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Temporary expats for exports: micro-level evidence

Abstract

We analyze the relation between temporary expats in firms and exports, exploiting micro-level panel data on migration and trade. Temporary expats are positively associated with exports. Their link with export intensity is larger for services than for merchandise and for exports of differentiated services and merchandise than for exports of homogeneous products. Our evidence also suggests that temporary expats are positively related to exports by assisting firms in overcoming informal destination-specific barriers. Overall, our findings suggest the importance of the temporary movement of persons for providing firms with up-to-date links to export markets.

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Notes

  1. 1.

    In addition to case studies and some limited empirical studies (e.g., Denstadli et al. 2013; Gustafson 2012; National Board of Trade 2013b; Westermark 2013; The Economist 2014a), this emphasis is indicated in business surveys regarding meetings and obstacles to trade (Harvard Business Review 2009; Kneller and Pisu 2011).

  2. 2.

    The Swedish multinational SKF, cited in National Board of Trade (2013b, p. 10). The Economist (2014b) also highlights the importance of avoiding "bumpkinism" for the performance of multinational firms, such as by promoting cosmopolitan management and cross-country mobility within corporations.

  3. 3.

    As is displayed in Fig. 4 of the "Appendix".

  4. 4.

    In a meta-analysis of the literature on migration and trade in merchandise, the elasticity of trade to immigration is estimated to be approximately 0.15 on average (Genc et al. 2011).

  5. 5.

    Another segment of the literature analyzes the role of travel for trade in goods (e.g., Kulendran and Wilson 2000; Poole 2009). One recent study finds the elasticity of US exports to business travel to be 0.46 using data on trade with 21 countries in the 1996–2009 period (Riker and Belenkiy 2012). Temporary movement in the form of tourism may also promote trade, for example, through the discovery of new goods or services (e.g., Brau and Pinna 2013; Quinn 2009). Most recently, Brau and Pinna (2013) analyze the effect of moving people to move goods by regressing the exports of goods of the 25 countries of the European Union (EU) on international tourist arrivals in the 1998–2009 period. They find that tourism is positively associated with exports of consumption goods, with an elasticity of 0.05, but the link to non-final goods is small, negative and, in most cases, not statistically significant.

  6. 6.

    See, e.g., Lopez 2009; Labanca et al. 2014; Minondo 2011; Sala and Yalcin 2015; Mion and Opromolla 2014; Koenig et al. 2010; Choquette and Meinen 2015; Malchow-Møller et al. 2013; and Munch and Skaksen 2008.

  7. 7.

    Additionally, Malchow-Møller et al. (2011) touch on the export impact of hiring foreign experts under a particular tax regime in Denmark, while focusing on the link between experts and productivity. They find a productivity effect and a contemporaneous impact on export entry and a prolonged impact on export intensity. However, the number of foreign experts included in the study is small, relative to this study, and their focus is not on destination-specific knowledge transfer or the bilateral trade dimension more generally.

  8. 8.

    Herander and Saavedra (2005) demonstrate the importance of proximity for migrants’ effect on trade using state-level US data, whereas Aleksynska and Peri (2014) exploit detailed and pooled cross-sectional data at the macro-level to show that migrants in certain occupational groups that are expected to have more of an influence on business account for an additional effect on trade. More generally, social networks and proximity are considered conducive to knowledge transfer, as discussed by Inkpen and Tsang (2005) and empirically demonstrated by Head et al. (2014).

  9. 9.

    We hypothesize that temporary expats are akin to the “sociometric stars” of Milgram (1967)—persons who were particularly useful in linking to distant agents—but in the foreign exports context.

  10. 10.

    That firm trade is limited in terms of the number of services traded or foreign markets that are served also suggests that there are substantial entry barriers in services trade (e.g., Haller et al. 2014). The presence of substantial barriers is also indicated by the fact that almost half of all firms in a survey by the Swedish Trade Council (2010) regarded public assistance with market surveys, establishment and recruitment as key to boost the exports of services.

  11. 11.

    The main explanation is likely to be that detailed statistics on trade in services have been absent until recently, and they are still relatively general in comparison with statistics on trade in goods.

  12. 12.

    Since the early 1990s, the share of services in total Swedish exports has increased, and since the early 2000s the country has been a net exporter of services and also steadily gained world market shares.

  13. 13.

    As is displayed in Fig. 5 in the "Appendix". We may add that the category of other business services, excluding merchanting, mainly is composed of head quarter services, such as management, educational, administrative and recruitment services; R&D services; and technical services, such as architect and engineering services (Swedish Trade Council 2010).

  14. 14.

