Subsidy and networking: The effects of direct and indirect support programs of the cluster policy
AbstractIndustrial clusters have attracted considerable attention worldwide for their expected contribution to regional innovation. Recently, policymakers in various countries have developed specific cluster policies. However, there exist few empirical studies on cluster policies. In this study, we use original questionnaire data to empirically evaluate the Industrial Cluster Project (ICP) initiated by the Ministry of Economy, Trade and Industry in 2001. We address two research questions on the effect of the ICP: are the project participants who exploit various support programs more successful in alliance/network formation within the cluster than others and which kind of ICP support program contributes to firm performance. In a departure from previous such projects, the ICP aims at the autonomous development of regional industries and includes both direct R&D support and indirect networking/coordination support. The focus of public support for local firms has clearly shifted toward enabling networking and coordination for those who can help themselves Thus, we pay special attention to the differences between direct R&D support and indirect networking/coordination support, which indicate the conditions necessary for the effective organization of cluster policies to improve firm performance. Our empirical evaluation is based on a recent original survey of a sample of 511 firms. We first employ the propensity score and the difference-in-differences estimation to analyze the degree of alliance/network formation before and after participating in the ICP. Thereafter, we use Heckman’s two-step procedure and the negative binomial model to examine the effects of support programs on firm performance. The estimation results suggest that cluster participants who exploit support programs (especially indirect support measures) expand the industry-university-government network after participating in the ICP. Moreover, we find that not every support program contributes to firm performance; firms should therefore select the program that is most aligned with their aims. Indirect support programs have an extensive and strong impact on output, especially innovation outcomes, whereas direct R&D support has only a weak effect.
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Bibliographic InfoPaper provided by Center for Research on Contemporary Economic Systems, Graduate School of Economics, Hitotsubashi University in its series CCES Discussion Paper Series with number 24.
Length: 30 p.
Date of creation: Dec 2009
Date of revision:
Note: [Revised January 2010]
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cluster policy; industrial cluster; R&D support; subsidy; networking;
Find related papers by JEL classification:
- O25 - Economic Development, Technological Change, and Growth - - Development Planning and Policy - - - Industrial Policy
- O38 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Government Policy
- R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-03-20 (All new papers)
- NEP-CSE-2010-03-20 (Economics of Strategic Management)
- NEP-INO-2010-03-20 (Innovation)
- NEP-PPM-2010-03-20 (Project, Program & Portfolio Management)
- NEP-SBM-2010-03-20 (Small Business Management)
- NEP-URE-2010-03-20 (Urban & Real Estate Economics)
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- Junichi Nishimura & Hiroyuki Okamuro, 2010.
"R&D Productivity and the Organization of Cluster Policy: An Empirical Evaluation of the Industrial Cluster Project in Japan,"
DRUID Working Papers
10-06, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
- Junichi Nishimura & Hiroyuki Okamuro, 2011. "R&D productivity and the organization of cluster policy: an empirical evaluation of the Industrial Cluster Project in Japan," The Journal of Technology Transfer, Springer, vol. 36(2), pages 117-144, April.
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