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The contribution of university research to the growth of academic start-ups: an empirical analysis

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Abstract

The aim of this paper is to analyze empirically under which circumstances the universities located in a geographical area contribute to the growth of a special category of local new technology-based firms (NTBFs), those established by academic personnel (academic start-ups, ASUs). We examine the effects of a series of characteristics of local universities on the growth rates of ASUs and we compare them with the effects of the same university characteristics on the growth of other (i.e., non-academic) NTBFs. In the empirical part of the paper, we estimate an augmented Gibrat law panel data model using a longitudinal dataset composed of 487 Italian NTBFs observed from 1994 to 2003. Out of these NTBFs 48 are ASUs. The results of the econometric estimates suggest that universities do influence the growth rates of local ASUs, while the effects on the growth rates of other NTBFs are negligible. In particular, the scientific quality of the research performed by universities has a positive effect on the growth rates of ASUs; conversely the commercial orientation of research has a negative effect. These results indicate that universities producing high-quality scientific research have a beneficial impact on the growth of local high-tech start-ups, but only if these firms are able to detect, absorb, and use this knowledge. In this perspective, a greater commercial orientation of university research leading to a reduction of the knowledge available for absorption by these companies, can be detrimental.

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Notes

  1. Researchers are defined as individuals who perform research activities in public research organizations, regardless of the contractual link with the parent institution. They include the research staff of parent organizations (both full time and part time) and also Ph.D. students.

  2. It is fair to acknowledge that, following the extant literature, we may expect a number of traits of universities additional to those analyzed in this paper to influence the growth potential of local NTBFs. In particular, prior studies have shown that university policies regarding intellectual property, licensing strategies and characteristics of technology transfer offices may affect university-to-industry knowledge transfer (for a review of these studies see again Agrawal 2001). Hence, we may expect these characteristics to influence firms’ growth potential too; however we decided not to consider them in this work. In Italy policies and support infrastructures for technology transfer have started spreading after 2000 and have proliferated only in the last couple of years. Therefore, very few universities already exhibited such properties over the period 1994–2003 that we consider in this work. As a consequence, we could not capture the effect of these characteristics through the estimation of econometric models over this time horizon. Thus we excluded the study of these characteristics from both the empirical analysis and the development of the theoretical hypotheses.

  3. Unfortunately, data provided by official national statistics do not allow to obtain a reliable description of the universe of Italian NTBFs. The main problem is that in Italy most individuals who are defined as “self-employed” by official statistics actually are salaried workers with atypical employment contracts. Unfortunately, on the basis of official data such individuals cannot be distinguished from entrepreneurs who created a new firm.

  4. Note that for only three firms the set of owner-managers at survey date did not include at least one of the founders of the firm. For these firms information relating to the human capital characteristics of the founders was checked through interviews with firms’ personnel so as to be sure that it did not relate to current owner-managers.

  5. Following prior studies on the Italian case (Piergiovanni et al. 1997; Rodríguez-Pose and Refolo 2003) we use the province as the geographic unit of analysis. Although some of the largest Italian universities have campuses in different provinces (for instance, Politecnico di Milano has six campuses over the Lombardy region in five provinces and one campus in Emilia Romagna), in Table 2 for each university we consider the location of the main campus only. This allows us be consistent with the data reported in the following. In fact, all the data on the characteristics of Italian universities are available at university level only (i.e., they are not disaggregated by provinces). Hence, in order to measure the number of researchers, the quality of the knowledge produced and the commercial orientation of local universities for Italian provinces, for each university we have attributed all the researchers and, coherently, all the research activities to the main campus. As faculty members are mainly located in the main campus, this approximation can be considered reasonably accurate.

  6. In particular, considering LSize i,t−1 as endogenous implies the use of instruments dated t−3 for the equation in first differences and instruments dated t−2 for the equation in level.

  7. The economic faculties include economics, management, and political sciences, while the technical faculties are engineering, chemistry, physics, geology, mathematics, biology, medicine, pharmaceutics, and computer science.

