Regional dominance and industrial success: a productivity-based analysis

The relationship between industrial structure and economic performance has long interested researchers in regional science, industrial economics, and economic development. Research on the subject, however, has largely overlooked the influence that regional industrial dominance—regional concentration within a specific industry— may have upon smaller local firms in that industry. This dissertation investigates the links between regional industrial dominance, agglomeration economies, and firm performance for selected U.S. industries, focusing on two main hypotheses: 1) plants in regional industries dominated by a few relatively large firms are less productive than establishments in the same industry located in other regions; 2) small establishments in dominated regional industries are less productive because they are limited in their ability to take advantage of regionally available external economies. Confidential micro-level data from the United States Census Bureau are used to estimate a cross-sectional production system at the plant level for three manufacturing sectors: rubber and plastics, metalworking machinery, and measuring and controlling devices. The models incorporate indicators of regional industrial dominance, spatially attenuating measures of agglomeration economies, and controls for other relevant establishment and regional characteristics. Estimating production functions at the establishment level serves to address many of the methodological drawbacks of earlier production function work and supports direct tests of the research hypotheses. The primary finding is that regional industrial dominance has substantial negative impacts on production, especially for small, dominated establishments. There is little evidence to support the second hypothesis that the diminished productivity of dominated businesses stems from reduced capacity to exploit localized agglomeration economies. The results demonstrate the importance of regional industrial dominance as a determinant of establishment productivity, and indicate that analysts and policymakers should examine regional industrial structure as a key component of the external environment that helps shape business performance and regional economic adaptability. Further research will be required to understand the precise mechanisms by which regional industrial dominance acts to influence economic performance and to guide the design of appropriate policies for economic development

Innovation Districts As A Strategy for Urban Economic Development: A Comparison of Four Cases

Innovation districts are a relatively new strategy in urban economic development. They have been fast gaining attention and popularity, due in part to energetic third-party promotion and the apparent successes of two early adopters: Barcelona and Boston. As additional cities establish and promote innovation districts, it benefits policymakers to possess information regarding their characteristics and suitability as an economic development approach. We conduct in-depth case studies of four innovation districts in the United States—located in Boston, Detroit, Saint Louis, and San Diego—that present contrasting settings, policies, and outcomes. The empirical information is drawn primarily from interviews with the innovation district creators and implementers and the entrepreneurs embedded within them. We assess the expectations, design, implementation, and operation of these innovation districts, with reference to stated and normative policy goals along with theories of regional economic development. Our purpose is to provide scholars and policymakers with guidance as to how, and how well, innovation districts may achieve the aim of urban economic development to generate economic dynamism and prosperity

Testing the data framework for an AI algorithm in preparation for high data rate X-ray facilities

The advent of next-generation X-ray free electron lasers will be capable of delivering X-rays at a repetition rate approaching 1 MHz continuously. This will require the development of data systems to handle experiments at these type of facilities, especially for high throughput applications, such as femtosecond X-ray crystallography and X-ray photon fluctuation spectroscopy. Here, we demonstrate a framework which captures single shot X-ray data at the LCLS and implements a machine-learning algorithm to automatically extract the contrast parameter from the collected data. We measure the time required to return the results and assess the feasibility of using this framework at high data volume. We use this experiment to determine the feasibility of solutions for `live' data analysis at the MHz repetition rate

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Trends in Regional Industrial Concentration in the United States

In a seminal article, Benjamin Chinitz (1961) raises the question of the effects that industry size, structure, and economic diversification may have on firm performance and regional economies. His line of inquiry suggests a related but conceptually distinct issue: how does the extent to which a industry is regionally dominated—concentrated locally in a single or small number of firms—impact the local performance of that industry? This question has received little attention, principally because accurately measuring industrial concentration at the regional scale requires firm-level information. This paper makes use of confidential plant- and firm-level manufacturing data to explore patterns of industrial concentration in the United States at the regional scale. Regional analogues of concentration ratios and other measures commonly used in the aspatial industrial organization literature indicate the extent to which manufacturing activity is concentrated in a small number of firms. Both the manufacturing sector as a whole and major manufacturing industry sectors are examined in order to determine the extent of industrial concentration in the continental United States, to explore changes over time in geographic patterns of concentration, and to investigate associations between industrial concentration and employment growth at the regional scale. Implications for understanding regional growth and for devising regional economic development policy are discussed.

