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Agglomeration Elasticities and Firm Heterogeneity

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  • Daniel J. Graham
  • David C. Maré

Abstract

This paper estimates the relationship between agglomeration and multi factor productivity at the one digit industry level and by region using longitudinal firm level data for New Zealand. A key focus of the paper is on methods to represent firm level heterogeneity and non-random sorting of firms. The panel structure of the data allows us to control for it at the level of local industries or enterprises. We obtain a cross-sectional agglomeration elasticity of 0.171, which falls by 70% when we use local industry controls, and by 90% when we impose enterprise fixed effects. Using industry specific production functions, we find that the "within local industry" estimates are similar, though slightly larger than the cross sectional estimates (~0.070), suggesting negative sorting between areas, combined with positive sorting within areas. The within-enterprise estimates yield a small elasticity of 0.010. Our results indicate that the imposition of a common production technology across all industries is not a valid assumption. While cross-sectional estimates may overstate the true impact of agglomeration on productivity in the presence of positive bias from sorting, the within enterprise approach (which is increasingly common in the literature) can suffer from identification problems due to the highly persistent nature of agglomeration variables and may understate the true causal effect of agglomeration on productivity. We thus rely on the "within local industry" estimates as providing the most reliable indication of agglomeration elasticities.

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  • Daniel J. Graham & David C. Maré, 2010. "Agglomeration Elasticities and Firm Heterogeneity," SERC Discussion Papers 0043, Spatial Economics Research Centre, LSE.
  • Handle: RePEc:cep:sercdp:0043
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    Cited by:

    1. David C. Maré, 2016. "Urban Productivity Estimation with Heterogeneous Prices and Labour," Working Papers 16_21, Motu Economic and Public Policy Research.
    2. Iimi,Atsushi & Humphrey,Richard Martin & Melibaeva,Sevara, 2015. "Firm productivity and infrastructure costs in east Africa," Policy Research Working Paper Series 7278, The World Bank.
    3. MORIKAWA Masayuki, 2016. "Location and Productivity of Knowledge- and Information-intensive Business Services," Discussion papers 16067, Research Institute of Economy, Trade and Industry (RIETI).
    4. Richard Fabling & David C Maré, 2015. "Production function estimation using New Zealand’s Longitudinal Business Database," Working Papers 15_15, Motu Economic and Public Policy Research.
    5. Eliasson, Jonas & Fosgerau, Mogens, 2017. "Cost-benefit analysis of transport improvements in the presence of spillovers, matching and an income tax," MPRA Paper 76526, University Library of Munich, Germany.
    6. Daniel Graham & Kurt Dender, 2011. "Estimating the agglomeration benefits of transport investments: some tests for stability," Transportation, Springer, vol. 38(3), pages 409-426, May.
    7. Iimi,Atsushi & Humphrey,Richard Martin & Melibaeva,Sevara, 2015. "Firms? locational choice and infrastructure development in Rwanda," Policy Research Working Paper Series 7279, The World Bank.
    8. David C. Maré & Dean R. Hyslop & Richard Fabling, 2017. "Firm productivity growth and skill," New Zealand Economic Papers, Taylor & Francis Journals, vol. 51(3), pages 302-326, September.
    9. Arthur Grimes & Eyal Apatov & Larissa Lutchmann & Anna Robinson, 2014. "Infrastructure?s Long-Lived Impact on Urban Development: Theory and Empirics," ERSA conference papers ersa14p178, European Regional Science Association.
    10. repec:eee:retrec:v:66:y:2017:i:c:p:36-45 is not listed on IDEAS
    11. World Bank, 2014. "Regional Economic Impact Analysis of High Speed Rail in China : Main Report," World Bank Other Operational Studies 19996, The World Bank.
    12. Békés, Gábor & Harasztosi, Péter, 2013. "Agglomeration premium and trading activity of firms," Regional Science and Urban Economics, Elsevier, vol. 43(1), pages 51-64.
    13. Iimi,Atsushi & Humphreys,Richard Martin & Melibaeva,Sevara, 2015. "Firms? locational choice and infrastructure development in Tanzania : instrumental variable spatial autoregressive model," Policy Research Working Paper Series 7305, The World Bank.
    14. Marco-Lajara, Bartolomé & Claver-Cortés, Enrique & Úbeda-García, Mercedes & Zaragoza-Sáez, Patrocinio del Carmen, 2016. "A dynamic analysis of the agglomeration and performance relationship," Journal of Business Research, Elsevier, vol. 69(5), pages 1874-1879.
    15. Ying Jin & Richard Bullock & Wanli Fang, 2013. "Regional Impacts of High Speed Rail in China : Spatial Proximity and Productivity in an Emerging Economy," World Bank Other Operational Studies 19989, The World Bank.
    16. KONDO Keisuke, 2017. "Urban Wage Premium Revisited: Evidence from Japanese matched employer-employee data," Discussion papers 17047, Research Institute of Economy, Trade and Industry (RIETI).

    More about this item

    Keywords

    Agglomeration; urban density; productivity;

    JEL classification:

    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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