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Claudio Bravo-Ortega is Professor of Economics at Universidad de Chile. The authors would like to thank Müge Adalet, Barry Eichengreen, Miguel Fuentes, Pierre-Olivier Gourinchas, Gian Maria Milesi-Ferretti, Maurice Obstfeld, and Andrew Rose for comments.
Bravo-Ortega, and di Giovanni (2004) highlights a different mechanism through which trade costs affect real exchange rate volatility. In this paper, the impact of heterogeneous suppliers of traded goods on real exchange rate volatility is examined using a multicountry model of trade.
In Hau’s paper the size of nontraded goods sector is fixed, and there exists only one traded good.
Naknoi (2004) has also examined a similar channel in a dynamic general equilibrium framework. However, her work concentrates on short-run dynamics, whereas we argue that endogenous nontradability should be modeled in a long-run context. Furthermore, we provide direct evidence to test the hypothesis drawn from our model.
The results go through using the more general CES function, but greatly complicates the algebra. Therefore, the more specific function (i.e., logarithmic) is used for clarity.
The assumption of independent productivity shocks, i.e., Cov (ε, ε*) = 0, may seem strong. However, the assumption does not alter our main result. If there were covariance in the shocks one extra term would be added.
Note that similar conditions will hold ex post.
These assumptions allow us to introduce uncertainty in a tractable manner.
Note, that as argued in footnote 7 above, the assumption of independent domestic and foreign shocks does not alter our results. Specifically, given the setup of the model, the solution for real exchange rate volatility, equation (7), would have the additional term Cov (ε, ε*) (zH − zF). Therefore, volatility will always be increasing in trade costs.
We also experimented with fixed vs. floating exchange rate dummies, but our results were robust to the inclusion of these variables.
We include some countries that have experienced hyperinflation, such as Bolivia (BOL), Uganda (UGA), and the Dem. Rep. of the Congo (ZAR), where measured exchange rate volatility is very high due to a small part of the whole sample period. However, if anything, including these countries will bias our estimation away from finding a strong relationship between volatility and Remoteness.
Taking the volatility of the log change has two advantages over taking the volatility of the log level: (i) the resulting measure is in invariant to the country, and (ii) the measure allows us to interpret the coefficients in the regressions as essentially elasticities.