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Labor mobility from R&D-intensive multinational companies: implications for knowledge and technology transfer

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Abstract

Private sector R&D is largely concentrated in a few multinational companies (MNCs). The mobility of labor between these MNCs and the rest of the economy is therefore an important mechanism for the diffusion of knowledge and technology, but these flows are not without friction. This paper analyses in great detail the flow of labor between firms with specific emphasis on flows to and from R&D intensive MNCs. Using linked employer-employee data for Denmark, we match employees moving from R&D intensive MNCs to other employees switching jobs. We find that employees are more inclined to move between R&D intensive MNCs and their subsidiaries rather than between these firms and other firms in the economy. This is particularly true for high skill employees. Our results suggest that other domestic firms are to a larger extent kept out of the ‘knowledge spillover’ loop, which provides them with fewer opportunities to learn from the R&D intensive MNCs. In other words, R&D intensive MNCs and their subsidiaries form a kind of sub-labor market within the national labor market; employees exhibit higher mobility within this group of firms than between this group and the rest of the labor market.

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Notes

  1. In our analysis, we also run regression analysis on the unrestricted sample and on a sample only including R&D workers, where R&D workers are defined according to Kaiser et al. (2018), i.e. individuals that have a college degree in Science, Technology, Mathematics and Medicine (STEMM) and have an occupation with ISCO level 2 or 3. The findings are robust and details are available upon request.

  2. The full scoreboard is freely accessible at the webpage of the JRC-B3-IRITEC: http://iri.jrc.ec.europa.eu/home.

  3. Information on subsidiaries is obtained directly from Bureau van Dijk using the corporate structure of SB firms in the period 2012–2015. Overall, Scoreboard firms are linked to about 600,000 subsidiaries.

  4. The two numbers do not add up to 1191 as some subsidiaries change parent company from Danish SB to Foreign SB.

  5. The differences between the foreign SB subsidiaries and domestic SB firms and their subsidiaries cannot be attributed to the latter group including the 25 Danish SB firms themselves, as a large share of the SB firms appear very small in the registry data and are not covered by the Community Innovation Survey, cf. earlier. Instead, it indicates a corporate structure among SB firms where activities in the home country are separated into a number of distinct and legally independent firms, e.g. a large domestic SB firm may have a separate R&D subsidiary and not just a R&D department.

  6. To test whether we violate the IIA assumption, we apply a Hausman test especially designed for multinomial logistic analysis with clustered data (Weesie 2000). The Hausman test indicates that the IIA assumption is not violated, which means our specification is correct.

References

  • Agarwal, R., Gambardella, A., & Olson, D. M. (2016). Employee mobility and entrepreneurship. Strategic Management Journal, Virtual Special Issue, 37(13), E11–E21.

    Article  Google Scholar 

  • Almeida, P., & Kogut, B. (1999). Localization of knowledge and the mobility of engineers in regional networks. Management Science, 45(7), 905–917.

    Article  Google Scholar 

  • Audretsch, D. B., & Keilbach, M. (2005). The mobility of economic agents as conduits of knowledge spillovers. In The role of labour mobility and informal networks for knowledge transfer (pp. 8–25). Boston, MA: Springer.

  • Balsvik, R. (2011). Is labor mobility a channel for spillovers from multinationals? Evidence from Norwegian manufacturing. Review of Economics and Statistics, 93(1), 285–297.

    Article  Google Scholar 

  • Camerani, R., Rotolo, D., & Grassano, N. (2018). Do firms publish? A multi-sectoral analysis. JRC working papers on corporate R&D and innovation No. 5/2018. Joint Research Centre.

  • Campbell, B. A., Ganco, M., Franco, A. M., & Agarwal, R. (2012). Who leaves, where to, and why worry? Employee mobility, entrepreneurship and effects on source firm performance. Strategic Management Journal, 33(1), 65–87.

    Article  Google Scholar 

  • Ciabuschi, F., Martín, O. M., & Ståhl, B. (2010). Headquarters’ influence on knowledge transfer performance. Management International Review, 50(4), 471–491.

    Article  Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152.

    Article  Google Scholar 

  • Crespo, P., & Fontoura, M. P. (2007). Determinant factors of FDI spillovers: What do we really know? World Development, 35, 410–425.

    Article  Google Scholar 

  • Csáfordi, Z., Lőrincz, L., Lengyel, B., & Kiss, K. M. (2020). Productivity spillovers through labor flows: Productivity gap, multinational experience and industry relatedness. Journal of Technology Transfer, 45(1), 86–121.

    Article  Google Scholar 

  • Davis, S. J., Haltiwanger, J., Katz, L. F., & Topel, R. (1991). Wage dispersion between and within U.S. manufacturing plants, 1963–86. Brookings Papers on Economic Activity. Microeconomics, 1991, 115–200.

    Article  Google Scholar 

  • Dernis, H., Gkotsis, P., Grassano, N., Nakazato, S., Squicciarini, M., van Beuzekom, B., & Vezzani, A. (2019). World corporate top R&D investors: Shaping the future of technologies and of AI (No. JRC117068). Joint Research Centre (Seville site).

