IDEAS home Printed from https://ideas.repec.org/p/jet/dpaper/dpaper339.html
   My bibliography  Save this paper

Assessing agglomeration economies in the Yangzi River Delta, China : a bayesian spatial econometric approach

Author

Listed:
  • Hashiguchi, Yoshihiro
  • Chen, Kuang-hui

Abstract

This paper estimates the elasticity of labor productivity with respect to employment density, a widely used measure of the agglomeration effect, in the Yangtze River Delta, China. A spatial Durbin model is presented that makes explicit the influences of spatial dependence and endogeneity bias in a very simple way. Results of Bayesian estimation using the data of the year 2009 indicate that the productivity is influenced by factors correlated with density rather than density itself and that spatial spillovers of these factors of agglomeration play a significant role. They are consistent with the findings of Ke (2010) and Artis, et al. (2011) that suggest the importance of taking into account spatial dependence and hitherto omitted variables.

Suggested Citation

  • Hashiguchi, Yoshihiro & Chen, Kuang-hui, 2012. "Assessing agglomeration economies in the Yangzi River Delta, China : a bayesian spatial econometric approach," IDE Discussion Papers 339, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    • Handle: RePEc:jet:dpaper:dpaper339
    as

    Download full text from publisher

    File URL: https://ir.ide.go.jp/?action=repository_action_common_download&item_id=37835&item_no=1&attribute_id=22&file_no=1
    File Function: First version, 2012
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Brülhart, Marius & Mathys, Nicole A., 2008. "Sectoral agglomeration economies in a panel of European regions," Regional Science and Urban Economics, Elsevier, vol. 38(4), pages 348-362, July.
    2. Randall W. Eberts & Daniel P. McMillen, 1999. "Agglomeration Economies and Urban Public Infrastructure," Book chapters authored by Upjohn Institute researchers, in: Paul Cheshire & Edwin S. Mills (ed.),handbook or Regional and Urban Economics, volume 3, pages 1455-1495, W.E. Upjohn Institute for Employment Research.
    3. Artis, Michael & Moreno, Rosina & Miguelez, Ernest, 2009. "Assessing agglomeration economies in a spatial framework with endogenous regressors," CEPR Discussion Papers 7267, C.E.P.R. Discussion Papers.
    4. Rosenthal, Stuart S. & Strange, William C., 2004. "Evidence on the nature and sources of agglomeration economies," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 49, pages 2119-2171, Elsevier.
    5. Ciccone, Antonio & Hall, Robert E, 1996. "Productivity and the Density of Economic Activity," American Economic Review, American Economic Association, vol. 86(1), pages 54-70, March.
    6. Diego Puga, 2010. "The Magnitude And Causes Of Agglomeration Economies," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 203-219, February.
    7. Roberta Capello & Peter Nijkamp (ed.), 2009. "Handbook of Regional Growth and Development Theories," Books, Edward Elgar Publishing, number 12874.
    8. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    9. Lourens Broersma & Jan Oosterhaven, 2009. "Regional Labor Productivity In The Netherlands: Evidence Of Agglomeration And Congestion Effects," Journal of Regional Science, Wiley Blackwell, vol. 49(3), pages 483-511, August.
    10. Nijkamp, P. & Abreu, M., 2009. "Regional development theory," Serie Research Memoranda 0029, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    11. Shanzi Ke, 2010. "Agglomeration, productivity, and spatial spillovers across Chinese cities," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 45(1), pages 157-179, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kiyoyasu Tanaka & Yoshihiro Hashiguchi, 2015. "Spatial Spillovers from Foreign Direct Investment: Evidence from the Yangtze River Delta in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 23(2), pages 40-60, March.
    2. Yoshihiro Hashiguchi & Kiyoyasu Tanaka, 2015. "Agglomeration and firm-level productivity: A Bayesian spatial approach," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 95-114, November.
    3. Tanaka, Kiyoyasu & Hashiguchi, Yoshihiro, 2012. "Spatial spillovers from FDI agglomeration : evidence from the Yangtze River Delta in China," IDE Discussion Papers 354, Institute of Developing Economies, Japan External Trade Organization(JETRO).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tanaka, Kiyoyasu & Hashiguchi, Yoshihiro, 2017. "Agglomeration economies in the formal and informal sectors : a Bayesian spatial approach," IDE Discussion Papers 666, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    2. Tanaka, Kiyoyasu & Hashiguchi, Yoshihiro, 2015. "Agglomeration effects of informal sector: evidence from Cambodia," IDE Discussion Papers 495, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    3. Yoshihiro Hashiguchi & Kiyoyasu Tanaka, 2015. "Agglomeration and firm-level productivity: A Bayesian spatial approach," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 95-114, November.
