要旨：This paper provides a detailed empirical investigation of the distribution of travel times on an urban road for valuation of travel time variability. Our investigation is premised on the use of a theoretical model with a number of desirable properties. The definition of the value of travel time variability depends on certain properties of the distribution of random travel times that require empirical verification. Applying a range of nonparametric statistical techniques to data giving minute-by-minute travel times for a congested urban road over a period of five months, we show that the standardized travel time is roughly independent of the time of day as required by the theory. Except for the extreme right tail, a stable distribution seems to fit the data well. The travel time distributions on consecutive links seem to share a common stability parameter such that the travel time distribution for a sequence of links is also a stable distribution. The parameters of the travel time distribution for a sequence of links can then be derived analytically from the link level distributions.

要旨：This paper empirically examines whether the geographical proximity of transaction partners improves the firms' profits by using the actual microdata on inter-firm transactions. I model the formation of transaction partners between newly entering firms and existing firms as a two-sided many-to-many matching game with transferable utility and estimate the structural parameters of the model. In the results, I find that the average distance to the transaction partners negatively affects the firms' structural revenues. This strongly suggests that the existence of agglomeration economies results from the inter-firm transactions that occur between geographically close firms. Furthermore, this effect is larger for entrant firms than existing firms.