  • Di Ubaldo, M., Lawless, M., & Siedschlag, I. (2018). Productivity spillovers from multinational activity to indigenous firms in Ireland. ESRI working paper 587.

  • Falck, S. (2016). Foreign-to-domestic labour mobility in Sweden. Regional Science Policy & Practice, 8(3), 111–125.

    Article  Google Scholar 

  • Görg, H., & Strobl, E. (2005). Spillovers from foreign firms through worker mobility: An empirical investigation. Scandinavian Journal of Economics, 107(4), 693–709.

    Article  Google Scholar 

  • Guerrero, O. A., & Axtell, R. L. (2013). Employment growth through labor flow networks. PLoS ONE, 8(5), 1–12.

    Article  Google Scholar 

  • Guevara, H. H., Soriano, F. H., Tuebke, A., Vezzani, A., Dosso, M., Amoroso, S., Grassano, N., Coad, A., & Gkotsis, P. (2015). The 2015 EU industrial R&D investment scoreboard (No. JRC98287). Joint Research Centre (Seville site).

  • Haltiwanger, J., Hyatt, H., & McEntarfer, E. (2018a). Who moves up the job ladder? Journal of Labor Economics, 36(S1), S301–S336.

    Article  Google Scholar 

  • Haltiwanger, J. C., Hyatt, H. R., Kahn, L. B., & McEntarfer, E. (2018b). Cyclical job ladders by firm size and firm wage. American Economic Journal: Macroeconomics, 10(2), 52–85.

    Google Scholar 

  • Hijzen, A., & Swaim, P. (2008). Do multinationals promote better pay and working conditions? The effect multinationals have on wages and working conditions can be positive, but there are conditions to bear in mind, not least for policymakers wishing to attract foreign direct investment. OECD Observer, 269, 15–18.

    Google Scholar 

  • Hilbe, J. M. (2009). Logistic regression models. London: Chapman and Hall.

    Book  Google Scholar 

  • Holm, J. R., Timmermans, B., & Østergaard, C. R. (2017). The impact of multinational R&D spending firms on job polarization and mobility. JRC Technical Report, JRC108560, Luxembourg, Publications Office of the European Union. https://doi.org/10.2760/28345.

  • Iacus, S. M., King, G., & Porro, G. (2012). Causal inference without balance checking: Coarsened exact matching. Political Analysis, 20(1), 1–24.

    Article  Google Scholar 

  • Kaiser, U., Kongsted, H. C., Laursen, K., & Ejsing, A. K. (2018). Experience matters: The role of academic scientist mobility for industrial innovation. Strategic Management Journal, 39(7), 1935–1958.

    Article  Google Scholar 

  • Kaiser, U., Kongsted, H. C., & Rønde, T. (2015). Does the mobility of R&D labor increase innovation? Journal of Economic Behavior & Organization, 110, 91–105.

    Article  Google Scholar 

  • Lengyel, B., & Eriksson, R. H. (2017). Co-worker networks, labour mobility and productivity growth in regions. Journal of Economic Geography, 17(3), 635–660.

    Google Scholar 

  • Lenzi, C. (2010). Workers’ mobility and patterns of knowledge diffusion: Evidence from Italian data. The Journal of Technology Transfer, 35(6), 651–670.

    Article  Google Scholar 

  • Mincer, J., & Jovanovic, B. (1981). Labor mobility and wages. In R. Shervin (Ed.), Studies in labor markets. Chicago: University of Chicago Press.

    Google Scholar 

  • Narula, R., & van der Straaten, K. (2019). A comment on the multifaceted relationship between multinational enterprises and within-country inequality (No. 035). United Nations University-Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

  • Oi, W. Y., & Idson, T. L. (1999). Firm size and wages. In O. Ashenfelter & D. Card (Eds.), Handbook of labor economics (Vol. 3B, pp. 2165–2214). Amsterdam: Elsevier.

    Google Scholar 

  • Palomeras, N., & Melero, E. (2010). Markets for inventors: Learning-by-hiring as a driver of mobility. Management Science, 56(5), 881–895.

    Article  Google Scholar 

  • Poole, J. P. (2013). Knowledge transfers from multinational to domestic firms: Evidence from worker mobility. Review of Economics and Statistics, 95(2), 393–406.

    Article  Google Scholar 

  • Rahko, J. (2017). Knowledge spillovers through inventor mobility: The effect on firm-level patenting. The Journal of Technology Transfer, 42(3), 585–614.

    Article  Google Scholar 

  • Siegel, D. S., & Wessner, C. (2012). Universities and the success of entrepreneurial ventures: Evidence from the small business innovation research program. Journal of Technology Transfer, 37(4), 404–415.

    Article  Google Scholar 

  • Siegel, D. S., & Wright, M. (2007). Intellectual property: The assessment. Oxford Review of Economic Policy, 23(4), 529–540.

