Host-country location decisions of early movers and latecomers: The role of local density and experiential learning

Service firms such as banks and hotels typically locate multiple foreign affiliates in the same host country. Often, these location patterns occur in waves with early movers followed by latecomers; for example, the early entries of Japanese banks into the U.S. market in the 1970s and 1980s were followed by emerging-market Asian banks in the 1990s. Using insights from the agglomeration and organizational learning literatures, we argue that local density and experiential learning affect location choices within a host country, and that these relationships differ between early movers and latecomers. We test and find support for our arguments using a sample of Asian banks in the United States over 1997–2003.     

Migration to U.S. frontier cities and job opportunity, 1860–1880

I use a new sample of families linked between the 1860 and 1880 U.S. censuses to study the impact of migration to frontier cities on job holding. Using variation in transportation costs between different regions of the country to generate exogenous migration, I find frontier city migration had significant job-holding benefits. The impact of migration on job holding was 68% greater for immigrants than for the native born. Expectations about job holding were the most important factor in the decision to migrate to a frontier city. Clerical workers, unskilled blue-collar workers, immigrants, and the poor were also the most likely to migrate. These results show the benefits of geographic mobility and suggest the contribution of frontier cities to economic opportunity in America's past.     

Interest Rate Derivatives in a Duffie and Kan Model with Stochastic Volatility: An Arrow-Debreu Pricing Approach

Simple analytical pricing formulae have been derived, by different authors and for several derivatives, under the Gaussian Langetieg (1980) model. The purpose of this paper is to use such exact Gaussian solutions in order to obtain approximate analytical pricing formulas under the most general stochastic volatility specification of the Duffie and Kan (1996) model. Using Gaussian Arrow-Debreu state prices, first order stochastic volatility approximate pricing solutions will be derived only involving one integral with respect to the time-to-maturity of the contingent claim under valuation. Such approximations will be shown to be much faster than the existing exact numerical solutions, as well as accurate.