Concentration, Diversity, and Manufacturing Performance

Regional economist Benjamin Chinitz was one of the most successful proponents of the idea that regional industrial structure is an important determinant of economic performance. His influential article in the American Economic Review in 1961 prompted substantial research measuring industrial structure at the regional scale and examining its relationships to economic outcomes. A considerable portion of this work operationalized the concept of regional industrial structure as sectoral diversity, the degree to which the composition of an economy is spread across heterogeneous activities. Diversity is a relatively simple construct to measure and interpret, but does not capture the implications of Chinitz’s ideas fully. The structure within regional industries may also influence the performance of business enterprises. In particular, regional intra-industry concentration—the extent to which an industry is dominated by a few relatively large firms in a locality—has not appeared in empirical work studying economic performance apart from individual case studies, principally because accurately measuring concentration within a regional industry requires firm-level information. Multiple establishments of varying sizes in a given locality may be part of the same firm. Therefore, secondary data sources on establishment size distributions (such as County Business Patterns or aggregated information from the Census of Manufactures) can yield only deceptive portrayals of the level of regional industrial concentration. This paper uses the Longitudinal Research Database, a confidential establishment-level dataset compiled by the United States Census Bureau, to compare the influences of industrial diversity and intra-industry concentration upon regional and firm-level economic outcomes. Manufacturing establishments are aggregated into firms and several indicators of regional industrial concentration are calculated at multiple levels of industrial aggregation. These concentration indicators, along with a regional sectoral diversity measure, are related to employment change over time and incorporated into plant productivity estimations, in order to examine and distinguish the relationships between the differing aspects of regional industrial structure and economic performance. A better understanding of the particular links between regional industrial structure and economic performance can be used to improve economic development planning efforts. With continuing economic restructuring and associated workforce dislocation in the United States and worldwide, industrial concentration and over-specialization are separate mechanisms by which regions may “lock in” to particular competencies and limit the capacity to adjust quickly and efficiently to changing markets and technologies. The most appropriate and effective policies for improving economic adaptability should reflect the structural characteristics that limit flexibility. This paper gauges the consequences of distinct facets of regional industrial structure, adding new depth to the study of regional industries by economic development planners and researchers.

Reconsidering the Regional Economic Development Impacts of Higher Education Institutions in the United States

<p>Drucker J. Reconsidering the regional economic development impacts of higher education institutions in the United States, <i>Regional Studies.</i> This study models relationships between US higher education activities and regional economic performance, 2001–11. Advances include incorporating all degree-granting institutions; estimating spatial spillovers; and comparing multiple economic outcomes, including production and entrepreneurship. Higher education impacts vary by outcome measure but are less influential than in previous studies. Spillovers are substantial up to 60 miles (97 kilometres), reflecting considerable influence across space. More advanced degrees, science and engineering education, and population educational attainment are positively associated with entrepreneurial activity. These findings encourage the traditional university missions of research and teaching, and general policies promoting entrepreneurship, to support economic performance.</p

How Does Size Matter? Investigating the Relationships Among Plant Size, Industrial Structure, and Manufacturing Productivity

Industrial concentration and market power have been studied extensively at the national scale, in fields ranging from economics and industrial organization to regional science and economic development. At the regional scale, however, industrial structure and firm size relationships have received little attention outside of non-generalizable case studies, primarily because accurate measurements require difficult-to-obtain plant- or firm-level information. Readily available secondary data sources on establishment size distributions (such as County Business Patterns or the Census of Manufactures) cannot be linked to performance information for particular establishments or firms. Yet region-specific industrial structure may be a crucial determinant of firm performance and thus regional economic fortunes as well (Chinitz 1961; Christopherson and Clark 2007). This paper examines how industrial concentration and agglomeration economies impact plant performance, focusing on the influence of establishment size in mediating these effects. The Longitudinal Research Database of the U.S. Census Bureau is accessed to construct production functions for three manufacturing industries nationwide. These production functions, specified at the establishment level, incorporate characteristics of establishments, industries, and regions, including spatially-differentiated measures of agglomeration economies. Establishment size is evaluated both as an absolute metric and relative to other regional industry plants, as theory suggests that absolute size may be most pertinent to agglomeration benefits but relative size more relevant to industrial structure (Caves and Barton 1990; Bothner 2005). The research builds on earlier work by the author that establishes a direct link between regional industry concentration and the productivity of manufacturing establishments.