    This fact is arguably related to the servicification of Swedish manufacturing (Lodefalk 2013, 2014).

  15. 15.

    For example, being part of a multinational corporation is positively associated with firm exports, which may at least partly be due to the international experience of the corporation.

  16. 16.

    The model incorporates features of Carayol and Roux (2009) into a firm model of trade, drawing heavily on Cristea (2011). The model is advantageous in considering the social embeddedness of the firm, which, in estimation, would otherwise introduce potential omitted-variable bias.

  17. 17.

    Alternatively, the specific appeal could be attached to the business relation.

  18. 18.

    The firm maximizes profits and arrives at the following log-linearized export revenue function: \( \ln r_{ihj}^{ *} \left( \varphi \right) = \ln c_{ih} + \ln i_{ihj}^{ *} \left( \varphi \right) + \ln \sigma - \ln \theta_{h} \), where \( r_{ihj} \) is revenue from exports of the firm in country i, in sector h, to country j, \( c_{ih} \) is the unit cost of the service of links to foreign networks, \( i_{ihj} \) is the investment in services of links, \( \sigma \) is the CES between varieties of a product, and \( \theta_{h} \) denotes informational frictions in sector h. In turn, \( i_{ihj} \) is negatively affected by investment by other firms in the vicinity of the firm under parameter assumptions in line with Carayol and Roux (2009).

  19. 19.

    Anecdotal evidence suggests that even blue-collar workers can be instrumental in firm internationalization, through their knowledge of foreign languages, information and contacts.

  20. 20.

    However, temporary expats are expected to be less integrated in the host country, which may reduce their ability to link agents. Nonetheless, such a negative bias is more primarily applicable to temporary expats who are entrepreneurs than for temporary expats who are employed in a host country firm, which has its own domestic network.

  21. 21.

    Access to foreign social networks may be useful for reasons other reasons than primarily fostering exports, such as acquiring skills, improving learning, or improving management (Podolny and Page 1998).

  22. 22.

    Empirically, this is, e.g., in line with Markusen and Trofimenko (2009) and Bitzer et al. (2014). The latter study explores Danish micro-level data, and concludes that immigrant employees bring-in human capital that promotes firm output. In addition to the potential importance of specific human capital from abroad, there is a small related body of literature that explores the impact of ethnic diversity on economic performance in terms of productivity or innovation. The results are mixed (e.g., Parrotta et al. 2014a, b; Alesina and Ferrara 2005; Peri 2012). Parrotta et al. (2014a) find that diversity is negatively linked to productivity in Danish firms with at least ten employees in the 1995–2005 period, with diversity measured in the form of a Herfindahl index that is based on statistics on the classification of employees as belonging to one of eight country groups. Parrotta et al. (2014b) use similar data and conclude that ethnic diversity is positively associated with firm innovation.

  23. 23.

    Estimating the log-linear export revenue function of HL’s theoretical model necessitates scarce data on information frictions and unit costs of the services of temporary expats across countries and industries while omitting known export determinants, such as firm size and multinational status. We therefore add fixed effects that capture variables for which data are scarce and key firm-level and gravity variables that are omitted from the parsimonious model of HL.

  24. 24.

    The variable corresponds to the idiosyncratic demand shock of HL’s theoretical framework.

  25. 25.

    However, comfortingly, the correlations between covariates and expats are found to be weak in our panel dataset.

  26. 26.

    Additional analysis demonstrates that the results are robust to using alternative or no lags; see, e.g., Table B2–B3. Henceforth, please note that figures and tables that have prefix A are available in the "Appendix", and those with prefix B are in the online appendix at www.oru.se/personal/magnus_lodefalk/.

  27. 27.

    In the robustness analysis, we also add destination-country-year-specific effects, which stretch the limits of the computational resources we access. One advantage of doing so is that, for example, this approach controls for the short-time movement of persons, such as business visitors from country i in country j.

  28. 28.

    The underlying the dataset is a register-based linked employer–employee dataset, which has been aggregated to the firm level by Statistics Sweden for reasons of confidentiality.

  29. 29.

    We may add that during the studied period, there was a threshold for recording trade in goods with the rest of the EU amounting to 1.5 mn SEK per year in the 1998–2004 period, and 4.5 mn SEK thereafter. Our results are robust to this threshold (Table B14). For trade in services, there was a threshold of 150,000 SEK per cross-border transaction with any country up to year 2002, which later was been removed.

  30. 30.

    Another advantage of using population registers is that physical flows are captured, whereas data on permits capture approved applications that might never ultimately be used.

  31. 31.

    The online appendix is available at www.oru.se/personal/magnus_lodefalk/.

  32. 32.

