Measuring industry coagglomeration and identifying the driving forces
Bibliographic Data
| ID | 12694222 |
|---|---|
| Authors | Emma Howard (0000-0003-0108-1220, University of Oxford, corresponding author), Carol Newman (0000-0002-1785-0891, Trinity College Dublin), Finn Tarp (0000-0002-6247-4370, Trinity College Dublin) |
| Year | 2015 |
| Volume | 16 |
| Issue | 5 |
| Pages | 1055-1078 |
| Publication date | 2015-10-13 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Economic Geography (JOURNAL) |
| Journal identifiers | ISSN: 1468-2702 • E-ISSN: 1468-2710 |
| Publisher | Oxford University Press (OUP) (PUBLISHER) |
| DOI | 10.1093/jeg/lbv037 |
| OpenAlex | W1572455474 |
| Language | EN |
| Citations received | 20 |
| References cited | 25 |
Understanding industry agglomeration and its driving forces is critical for the formulation of industrial policy in developing countries. Crucial to this process is the definition and measurement of agglomeration. We construct a new coagglomeration index based purely on the location of firms. We examine what this index reveals about the importance of transport costs, labour market pooling and technology transfer for agglomeration processes, controlling for overall industry agglomeration. We compare the results based on our new measure to existing measures in the literature and find very different underlying stories at work. We conclude that in conducting analyses of this kind giving consideration to the source of agglomeration economies, employees or entrepreneurs, and finding an appropriate measure for agglomeration, are both crucial to the process of identifying agglomerative forces
Business · Construct (python library · Econometrics · Economic geography · Economics · Economies of agglomeration · Index (typography · Industrial organization · Measure (data warehouse · Microeconomics · Pooling · Process (computing · Urban agglomeration · Work (physics · Computer Science · Economic Growth and Productivity · Engineering · Fiscal Policy and Economic Growth · Regional Economics and Spatial Analysis
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Co-location of skill-related suppliers
Towards sustainable development
China's impact on regional employment
Spatio-temporal agglomeration and morphological causes of Shanghai catering clusters
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Economic development, openness, and the impact of industrial co-agglomeration on urban carbon efficiency
Economic agglomeration and technical efficiency of small and medium-sized enterprises
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Spag
Private sector development and provincial patterns of poverty
Spillovers in ICT adoption from formal to informal firms
Industrial Coagglomeration, Green Innovation, and Manufacturing Carbon Emissions
Exploring the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control in China
Will green technological progress help industrial collaborative agglomeration increase regional carbon productivity
Firm heterogeneity in industrial clustering of Indian manufacturing industries
Urban wage premium and informal agglomeration in Vietnam
Which commercial sectors coagglomerate with the accommodation industry? Evidence from Barcelona
Why do industries coagglomerate? How Marshallian externalities differ by industry and have evolved over time
What Geographical Concentration of Industries in the Tunisian Sahel? Empirical Evidence Using Distance‐Based Measures
The Spatial Economy
Econometric Issues in the Analysis of Regressions with Generated Regressors
Multiple equilibria and structural transition of non-monocentric urban configurations
Matching and agglomeration economies in a system of cities
Testing for Localization Using Micro-Geographic Data
What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns
The Geographic Concentration of Industry
The knowledge spillover theory of entrepreneurship
Innovation and spatial inequality in Europe and USA
Clusters of entrepreneurship
Marshall's scale economies
Increasing Returns and Economic Geography
Identifying Agglomeration Spillovers
Geographic Concentration in U.S. Manufacturing Industries
| Unique citing works | 20 |
|---|---|
| Citations per year | 2 |
| Citation span | 2016 - 2026 (11) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 20 |