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The role of skilled migrant workers in FDI-related technology transfer

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Abstract

In this paper, we analyse the role of skilled migrant workers holding managing and expert positions in the effective transfer of technology by multinational enterprises (MNEs) to their local affiliates. In the context of multiple treatments, i.e. foreign ownership and skilled migrant worker appointment, and based on propensity score matching and the difference-in-differences approach for matched employer–employee Slovenian firm level data for the 2002–2010 period, it is established that foreign-owned firms which, along with foreign direct capital inflow (FDI), appoint foreign skilled workers to managing or expert positions indeed perform better in TFP growth terms than firms that only experience FDI. The results are even more robust and significant where FDI activity is followed by the employment of a parent-country-national (PCN) manager, suggesting that expat managers play a key role in effectively transferring knowledge within MNEs. PCN managers and foreign experts appear to be crucial in explaining the productivity advantage over the domestic counterparts, with the former having a more immediate effect and the latter becoming important over a longer time. In contrast, no evidence was found regarding the technology transfer associated with either direct capital inflow alone or in connection with the employment of foreign unskilled workers.

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Notes

  1. Propensity score matching results of the multiple treatment model for the FDI-related employment of unskilled foreign and PCN workers are available from the authors upon request.

  2. In robustness check specifications, ebitda is excluded from the set of covariates for the sake of feasibility of the model estimations due to the decreased number of observations when extending the observation window. We opted to eliminate ebitda since the remaining covariates are more commonly considered in similar studies.

  3. In the rest of the paper the term propensity score matching will be used in the narrower sense, referring to the matching algorithm implemented under Stata teffects psmatch command.

  4. The probit model gives very similar and robust results, leading to identical conclusions.

  5. In the treatment model of foreign managers, the number of firms in the first treatment level drops from 1549 to 1479 and further to 1435, while the number of observations in the second treatment level falls from 134 to 122 and finally to 119, when the threshold is elevated to a 150% and 200% increase, respectively. In the PCN manager treatment model, the number of firms in the first treatment level drops from 1723 to 1643 and further to 1598, while the number of observations in the second treatment level decreases from 89 to 80 and finally to 77 with the threshold being raised to a 150% and 200% increase, respectively. Finally, in the treatment model of foreign experts, the number of firms in the first treatment level drops from 1629 to 1552 and further to 1509, while the number of observations in the second treatment level declines from 54 to finally 49 once the threshold is raised to a 150% and 200% increase, respectively.

  6. Balancing tests checking covariate balance for each of the model specifications are summarised in tables of results where we list the unbalanced covariates. They can be obtained from the authors upon request.

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Acknowledgements

We are grateful to Stefano Bolatto, Polona Domadenik, Marco Grazzi, Črt Kostevc and Alireza Naghavi for valuable discussions. We also benefited from helpful comments by participants at the research seminars at the University of Bologna, Department of Economics in November 2015, and the Institute of International Business, Shanghai University of International Business and Economics in June 2016, and the European Trade Study Group Conference held in Helsinki in 2016. Katja Zajc Kejžar also acknowledges financial support from the Slovenian Research Agency [research core funding No. (P5-0117)]. The usual disclaimer applies.

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Correspondence to Katja Zajc Kejžar.

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Appendix

Appendix

See Table 8.

Table 8 Summary statistics for the treatment models’ groups considering the employment of foreign managers, PCN managers and foreign experts (100% FDI-stock-increase benchmark)

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Golob Šušteršič, T., Zajc Kejžar, K. The role of skilled migrant workers in FDI-related technology transfer. Rev World Econ 156, 103–132 (2020). https://doi.org/10.1007/s10290-019-00360-3

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  • DOI: https://doi.org/10.1007/s10290-019-00360-3

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