    To be more specific with respect to the requirement of time in Sweden and the contractual relationship with a firm in Sweden, we expect to capture persons who have been in Sweden <4 years after their most recent arrival and for whom two additional conditions are fulfilled, as explained below. With regard to the time limit, to the best of our knowledge, firms consider postings or secondments for presence in the host country of <4 years, else regular employment. With respect to the additional conditions, first, expats need to be expected to stay in Sweden at least a year with some regularity, where regularity means the equivalent of a weekly stay-over during the rest of the year. Second, they must have been reported to Inland Revenue (IR). The first requirement is related to being registered as a resident in Sweden. Being registered as a resident is almost a necessity for a temporary expat in Sweden, even when the person only intends to stay for a relatively short time. The reason is that residency status qualifies a person to receive a personal ID number, which every native is automatically given at birth, including returning Swedish expats. Only with such a number is it possible to easily conduct everyday life in Sweden. The personal ID number is commonly needed when renting a car, collecting an item at the post office, renting a flat, opening a bank account, etc. (National Board of Trade 2013a). Consequently, firms in Sweden that host persons on secondment typically assist in the registration of these persons as residents, for example, as part of a reallocation agreement. The second requirement is fulfilled for persons who come to Sweden for employment and commonly for persons on secondment in Sweden. Persons on secondment retain their employment and often their salary (or part thereof) from abroad, but they are also registered as employees in the hosting firm. As employees, they are normally reported to IR by the hosting firm in Sweden and must be reported if a benefit of any kind is provided to them, such as accommodations or a business car.

  33. 33.

    Five of the top ten source countries of immigrants living in Sweden in 2007 were countries beset by conflict. Our classification is based on merged data for the 1968–2007 period from the Uppsala Conflict Database Program (UCDP 2014a, b, c, d). For general information about the UCDP, see http://www.pcr.uu.se/research/ucdp/program_overview/about_ucdp/.

  34. 34.

    Using a narrower definition reduces the number of conflict countries by a third, yet hardly alters estimation results (Table B4). The narrower definition only assigns the conflict label if the government of the country is itself involved in the armed conflict and the cumulative number of battle-related deaths also exceeds 1000 persons in the period of the study.

  35. 35.

    Our discussions with businesses suggest that most temporary movers stay at least a year and that approximately 90 % of them subsequently leave the country.

  36. 36.

    In December 2012, 93 % of valid residence permits were for purposes of remuneration, and 49 % of the new permits issued during that year consisted of permits for 12 months or longer, with approximately half of the EU member states mostly issuing new permits for long durations. However, a caveat is that that information is lacking on the duration of EU professionals’ stay in other member countries given that they do not need a work permit. However, for the reasons explained above, postings in Sweden normally imply the need for a personal identification number. Therefore, EU professionals are expected to register as residents and employees and thus are included in our dataset.

  37. 37.

    In the period studied, on average, 52 % of temporary expats were employed in firms that export.

  38. 38.

    Table B5.

  39. 39.

    If only non-conflict countries are included, the top 10 source countries of temporary expats to Sweden are Poland, Norway, Germany, Finland, Denmark, France, the Netherlands, Australia, Lithuania, and Switzerland. Nine and eight of these countries are among the top 15 destinations for Swedish exports of merchandise and services, respectively. Seven of the source countries of temporary expats are also among the top source countries of permanent expats.

  40. 40.

    Together with other evidence in this section, it therefore seems as if temporary expats are hired for their country-specific (or general) skills, rather than, for example, to reduce the wage bill of firms.

  41. 41.

    Tables B7–8.

  42. 42.

    The results are consistent with the finding in Labanca et al. (2014) that hiring from exporters is much more common among firms that are engaged in the exports of merchandise.

  43. 43.

    In the 1998–2002 period 14,826 firm-country dyads entered into exports of services for the first time. 573 of those dyads hired their first temporary expat at entry, corresponding to approximately 4 % of the entrance dyads.

  44. 44.

    Looking at all firms, we discern a similar pattern in which the total number of temporary (and permanent expats) increases before and decreases after export entry.

  45. 45.

    To avoid truncation, we define the response variable as \( x_{fjt - 0} = \ln \left( {export\,value + 1e^{ - 7} } \right) \); This is practical since our within-firm-country estimations already are very demanding. Furthermore, this approach is commonly adopted in the literature (Eichengreen and Irwin 1995; Dunlevy 2006; Lewer 2006; Peri and Requena-Silvente 2010; Bratti et al. 2014; Coughlin and Wall 2011; Artal-Tur et al. 2012). In essence, the approach mimics a semi-log Tobit (Eichengreen and Irwin 1995; Dunlevy and Hutchinson 1999). We expect it only to imply a minor measurement error, since our trade flows are measured in thousands of SEK rather than in millions or billions of US dollars, see Liu (2009). Reassuringly, we find the results only to be marginally different from those of panel selection model estimations, see Table 10.