    4. Jonathan Jones, 2017. "Agglomeration economies and the location of foreign direct investment: A meta-analysis," Journal of Regional Science, Wiley Blackwell, vol. 57(5), pages 731-757, November.
    5. Thomas de Graaff & Frank G. van Oort & Raymond J.G.M. Florax, 2012. "Regional Population–Employment Dynamics Across Different Sectors Of The Economy," Journal of Regional Science, Wiley Blackwell, vol. 52(1), pages 60-84, February.
    6. Stefan P. T. Groot & Henri L. F. Groot, 2020. "Estimating the Skill Bias in Agglomeration Externalities and Social Returns to Education: Evidence from Dutch Matched Worker-Firm Micro-Data," De Economist, Springer, vol. 168(1), pages 53-78, March.
    7. Benos, Nikos & Karagiannis, Stelios, 2013. "Do Cross-Section Dependence and Parameter Heterogeneity Matter? Evidence on Human Capital and Productivity in Greece," MPRA Paper 53326, University Library of Munich, Germany.
    8. Stefan P.T. Groot & Henri L.F. Groot & Martijn J. Smit, 2014. "Regional Wage Differences In The Netherlands: Micro Evidence On Agglomeration Externalities," Journal of Regional Science, Wiley Blackwell, vol. 54(3), pages 503-523, June.
    9. Ana Maria Bonomi Barufi & Eduardo Amaral Haddad & Peter Nijkamp, 2016. "Industrial scope of agglomeration economies in Brazil," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(3), pages 707-755, May.
    10. Frank G. van Oort & Martijn J. Burger & Joris Knoben & Otto Raspe, 2012. "Multilevel Approaches And The Firm-Agglomeration Ambiguity In Economic Growth Studies," Journal of Economic Surveys, Wiley Blackwell, vol. 26(3), pages 468-491, July.
    11. Giulio Cainelli & Andrea Fracasso & Giuseppe Vittucci Marzetti, 2015. "Spatial agglomeration and productivity in Italy: A panel smooth transition regression approach," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 39-67, November.
    12. Holl , Adelheid, 2013. "Firm location and productivity in Spain," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 25, pages 27-42.
    13. Benos, Nikos & Karagiannis, Stelios, 2016. "Do education quality and spillovers matter? Evidence on human capital and productivity in Greece," Economic Modelling, Elsevier, vol. 54(C), pages 563-573.
    14. Akihiro Otsuka, 2017. "Regional determinants of total factor productivity in Japan: stochastic frontier analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(3), pages 579-596, May.
    15. Katiuscia Lavoratori & Davide Castellani, 2021. "Too close for comfort? Microgeography of agglomeration economies in the United Kingdom," Journal of Regional Science, Wiley Blackwell, vol. 61(5), pages 1002-1028, November.
    16. Julián Ramajo & José Manuel Cordero & Miguel Ángel Márquez, 2017. "European regional efficiency and geographical externalities: a spatial nonparametric frontier analysis," Journal of Geographical Systems, Springer, vol. 19(4), pages 319-348, October.
    17. de Graaff, Thomas & van Oort, Frank G. & Florax, Raymond J.G.M., 2012. "Sectoral heterogeneity, accessibility and population–employment dynamics in Dutch cities," Journal of Transport Geography, Elsevier, vol. 25(C), pages 115-127.
    18. Emanuela Marrocu & Raffaele Paci & Stefano Usai, 2013. "Productivity Growth In The Old And New Europe: The Role Of Agglomeration Externalities," Journal of Regional Science, Wiley Blackwell, vol. 53(3), pages 418-442, August.
    19. Neil Foster & Robert Stehrer, 2009. "Sectoral Productivity, Density and Agglomeration in the Wider Europe," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(4), pages 427-446.
    20. Federico Curci, 2015. "The taller the better? Agglomeration determinants and urban structure," ERSA conference papers ersa15p991, European Regional Science Association.

    More about this item

    Keywords

    China; Local economy; Econometric model; Agglomeration economies; Spatial autocorrelation; Endogeneity; Bayesian estimation; Omitted variables; Bayesian; Spatial Durbin model;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jet:dpaper:dpaper339. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michitaka Imamitsu (email available below). General contact details of provider: https://edirc.repec.org/data/idegvjp.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.