Regional heterogeneity and firms’ innovation: the role of regional factors in industrial R&D in India

This study makes an early attempt to estimate the magnitude and intensity of manufacturing firms’ R&D by Indian states during the period 1991‒2008 and analyses the role of regional factors on firm-level R&D activities. As there is little research on state-wise R&D performance of firms in India, this study serves an important contribution to the academic and policy realm. It has brought out the fact the total manufacturing R&D investment in India is unevenly distributed regionally with a few states accounting for disproportionate share of it. Regional heterogeneity or inter-state disparities in R&D has increased between the 1990s and the first decade of the twenty-first century. In view of this persistent regional heterogeneity in R&D, the study has developed and estimated an empirical model for a sample of 4545 Indian manufacturing firms with R&D facilities located in single state and that explicitly includes regional factors as probable factors affecting R&D. The three-step Censored Quantitle Regression results confirm that regional factors play an important role in shaping the R&D intensity of the sample of firms. This led us to some useful policy suggestions for regional governments to promote local firms’ R&D activities

The location of US manufacturing: some empirical evidence on recent geographical shifts

In this paper, current theories and hypotheses of industrial location are tested, using a cross-sectional regression analysis of employment change in total manufacturing, and in five high-technology sectors in each of 264 Metropolitan Statistical Areas, for the period 1977 - 84. Agglomeration forces and market opportunities, unions, wages, climate, and university research parks are best used to explain employment growth. Employment losses are related to declining markets and the downsizing of establishments. Agglomeration forces which influence the growth of total manufacturing are metropolitan-size related, in contrast to industry-specific externalities for individual high-technology sectors. The results indicate that growth rates decline with increasing industry concentration and metropolitan size. Policy variables based on taxes and public expenditures are not significant. The interrelationships between social and economic characteristics in selected metropolitan areas are explored. The effects of these relationships on the determinants of total manufacturing growth and decline are identified.

The restructuring of the US steel industry: changes in the location of production and employment

Recent reorganization of the US iron and steel industry provides a useful setting for an analysis of the relationship between industrial location and institutional forms. Regression analysis shows that institutional shifts in the organization of production dominated geographical shifts in employment and product value as integrated maxi-mills sought to raise productivity. The reorganization of production includes mill abandonment, increased subcontracting by maxi-mills in the initial stages of production, horizontal penetration by mini-mills in the sheet-steel market, and the growing integration of steel finishing and automobile assembly as firms that belong to Japanese corporate groups expand their operations in the USA. Maxi-mills are concentrating investment and production in the Midwest states as their joint ventures with Japanese steel firms specialize in the mass production of galvanized sheets for the automobile industry. Locational shifts also include the national spread of scrap-processing mini-mills and the rapid decline of raw-steel production in Pittsburgh as maxi-mills close furnaces and mills producing construction-grade bars and rods.

Statistical approaches to structural change in regional interindustry models

The conventional approach to assessing structural change in regional input - output tables is to measure the impact of coefficient change on the estimation of outputs and multipliers. The methods developed and tested in this paper focus exclusively on the coefficients. Univariate and multivariate statistical analyses can be used to identify and measure various types of changes ranging from coefficient instability to changes in interindustry relationships as a system. A distinction is made between structural changes in input relationships and those in output relationships. The methods are tested by using Washington State data for the years 1963 and 1967. The results are compared with previous analyses of change in these data.