  46. 46.

    Estimation output from a step-by-step construction of the full specification is available in Table B2–3 and B10. We find the coefficients of interest to be very robust across specifications.

  47. 47.

    Key control variables have the expected signs in comparison with previous within-estimations of firm-level gravity models, which largely focus on trade in merchandise. A firm exports more the larger the market is, and firms export more the more efficient the firm is and the larger its workforce is. As for the negative sign of the indicator of multinational status, in Column 1, the sign is related to the lagged structure of the specification and the inclusion of fixed effects. Additional analysis shows that becoming part of a multinational promotes the intensity of services exports in the current year, but not 2 years later. We interpret this finding to mean that firms gradually accommodate to their new opportunities of serving the foreign market through foreign affiliates, substituting it for other modes of delivery, which would seem to be particularly attractive for services sales. The results are in line with previous findings that becoming a multinational has heterogeneous effects on exports (e.g., Greenaway and Kneller 2007; Girma and Kneller 2008).

  48. 48.

    Additional Probits estimations, using a Mundlak–Chamberlain device that controls for unobserved heterogeneity, reveals a generally positive but small link between temporary expats and the propensity to export merchandise, while for exports of services such a link only exists for subsets of exporters, such as previous non-exporters of services (Table B11), or for subsets of destinations (Mundlak 1978; Chamberlain 1980).

  49. 49.

    Hatzigeorgiou and Lodefalk (2016) provide a brief overview of previous findings in the migration and trade literature on the issue as well as a new survey. Additionally, a recent natural experimental study on bilateral data suggests a causal effect of migration on trade (Parsons and Vézina 2014). Together, this evidence seems to indicate that the relation goes from migration to trade and, at the very least, from migration to realized trade flows. Finally, it can be noted that a system of tax cuts for scarce labor (such as business leaders, experts and researchers) was introduced in Sweden during the period of time that we study, stimulating the temporary movement of persons to Sweden for work and potentially affecting subsequent exports, rather than vice versa.

  50. 50.

    We thank a reviewer for this suggestion.

  51. 51.

    In the DiD analysis, we exploit both between and within variation.

  52. 52.

    First-stage results are displayed in Table B12, and they suggest that the second instrument in particular—the average number of temporary expats employed in other firms in the same three-digit industry as firm f—is strongly and positively associated with temporary expats, while being significant at the 1 % level.

  53. 53.

    That GMM estimates are larger than, e.g., pooled OLS estimates is not uncommon (e.g., Angrist and Pischke 2009; Malchow-Møller et al. 2013; Hiller 2013). An explanation for such differences in the present study may be that the exploited variation likely differs non-trivially between the pooled OLS and the GMM estimations. Whereas the instruments capture variation at the industry and/or industry-country level, the instrumented variable does so at the firm-country level.

  54. 54.

    Alternative instruments, including permanent expats, have been considered and experimented with as instruments, and in different combinations. The results are consistent with the presented ones. However, considering identification and the orthogonality requirements, only the already presented results hold.

  55. 55.

    In the classification of merchandise as differentiated, we follow Rauch (1999), whereas for services, we draw on industry classifications that consider occupational composition in industries and their corresponding skill requirements (O'Mahony and van Ark 2003; Peneder 2007). Presumably, differentiated services are predominantly produced by employees in occupations that require high skills.

  56. 56.

    In brief, the trade indicator is the difference between a measure of the relative absence of weighted tariff levels above the world minimum and a measure of the absence of non-tariff measures for goods and services.

  57. 57.

    Unfortunately, these indicators of informal barriers, like most other such indicators currently available, are cross-sectional and limited in terms of country coverage. Therefore, fewer countries can be included in estimation and we have to replace country-specific with region-specific effects, when considering unobserved destination-specific heterogeneity.

  58. 58.

    Estimations that consider good governance—proxied by an indicator that is the average of ten ratings in areas such as rule of law and open markets—only display insignificant, albeit negative, coefficients (Heritage Foundation 2014).

  59. 59.

    Z-tests confirm that the differences are statistically significant at the 7 and 5 % level for services and merchandise, respectively.

  60. 60.

    Also when estimating an unlagged specification for firms that export to one or at most two markets, we find a positive and statistically significant association between temporary expats and exports. The result would seem to further corroborate that temporary expats provide foreign links that promote export, rather than, e.g., merely being proxies for within-firm reallocation of resources used to supply for different foreign markets. I thank Håkan Nordström for suggesting this analysis.

