Location Determinants of New Foreign-Owned Manufacturing Plants

Abstract

In this paper we examine the county-level pattern of new foreign-owned manufacturing plants in the United States from 1989 through 1994. We construct a model to produce insights into the differences in the location of these plants among Bureau of Economic Analysis regions, as well as between rural and urban counties. Higher levels of economic size, educational attainment, the existing manufacturing base, and transportation infrastructure are found to be associated with larger numbers of new foreign-owned plants. Meanwhile, higher levels of taxes and labor-intensiveness are found to be associated with smaller numbers of new plants. Comparing regions, we find that the main advantages of the Southeast region stem from a relatively high manufacturing base and relatively low taxes. Comparing urban with rural counties, we find that urban counties possess more favorable average values for nearly all the explanatory variables.

The geography of new firm formation: Evidence from independent start-ups and new subsidiaries in the Netherlands

“…As regards policy environment, it depends on the kind of policy measures considered. For example, regional differences in taxes might, conform the findings by Coughlin and Segev (2000) for MNE's, especially affect new subsidiaries. Other measures that aim at reducing barriers to start especially from the individual's point of view would be particularly beneficial for increasing the number of independent start-ups.…”

“…The empirical literature points at the importance of most of the determinants discussed above, but the balance may be different. Coughlin and Segev (2000), for instance, find significant impacts of economic size, educational attainment, localization economies and urbanization economies on firm formation for MNE's in US manufacturing. In addition, they found the region's transportation infrastructure (measured by the existence of an interstate highway), as well as state and local taxes (negative) to play a key role.…”

Location decisions of Japanese new manufacturing plants in China: a discrete-choice analysis

“…Many attempts have been tried to remedy this. Coughlin and Segev (2000b), Head et al (1995Head et al ( , 1999, and Woodward (1992) adopted regional dummy variables, which are in line with American Census divisions, to capture similar unobserved location characteristics within a region. Ondrich and Wasylenko (1993) employed a nested logit model, in which they assumed that an investor would face a hierarchical and staged decision process, i.e., he/she first chooses a region and then selects a state within that region to locate his/her plant.…”

“…Therefore, greenfield investments or new plants may be more capable of reflecting the real location preferences of foreign investors because, at least in theory, they can be established on any place to satisfy these preferences. Along with Little's reasoning, the examination on the location needs of new manufacturing plants has become the dominant research design in the USA (e.g., Coughlin and Segev 2000b;Friedman et al 1992;Ondrich and Wasylenko 1993;Luger and Shetty 1985;Woodward 1992).…”

“…Discrete-choice models, which are well grounded on microeconomic utility maximization and feasible to rich empirical specifications, provide a powerful tool to reveal each individual's choices. The discrete-choice models on location choices of FDI have been well developed and successfully employed in the context of the USA (e.g., Coughlin et al 1991;Coughlin and Segev 2000b;Friedman et al 1992;Ondrich and Wasylenko 1993;Luger and Shetty 1985;Woodward 1992). New insights would be provided by integrating the discrete-choice models into the analyses on the location choices of Japanese FDI in China.…”