase in exchange rate volatility reduces export growth by 0.31 percentage points. In a subsample analysis, we find that the interaction between exchange rate volatility and labor market rigidity has a more pronounced negative impact on export growth in Organization for Economic Co-operation and Development (OECD) countries compared to non-OECD countries. We also find that there is little treatment heterogeneity across industries.

Abstract

This study examines the impact of exports on subnational income and regional inequality between urban (trade hub) and rural (non-trade hub) areas, using nighttime luminosity as a proxy for economic activity. We construct a country-period panel dataset covering 104 countries, based on five-year averaged data from 1997 to 2020. Trade hub areas are defined as the union of areas within a 30 km  or 50 km radius of each of the three largest ports and three international airports in a country; all remaining areas are classified as non-trade hub areas.

To address endogeneity, we employ a two-stage least squares (2SLS) model using predicted trade as an instrumental variable. Predicted trade is derived from a dynamic gravity equation in which time dummies are interacted with sea and air transport distances. This instrument captures changes in transportation costs driven by technological advances that have shifted trade from sea to air, thereby affecting trade volumes.

Our results indicate that a 1\% increase in exports raises nighttime luminosity by 0.33\% in trade hub areas and by 0.09\% in non-trade hub areas. Export growth also leads to population increases in trade hub areas, but not in non-trade hub areas. Moreover, we find that a 1\% increase in exports raises nighttime luminosity per capita by 0.21\% in trade hub areas and by 0.08\% in non-trade hub areas. These findings suggest that while exports enhance economic activity in trade hubs, population inflows partially offset per capita gains. Nonetheless, trade significantly amplifies regional inequality.