    Article  Google Scholar 

  • Sofka, W., Preto, M. T., & de Faria, P. (2014). MNC subsidiary closures: What is the value of employees’ human capital in new jobs? Journal of International Business Studies, 45(5), 723–750.

    Article  Google Scholar 

  • Song, J., Almeida, P., & Wu, G. (2003). Learning-by-hiring: When is mobility more likely to facilitate interfirm knowledge transfer? Management Science, 49(4), 351–365.

    Article  Google Scholar 

  • Sorkin, I. (2018). Ranking firms using revealed preference. Quarterly Journal of Economics, 133(3), 1331–1393.

    Article  Google Scholar 

  • Stoyanov, A., & Zubanov, N. (2014). The distribution of the gains from spillovers through worker mobility between workers and firms. European Economic Review, 70, 17–35.

    Article  Google Scholar 

  • Weesie, J. (2000). Seemingly unrelated estimation and the cluster-adjusted sandwich estimator. Stata Technical Bulletin, 9(52), 231–248.

    Google Scholar 

  • Wright, M., Tartari, V., Huang, K. G., Di Lorenzo, F., & Bercovitz, J. (2018). Knowledge worker mobility in context: Pushing the boundaries of theory and methods. Journal of Management Studies, 55(1), 1–26.

    Article  Google Scholar 

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Acknowledgements

Some of the ideas in this paper were previously explored on less recent data in a European Commission technical report (see Holm et al. 2017). We are grateful to seminar participants at the Fifth International workshop in Inter-Industry Relatedness in The Hague (NL), 2018, and also to the Editor (Al Link) and two anonymous reviewers, for many helpful comments and suggestions. The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission. The usual caveat applies.

Author information

Authors and Affiliations

  1. Department of Business and Management, Aalborg University, Aalborg, Denmark

    Jacob Rubæk Holm, Bram Timmermans & Christian Richter Østergaard

  2. Department of Strategy and Management, Norwegian School of Economics, Bergen, Norway

    Bram Timmermans

  3. CENTRUM Católica Graduate Business School (CCGBS), Lima, Peru

    Alex Coad

  4. Pontificia Universidad Católica del Perú (PUCP), Lima, Peru

    Alex Coad

  5. Unit B.3 Territorial Development, European Commission JRC Directorate B - Growth and Innovation, Seville, Spain

    Nicola Grassano

  6. Department of Economics, Roma Tre University, Rome, Italy

    Antonio Vezzani

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  1. Jacob Rubæk Holm
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Appendix: mobility analysis on movers

Appendix: mobility analysis on movers

 

Model A1

Model A2

Model A3

Variables

SB firm

SB firm

Foreign SB firm

Domestic SB firm

CEM

Sample

Sample

Sample

Sample

Industry and region FE

Yes

Yes

Yes

Yes

Scoreboard firm (any)

0.9699***

   

(0.079)

   

Scoreboard firm (domestic)

 

1.0598***

0.4158*

1.2817***

 

(0.115)

(0.183)

(0.148)

Scoreboard firm (foreign)

 

0.9119***

1.0084***

0.8017***

 

(0.091)

(0.113)

(0.125)

Gender

0.0132

0.0122

− 0.0829

0.0959+

(0.040)

(0.040)

(0.061)

(0.051)

Age

− 0.0171**

− 0.0170**

− 0.0082

− 0.0268***

(0.005)

(0.005)

(0.008)

(0.007)

Education (years)

0.0642***

0.0639***

0.0133

0.1047***

(0.009)

(0.009)

(0.012)

(0.012)

Experience (years)

0.0091

0.0091

0.0088

0.0114

(0.006)

(0.006)

(0.009)

(0.008)

Tenure (in previous firm)

− 0.0143**

− 0.0147**

− 0.0212***

− 0.0085

(0.005)

(0.005)

(0.006)

(0.006)

ln (hourly_wage)

0.3640***

0.3680***

0.4118***

0.3492***

(0.054)

(0.054)

(0.074)

(0.068)

occuH

0.4118***

0.4157***

0.4716***

0.3777***

(0.058)

(0.058)

(0.078)

(0.079)

occuM

0.1352*

0.1352*

0.2219**

0.0609

(0.064)

(0.064)

(0.086)

(0.092)

ln (employment_size)

0.0796***

0.0757***

0.0263+

0.1165***

(0.014)

(0.015)

(0.016)

(0.022)

Constant

− 4.6820***

− 4.6768***

− 5.4780***

− 5.4496***

(0.315)

(0.316)

(0.446)

(0.413)

Observations

55.537

55.537

55.567

55.567

Pseudo-R2

0.143

0.143

0.145

0.145

Log Likelihood

− 17,194

− 17,190

− 20,966

− 20,966

  1. Robust standard errors in parentheses. ***p < 0.001. **p < 0.01. *p < 0.05. +p < 0.1

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Holm, J.R., Timmermans, B., Østergaard, C.R. et al. Labor mobility from R&D-intensive multinational companies: implications for knowledge and technology transfer. J Technol Transf 45, 1562–1584 (2020). https://doi.org/10.1007/s10961-020-09776-8

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