【土木計画学国際セミナーと共催】 要旨：Ontario is Canada's largest province in terms of both population and GDP. It accounts for about half of Canada-US trade, which is still the largest bilateral trade relationship in the world. The great majority of trade is in manufactured goods, many of which are intermediate goods moving between production facilities in cross-border supply chains. Border costs have a negative impact on the efficiency of these supply chains and the production systems they support. Costs at the Canada-US border are substantial for a number of reasons. NAFTA is not a customs union, so substantial documentation is required even on goods that cross duty-free. There are inconsistent product regulations and health inspections are often repeated on each side of the border. Geography dictates that crossings are limited to a small number of rivers that connect the Great Lakes, so traffic congestion is common. The terrorist attacks of September 11, 2001 led to heightened security measures that have increased the cost and time of border crossings for both goods and people. This presentation will summarize research on border costs and their economic impacts. It will also review policy initiatives directed at making borders more efficient, with emphasis on reducing border inspections through enhanced supply chain security.

要旨：The standard approaches to studying industrial agglomeration have been in terms of summary measures of the "degree of agglomeration" within each industry. But such measures often fail to distinguish between industries that exhibit substantially different spatial scales of agglomeration. In a previous paper, Mori and Smith (2014) proposed a new pair of quantitative measures for distinguishing both the scale and degree of industrial agglomeration based on an explicit method for detecting spatial clusters. The first, designated as the global extent (GE) of industrial clusters, measures the spatial spread of these clusters (within a given country) in terms of the areal size of their essential containment, defined to be the (convex-solid) region containing the most significant subset of these clusters. The second, designated as the local density (LD) of industrial clusters, measures the spatial extent of individual clusters within their essential containment in terms of the areal share of that containment occupied by clusters. The central purpose of the present paper is to apply these two measures to the manufacturing industries in Japan, and to demonstrate how they can be used in combination to distinguish both the relative scale and degree of agglomeration exhibited by cluster patterns for each industry. In addition, the information provided by this pair of measures (GE, LD) is systematically compared to that of the most prominent summary measures currently in use. Finally, it is shown that these measures also support certain predictions of new economic geography models in the sense that shipping distances for establishments in each industry tend to be negatively (positively) correlated with the GE (LD) measures of agglomeration in these industries.

要旨：An empirical finding by Trefler (2004, AER) and others that industrial productivity increases more strongly in liberalized industries than in non-liberalized industries has been widely accepted as evidence for the Melitz (2003, Econometrica) model. We show that under fairly standard assumptions, a multi-industry version of the Melitz model does not predict this relationship. Instead, it predicts the opposite relationship that industrial productivity increases more strongly in non-liberalized industries than in liberalized industries.