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A spatial regression methodology for exploring the role of regional connectivity in knowledge production: Evidence from Chinese regions

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  • Yuxue Sheng
  • James LeSage

Abstract

We explore the role of alternative types of connectivity between regions in knowledge production. Past literature has criticized exclusive focus on the role played by spatial proximity in knowledge production. We introduce a methodology that allows for simultaneous consideration of multiple dependence sets, based on a convex combination of multiple n × n weight matrices. Each matrix represents a different set of connections between regions on which knowledge production exhibits dependence. We show how to estimate spatial panel regression models based on the convex combination of alternative dependence sets, and to draw inferences regarding the relative importance of each type of dependence. We illustrate our method using a model of knowledge production for 263 Chinese regions. En este artículo se explora el papel de los tipos alternativos de conectividad entre regiones en la producción de conocimiento. La literatura anterior ha criticado el enfoque exclusivo en el papel que juega la proximidad espacial en la producción de conocimiento. Aquí se introduce una metodología que permite la consideración simultánea de múltiples conjuntos de dependencia, basada en una combinación convexa de múltiples matrices ponderadas n × n. Cada matriz representa un conjunto diferente de conexiones entre regiones de las que depende la producción de conocimiento. Se muestra cómo estimar modelos de regresión de panel espacial basados en la combinación convexa de conjuntos de dependencia alternativos, y cómo extraer inferencias sobre la importancia relativa de cada tipo de dependencia. El método se ilustra utilizando un modelo de producción de conocimiento para 263 regiones chinas. 知識生産における地域と地域をつなぐ新世代タイプのコネクティビティの役割を検討した。過去の研究では、知識生産における空間的近接性の役割にのみ注目していることを批判している。多重n×nの重み行列の凸結合に基づいて、複数の依存データセットを同時に考慮できる方法を導入した。各行列はそれぞれに異なる、知識生産が依存性を示す地域間の関係を表す。我々は、代替依存データセットの凸結合に基づく空間パネル回帰モデルを推定する方法を提示し、それぞれの依存タイプの相対的な重要性に関して推論する。中国の263の地域に対する知識生産のモデルを用いて、この方法を例証する。

