Research

The Efficiency of the Global Market for Productive Capabilities

Despite integration of financial and goods markets, borders still impose considerable friction on the flow of goods. This paper quantifies these frictions by estimating the cost that borders impose on international flows of capital goods. It constructs a novel measure of the real exchange rate and estimates the border cost directly from nonlinearities in the real exchange rate process. During the sample period, 1974 to 2007, a relocation reduces the quantity of the relocated capital good by 35% for the median country pair. A transfer of consumption goods entails a loss of only 15%. This difference holds even after accounting for within-country costs, and indicates that border frictions in markets for capital goods are substantially higher than in markets for consumption goods.

On the Correlation Structure of Microstructure Noise in Theory and Practice
(with F. Diebold)

We argue for incorporating the financial economics of market microstructure into the financial econometrics of asset return volatility estimation. In particular, we use market microstructure theory to derive the cross-correlation function between latent returns and market microstructure noise, which feature prominently in the recent volatility literature. The cross-correlation at zero displacement is typically negative, and cross-correlations at nonzero displacements are positive and decay geometrically. If market makers are sufficiently risk averse, however, the cross-correlation pattern is inverted. Our results are useful for assessing the validity of the frequently-assumed independence of latent price and microstructure noise, for explaining observed crosscorrelation patterns, for predicting as-yet undiscovered patterns, and for making informed conjectures as to improved volatility estimation methods.

Multivariate Comparisons of Predictive Accuracy
(with J. Christensen, F. Diebold and G. Rudebusch)

We propose a generalized Diebold-Mariano (DM) test of equal accuracy of a set of forecasts. The need for such a test arises in a variety of applications, but the existing DM literature is silent on the issue. Our approach makes only minimal assumptions on models and loss functions; it is therefore very flexible and applicable in many situations.

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