THE MEASUREMENT OF HIERARCHICALLY SPATIAL INDUSTRIAL KNOWLEDGE SPILLOVER EFFECTS

Authors

  • Qianting Ye School of Economic and Commerce, South China University of Technology, Guangzhou 510006, China 2 School of Geographical Science and Urban Planning, Arizona State University, Tempe 85281, United States

DOI:

https://doi.org/10.29121/granthaalayah.v6.i6.2018.1335

Keywords:

Knowledge Spillover, Hierarchically Spatial Model, GMM Estimation, Cobb -Douglas Production Function

Abstract [English]

Based on the “year–region–industry” three - dimensional unbalanced industrial production panel data of Guangdong Province in China from 2005-2013, the relationship between knowledge spillovers and industrial structure is investigated by hierarchically spatial lagged with spatial autoregressive error (HSARAR) model. The empirical results indicate that the impacts of MAR, Jacobs, and Porter spillover on Guangdong's industry economic growth is positive and statistically significant. The industrial HSARAR model considers the hierarchical structure and spatial effect simultaneously, which has a better description on economic reality than the pooled model and SARAR model.

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References

Baltagi B.H., Fingleton B., Pirotte A. Spatial lag models with nested random effects: An instrumental variable procedure with an application to English house prices. Journal of Urban Economics, 80, 2014, 76-86. DOI: https://doi.org/10.1016/j.jue.2013.10.006

Cainelli G., Leoncini R. Externalities and long-term local industrial development: Some empirical evidence from Italy. Revue D'economie Industrielle, 90, 1999, 25-39. DOI: https://doi.org/10.3406/rei.1999.1762

Cainelli G., Leoncini R., Montini A. The evolution of industrial sectors in Europe. Paper Prepared for the Nelson and Winter Conference Aalborg, 2001.

Cliff A.D., Ord J.K. Spatial autocorrelation. Pion, London, 1973.

Corrado L. Fingleton B. Multilevel modeling with spatial effects. University of Strathclyde, Discussion Paper, 2011, 11-05.

Corrado L., Fingleton B. Where is the economics in spatial econometrics? Journal of Regional Science, 52, 2012, 210-239. DOI: https://doi.org/10.1111/j.1467-9787.2011.00726.x

Drucker J. Industrial structure and the sources of agglomeration economies: Evidence from manufacturing plant production. Growth and Change, 44, 2013, 54-91. DOI: https://doi.org/10.1111/grow.12002

Ejermo O. Technological diversity and Jacobs' externality hypothesis revisited. Growth and Change, 36, 2005, 167-195. DOI: https://doi.org/10.1111/j.1468-2257.2005.00273.x

Fingleton B., Le Gallo J., Pirotte A. Panel data models with spatially dependent nested random effects. Journal of Regional Science, 58, 2018, 63-80. DOI: https://doi.org/10.1111/jors.12327

Glaeser E.L., Kallal H.D., Scheinkman J.A., Schleifer A. Growth in cities. Journal of Political Economy, 100, 1992, 1126-1152. DOI: https://doi.org/10.1086/261856

Goldstein H. Multilevel models for analysing social data. In Encyclopaedia of Social Research Methods. Newbury Park CA: Sage Publications, 1998.

He M, Lin K.P. Testing spatial effects and random effects in a nested panel data model. Economics Letters, 135, 2015, 85-91. DOI: https://doi.org/10.1016/j.econlet.2015.07.028

Henderson V., Kuncoro A., Turner M. Industrial development in cities. Journal of Political Economy, 103, 1995, 1067-1090. DOI: https://doi.org/10.1086/262013

Kelejian H H, Prucha I R. Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances. Journal of Econometrics, 157, 2010, 53-67. DOI: https://doi.org/10.1016/j.jeconom.2009.10.025

Kreft I.G.G., De Leeuw J. Introducing multilevel modeling. London: SAGE, 1998. DOI: https://doi.org/10.4135/9781849209366

Martin P., Mayer T., Mayneris F. Spatial concentration and plant-level productivity in France. Journal of Urban Economics, 69, 2011, 182-195. DOI: https://doi.org/10.1016/j.jue.2010.09.002

Mihn K.H. An analysis of agglomeration economies in the manufacturing sector of Korea. KIET Occasional Paper, No. 56. 2004.

Widodo W., Salim R., Bloch H. Agglomeration economies and productivity growth in manufacturing industry empirical evidence from Indonesia. Economic Record, 90, 2014, 41-58. DOI: https://doi.org/10.1111/1475-4932.12115

Zhang M., Wu Y. Impact of agglomeration spillover in spatial difference of innovation activities - panel data analysis of China manufacturing industry. Micro Evidence on Innovation in Developing Economies Conference Papers, 2008.

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Published

2018-06-30

How to Cite

Ye, Q. (2018). THE MEASUREMENT OF HIERARCHICALLY SPATIAL INDUSTRIAL KNOWLEDGE SPILLOVER EFFECTS. International Journal of Research -GRANTHAALAYAH, 6(6), 67–74. https://doi.org/10.29121/granthaalayah.v6.i6.2018.1335