Suggested Citation

  • Yuxue Sheng & James LeSage, 2021. "A spatial regression methodology for exploring the role of regional connectivity in knowledge production: Evidence from Chinese regions," Papers in Regional Science, Wiley Blackwell, vol. 100(4), pages 847-874, August.
  • Handle: RePEc:bla:presci:v:100:y:2021:i:4:p:847-874
    DOI: 10.1111/pirs.12601
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    1. Adam Jaffe & Manuel Trajtenberg, 1999. "International Knowledge Flows: Evidence From Patent Citations," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 8(1-2), pages 105-136.
    2. Cilem Selin Hazır & James LeSage & Corinne Autant‐Bernard, 2018. "The role of R&D collaboration networks on regional knowledge creation: Evidence from information and communication technologies," Papers in Regional Science, Wiley Blackwell, vol. 97(3), pages 549-567, August.
    3. Olivier Parent & James P. LeSage, 2008. "Using the variance structure of the conditional autoregressive spatial specification to model knowledge spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 235-256.
    4. Raffaele Paci & Emanuela Marrocu & Stefano Usai, 2014. "The Complementary Effects of Proximity Dimensions on Knowledge Spillovers," Spatial Economic Analysis, Taylor & Francis Journals, vol. 9(1), pages 9-30, March.
    5. Francesco Quatraro & Stefano Usai, 2017. "Are knowledge flows all alike? Evidence from European regions," Regional Studies, Taylor & Francis Journals, vol. 51(8), pages 1246-1258, August.
    6. Jaffe, Adam B, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits, and Market Value," American Economic Review, American Economic Association, vol. 76(5), pages 984-1001, December.
    7. Ernest Miguélez & Rosina Moreno, 2013. "Do Labour Mobility and Technological Collaborations Foster Geographical Knowledge Diffusion? The Case of European Regions," Growth and Change, Wiley Blackwell, vol. 44(2), pages 321-354, June.
    8. Thomas Scherngell & Yuanjia Hu, 2011. "Collaborative Knowledge Production in China: Regional Evidence from a Gravity Model Approach," Regional Studies, Taylor & Francis Journals, vol. 45(6), pages 755-772.
    9. Donald J. Lacombe & James P. LeSage, 2018. "Use and interpretation of spatial autoregressive probit models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 1-24, January.
    10. Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, Oxford University Press, vol. 108(3), pages 577-598.
    11. Henderson, J. Vernon, 2003. "Marshall's scale economies," Journal of Urban Economics, Elsevier, vol. 53(1), pages 1-28, January.
    12. Agrawal, Ajay & Kapur, Devesh & McHale, John, 2008. "How do spatial and social proximity influence knowledge flows? Evidence from patent data," Journal of Urban Economics, Elsevier, vol. 64(2), pages 258-269, September.
    13. Elhorst, J. Paul & Lacombe, Donald J. & Piras, Gianfranco, 2012. "On model specification and parameter space definitions in higher order spatial econometric models," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 211-220.
    14. Jannika Mattes, 2012. "Dimensions of Proximity and Knowledge Bases: Innovation between Spatial and Non-spatial Factors," Regional Studies, Taylor & Francis Journals, vol. 46(8), pages 1085-1099, December.
    15. Audretsch, David B & Feldman, Maryann P, 1996. "R&D Spillovers and the Geography of Innovation and Production," American Economic Review, American Economic Association, vol. 86(3), pages 630-640, June.
    16. Luc Anselin & Attila Varga & Zoltan Acs, 2008. "Local Geographic Spillovers Between University Research and High Technology Innovations," Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 9, pages 95-121, Edward Elgar Publishing.
    17. James P. LeSage & R. Kelley Pace, 2014. "The Biggest Myth in Spatial Econometrics," Econometrics, MDPI, vol. 2(4), pages 1-33, December.
    18. Jaffe, Adam B, 1989. "Real Effects of Academic Research," American Economic Review, American Economic Association, vol. 79(5), pages 957-970, December.
    19. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    20. Marrocu, Emanuela & Paci, Raffaele & Usai, Stefano, 2013. "Proximity, networking and knowledge production in Europe: What lessons for innovation policy?," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1484-1498.
    21. Hong, Wei & Su, Yu-Sung, 2013. "The effect of institutional proximity in non-local university–industry collaborations: An analysis based on Chinese patent data," Research Policy, Elsevier, vol. 42(2), pages 454-464.
    22. Debarsy, Nicolas & LeSage, James, 2018. "Flexible dependence modeling using convex combinations of different types of connectivity structures," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 48-68.
    23. LeSage, James P. & Pace, Robert Kelley, 2011. "Pitfalls in Higher Order Model Extensions of Basic Spatial Regression Methodology," The Review of Regional Studies, Southern Regional Science Association, vol. 41(1), pages 13-26, Summer.
    24. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
    25. Debarsy, Nicolas & LeSage, James, 2018. "Flexible dependence modeling using convex combinations of different types of connectivity structures," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 48-68.
    26. James LeSage & Yuxue Sheng, 2014. "A spatial econometric panel data examination of endogenous versus exogenous interaction in Chinese province-level patenting," Journal of Geographical Systems, Springer, vol. 16(3), pages 233-262, July.
    27. James P. LeSage & Manfred M. Fischer & Thomas Scherngell, 2007. "Knowledge spillovers across Europe: Evidence from a Poisson spatial interaction model with spatial effects," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 393-421, August.
    28. Roberta Capello & Andrea Caragliu, 2018. "Proximities and the Intensity of Scientific Relations," International Regional Science Review, , vol. 41(1), pages 7-44, January.
    29. Giacomo Becattini & Marco Bellandi & Gabi Dei Ottati & Fabio Sforzi, 2003. "From Industrial Districts to Local Development," Books, Edward Elgar Publishing, number 2884.
    30. J. Paul Elhorst, 2014. "Spatial Panel Data Models," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 37-93, Springer.
    31. Andrea Caragliu & Peter Nijkamp, 2016. "Space and knowledge spillovers in European regions: the impact of different forms of proximity on spatial knowledge diffusion," Journal of Economic Geography, Oxford University Press, vol. 16(3), pages 749-774.
    32. Vernon Henderson, J., 2007. "Understanding knowledge spillovers," Regional Science and Urban Economics, Elsevier, vol. 37(4), pages 497-508, July.
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    2. Piribauer, Philipp & Glocker, Christian & Krisztin, Tamás, 2023. "Beyond distance: The spatial relationships of European regional economic growth," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    3. Cai, Zhengzheng & Zhu, Yanli & Han, Xiaoyi, 2022. "Bayesian analysis of spatial dynamic panel data model with convex combinations of different spatial weight matrices: A reparameterized approach," Economics Letters, Elsevier, vol. 217(C).
    4. Qingyi Chen & Qinglan Qian & Zuolin Yao & Na Yang & Junyue Tong & Yujiao Wang, 2022. "Global–Local Knowledge Spillover Strategic Coupling Network: Biopharmaceutical Industry Study of GBA, China," Sustainability, MDPI, vol. 14(21), pages 1-17, November.

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