Scandinavian Working Papers in Economics

Papers in Innovation Studies,
Lund University, CIRCLE - Center for Innovation, Research and Competences in the Learning Economy

No 2014/10: Evaluating the Impact of Cluster Development Programs

Elisa Giuliani (), Alessandro Maffioli , Manuel Pacheco , Carlo Pietrobelli and Rodolfo Stucchi
Additional contact information
Elisa Giuliani: Department of Economics and Management, University of Pisa; CIRCLE, Lund University
Alessandro Maffioli: Inter-American Development Bank
Manuel Pacheco: Inter-American Development Bank
Carlo Pietrobelli: Inter-American Development Bank
Rodolfo Stucchi: Inter-American Development Bank

Abstract: Do the programs that aim to promote and develop industry clusters (also known as Cluster Development Programs, or CDP) work? Do they have an impact on enterprise development? This paper offers an insight into the methods that can help answer these fundamental questions through solid quantitative evidence. In general, results will depend on the level of coordination that is achieved and on the actions undertaken as a result of improved coordination and strategy-setting of the relevant actors. The techniques of Social Network Analysis (SNA) can be employed to assess the evolution of coordination among cluster actors, with the requirement that network indicators are observed before and after the implementation of the CDPs. While this particular analysis can assist in monitoring and assessing the process of coordination and its changes throughout the program, other qualitative and contextual information can also assist in interpreting the data and, thus, increase the reliability of results. However, in order to properly assess the impact of CDPs, their causality needs to be explored further by the application of additional quantitative methods. In fact, the effects cannot be attributed to the program itself, unless a proper counterfactual is built in, such as what would have happened to the beneficiaries in the absence of the program. By definition, this particular counterfactual cannot be observed, but the application of experimental and quasi-experimental techniques can help construct control groups of non-beneficiaries to approximate the counterfactual and assess the evidence with econometric techniques. Furthermore, a detailed observation of cases and specific interviews can help regarding the interpretation of results derived from these methods. The quantitative tools discussed herein are indeed complementary and not alternatives, with each applied as a means to strengthen the explanatory capacity of the other. Each tool requires specific and challenging data analysis that can be achieved with careful resource planning and the appropriate team skill set. The overarching objective is to build new and solid evidence on the effectiveness of CPDs and their respective policies.

Keywords: cluster development programs; policy evaluation; social network analysis

JEL-codes: O22; O25; O29; Z13

81 pages, June 16, 2014

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