  8. The first available data on the amount of financing of Italian universities refer to the fiscal year 2000. In fact, it was only in 2001 that the National Committee for the Evaluation of the Academic System (Comitato Nazionale per la Valutazione del Sistema Universitario, CNVSU) started collecting the financial accounts of Italian universities and making available aggregated data. The reports of the CNVSU on the fiscal years 2000 and 2001 classified the revenues of Italian universities in three categories: financing from MIUR (the Italian Ministry of University and Research), university internal funds and financing from external sources. Since the publication of the report on the fiscal year 2002, three subcategories have been distinguished within the “external sources” category: financing from the European Union, from other public research organizations and from other organizations. As we are interested in the share of research funded by the private sector, we have to focus on the last subcategory. Hence, in calculating %PrivateBudget, we could not use data on the fiscal years 2000 and 2001. Note that the category “financing from other organizations” includes both financing from firms and financing from other sources (e.g., foundations). However, the role of foundations in financing academic research in Italy was fairly limited in the observation period. Hence, even though %PrivateBudget is likely to overestimate financing from firms, absent more fine grained data, it can be considered as a reasonably good proxy.

  9. %PrivateBudget was calculated as the average value over two subsequent years in order to reduce random fluctuations. We are aware that this variable, being time-invariant, might generate biases that may distort the estimates. In particular, as financing to universities from the Italian Central Government has decreased during the last decade, universities have started looking for additional sources of income thus probably raising the share of funds from private sources out of the total budget. This increase might have been more relevant for northern provinces as the industrial system of this area is more developed and local companies are likely to be more prone to finance academic research. Therefore, our measure of %PrivateBudget might overestimate the commercial orientation of universities located in northern provinces in the first years of the period under scrutiny. As a consequence, if in this period the growth rates of NTBFs located in northern provinces were higher (lower) than those of the companies located elsewhere because of unobserved effects, the estimates of the coefficient of %PrivateBudget might reveal a upward (downward) bias.

  10. In small family-owned Italian companies decision authority is often centralized in the owner-managers’ hands (see Colombo and Delmastro 1999), while salaried managers are assigned execution tasks. So, entrepreneurial learning associated with such managerial positions generally is fairly limited.

  11. We also controlled for other characteristics of the provinces where sample NTBFs are located, namely provincial deflated GDP per capita, provincial deflated GDP per capita rescaled on a national basis and provincial population or provincial density of population. The results are almost unchanged. They are available from the authors upon request.

  12. As we mentioned in footnote 6, GMM-SYS estimate requires the use of instruments for LSize i,t−1 , (LSize i,t−1 )2 and LSize i,t−1 ×LAge i,t−1 dated t−3 for the equation in first differences. Hence, the sample used for the estimates presented in Tables 5 and 6 excludes all RITA NTBFs for which data on size were available for less than three consecutive years.

  13. It is fair to acknowledge that 95 out of the 487 NTBFs included in our sample are located in provinces where there were no universities in the period under consideration. For these firms all the variables measuring the characteristics of local universities are always equal to zero over the time horizon 1994–2003. As a check for robustness, we reestimated the models using only the data on the 392 firms located in provinces where at least one university existed. The results are almost unchanged. They are available from the authors upon request.

  14. For a similar argument in a different context see Klepper (2007).

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Acknowledgments

Support from the REBASPINOFF project promoted by the PRIME Network of Excellence, the PICO project (“Academic entrepreneurship, from knowledge creation to knowledge diffusion”, contract n°028928) sponsored by the Sixth Framework Programme, the FIRB 2003 fund, the PRIN 2006 project 2006132439_002 and a grant from Unicredit is gratefully acknowledged. The authors would like to thank E. Rasmussen, A. Hughes, the participants in the XX RENT conference, and two anonymous referees for their useful comments.

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  1. Politecnico di Milano, Department of Management, Economics and Industrial Engineering, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy

    Massimo G. Colombo, Diego D’Adda & Evila Piva

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Colombo, M.G., D’Adda, D. & Piva, E. The contribution of university research to the growth of academic start-ups: an empirical analysis. J Technol Transf 35, 113–140 (2010). https://doi.org/10.1007/s10961-009-9111-9

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