Narrow Results

We review our recent relativistic generalization of the Gutzwiller–Duistermaat–Guillemin trace formula and Weyl law on globally hyperbolic stationary space-times with compact Cauchy hypersurfaces. We also discuss anticipated generalizations to non-compact Cauchy hypersurface cases.

It is well-known that the crucial ingredient for a vector Gaussian random function is its covariance matrix, where a diagonal entry termed a direct covariance is simply the covariance function of a component but it seems no simple interpretation for an off-diagonal entry termed a cross covariance, which often make it hard to specify. In this paper we employ three approaches to derive vector random functions in space and/or time, which are not homogeneous (stationary) in general but contain the stationary case as a special case, and have long-range or short-range dependence.

Research has often focused on how foreign direct investment (FDI) transfers technology from developed economies to less developed economies. Most FDI occurs between developed economies, however, and the country receiving the greatest inflow of FDI is the United States. This paper examines whether such FDI inflows have stimulated growth of the U.S. economy. We apply time-series data to a simultaneous-equation model (SEM) that explicitly captures the bi-directional relationship between FDI and U.S. economic growth. FDI is found to have a significant, positive, and economically important impact on U.S. growth. Also, our SEM estimates reveal that FDI growth is income inelastic. These results imply that: (1) even a technologically advanced country such as the U.S. benefits from FDI, (2) the gains from FDI are very substantial in the long run, and (3) the sustainability of the U.S. current account deficit is enhanced by FDI's positive effect on productivity but undermined by the income inelasticity of FDI. Overall, the results suggest that U.S. policies should focus on keeping the country attractive to foreign direct investors.

In this paper, we derive an equilibrium relationship between the yields on Eurodollar and Treasury bills based on equivalent martingale results derived by Harrison and Kreps (1979) and Harrison and Pliska (1981, 1983), and corporate debt pricing model developed by Merton (1974). The derived equilibrium relationship incorporates the models used by Booth and Tse (1995) and Shrestha and Welch (2001) as special cases. The equilibrium relationship indicates that the conditional volatility of yield on Eurodollar explains the variation in TED spread. We empirically test the equilibrium relationship using a GARCH-M model and the concept of fractional cointegration. We use both the ex ante data implied by the respective futures contracts as well as the ex post spot data with daily, weekly and monthly frequencies. We find empirical support for the Equilibrium relationship.