Patterns and Determinants of Productive Efficiency in State Manufacturing*

Abstract

This paper uses a stochastic frontier production-function model to measure and compare productivity efficiency in the manufacturing sector of states in the United States over the period [1959][1960][1961][1962][1963][1964][1965][1966][1967][1968][1969][1970][1971][1972]. Based on this model we find considerable variations in productive efficiency across states. A large portion of the variation is found to be related to regional differences in labor-force characteristics, levels of urbanization and industrial structure. We also examine the relationship between productive efficiency and the subsequent growth of manufacturing and find some evidence of a weak relationship between efficiency and the growth of employment.

The location of American and Japanese multinationals in Europe

“…For an alternative method that offers the robust check to the conditional logit model and does not rely on the assumption of independence of random terms, see Guimarães et al (2003), and Bertrand et al (2004). because of the restrictions imposed by union contracts, Coughlin et al (1991) found evidence that higher level of unionization attracts foreign direct investment in the United States. They explain this unexpected result by the fact that higher levels of unionization are associated with higher productivity efficiency (Beeson and Husted 1989). Coughlin et al (1991) found that a high unemployment rate gives a signal to the potential MNE of the availability of labor and thus attracts it to invest in the region.…”

What Drives the Productive Efficiency of a Firm? The Importance of Industry, Location, R&D, and Size

“…For example, Beeson and Husted (1989) found that in the United States, a considerable part of the variation of efficiency can be attributed to regional differences of the labor force characteristics, levels of urbanization, and industry structure. Second, the firm's location may affect its innovation activities, with consequences for its production process and efficiency (for an overview, see Cooke, Heidenreich and Braczyk, 2004).…”

Decomposing regional productivity growth using an aggregate production frontier

“…The error is composed of two terms, v and u. v is a symmetric random disturbance which captures the effect of statistical noise and which is assumed to be distributed as a N(0, σ 2 v ), whereas u is a non-negative random disturbance that captures technical inefficiency and which is assumed to follow a half-normal distribution, that is, u ∼ |N(0, σ 2 u )|. Production frontiers have been estimated using regional data in several papers (e.g., Beeson and Husted 1989;Brock 1999;Puig-Junoy 2001).…”