Efficient Unit Root Tests of real Exchange Rates in the Post-Bretton Woods Era

We apply the efficient unit-roots tests of Elliott, Rothenberg, and Stock (1996), and Elliott (1998) to twenty-one real exchange rates using monthly data of the G-7 countries from the post-Bretton Woods floating exchange rate period. Our results indicate that, for eighteen out of the twenty-one real exchange rates, the null hypothesis of a unit root can be rejected at the 10% significance level or better using the Elliot et al (1996) DF-GLS test. The unit-root null hypothesis is also rejected for one additional real exchange rate when we allow for one endogenously determined break in the time series of the real exchange rate as in Perron (1997). In all, we find favorable evidence to support long-run purchasing power parity in nineteen out of twenty-one real exchange rates. Second, we find no strong evidence to suggest that the use of non-U.S. dollar-based real exchange rates tend to produce more favorable result for long-run PPP than the use of U.S. dollar-based real exchange rates as Lothian (1998) has concluded.

A Bootstrap-Regression Procedure to Capture Unit Specific Effects in Data Envelopment Analysis

The Data Envelopment Analysis (DEA) efficiency score obtained for an individual firm is a point estimate without any confidence interval around it. In recent years, researchers have resorted to bootstrapping in order to generate empirical distributions of efficiency scores. This procedure assumes that all firms have the same probability of getting an efficiency score from any specified interval within the [0,1] range. We propose a bootstrap procedure that empirically generates the conditional distribution of efficiency for each individual firm given systematic factors that influence its efficiency. Instead of resampling directly from the pooled DEA scores, we first regress these scores on a set of explanatory variables not included at the DEA stage and bootstrap the residuals from this regression. These pseudo-efficiency scores incorporate the systematic effects of unit-specific factors along with the contribution of the randomly drawn residual. Data from the U.S. airline industry are utilized in an empirical application.