  61. 61.

    Other potential sensitivities of the specification and the dataset are analyzed in additional estimations using alternative specifications and subsamples, with results available in Table B14. Throughout, the results seem to corroborate a positive and statistically significant link between temporary expats and exports.

  62. 62.

    For the full estimation results for the target equation and the preceding 16 yearly selection equations, see Tables B15–16.

  63. 63.

    Additionally, we control for heterogeneous effects of temporary expats across industries.

  64. 64.

    In an evaluation of different approaches to zeros, Gómez-Herrera (2013) conclude that a sample selection model is to prefer over other non-linear approaches, including a Pseudo-Poisson-Maximum-Likelihood model, when there is unobserved heterogeneity and heteroscedasticity.

  65. 65.

    Hatzigeorgiou and Lodefalk (2016) describe the construction of the measure in detail.

  66. 66.

    The difference is statistically significant at the 10 % level.

  67. 67.

    Doubling the number of temporary expats would roughly correspond to each firm in our sample hiring an additional temporary expat.

  68. 68.

    Figure 6 in the “Appendix” presents recent OECD data that display an indicator of the restrictiveness across groups of countries of the temporary movement of persons for the provision of services. The indicator only captures formal barriers such as bans, quotas and limits, which are delineated in official documents. Other aspects, such as waiting times, visa restrictions, and the uncertainty involved in the process, are not considered. With respect to visa restrictions, i.a., using panel data for Spain, Bertoli and Fernández-Huertas Moraga (2013) and Bertoli and Fernández-Huertas Moraga (2012) find that visa requirements substantially reduce and divert migration flows. An additional restriction is constituted by mandatory licensing to work in specific professions. According to The Economist (2014c), approximately one-third of workers in the Unites States today need a license, whereas only one in 20 needed it in the 1950s. In Sweden, there are at least 40 occupations that are regulated by law (UHR 2014).

  69. 69.

    An illustrative example is Massive Entertainment, a fast-growing firm in the Swedish computer game industry. It currently employs 300 persons from 26 countries and continuously needs scarce gaming specialists (Holm 2014). The firm must wait up to 12 months for work permits for foreign specialists and, in the meantime, does not receive any information on the status of the applications. As a result, the firm loses potential foreign specialists and oftentimes must resort to bought-in services or consultants. Another example is the British digital finance firm Wonga, which intended to expand its operations in the United Kingdom (The Economist 2013). Instead, the firm opted to open offices abroad because of the combination of scarce native talent and tough immigration rules. More generally, surveys among multinational corporations suggest that the temporary movement of people implies substantial risks of accidental violations of government policies, thereby incurring penalties (EY 2009, 2013a, b). Moreover, the majority of obstacles to factor flows within the EU (69 %) involve the movement of people (EU 2013).

References

  1. Aleksynska, M., & Peri, G. (2014). Isolating the network effect of immigrants on trade. The World Economy, 37(3), 434–455. doi:10.1111/twec.12079

    Article  Google Scholar 

  2. Alesina, A., & Ferrara, E. L. (2005). Ethnic diversity and economic performance. Journal of Economic Literature, 43(3), 762. doi:10.1257/002205105774431243

    Article  Google Scholar 

  3. Andrews, M., Schank, T., & Upward, R. (2006). Practical fixed-effects estimation methods for the three-way error-components model. Stata Journal, 6(4), 461.

    Google Scholar 

  4. Angrist, J. D., & Pischke, J.-S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton: Princeton University Press.

    Google Scholar 

  5. Artal-Tur, A., Pallardó-López, V. J., & Requena-Silvente, F. (2012). The trade-enhancing effect on immigration networks: New evidence on the role of geographic proximity. Economics Letters, 116(3), 554–557.

    Article  Google Scholar 

  6. Arvis, J.-F., Duval, Y., Shepard, B., & Utoktham, C. (2013). Trade costs in the developing world: 1995–2010 (World Bank Policy Researh Working Paper No. 6309). Washington: The World Bank.

  7. Bertoli, S., & Fernández-Huertas Moraga, J. (2012). Visa policies, networks and the cliff at the border (IZA Discussion Paper 7094). Bonn: Institute for the Study of Labor.

  8. Bertoli, S., & Fernández-Huertas Moraga, J. (2013). Multilateral resistance to migration. Journal of Development Economics, 102, 79–100. doi:10.1016/j.jdeveco.2012.12.001

    Article  Google Scholar 

  9. Bitzer, J., Gören, E., & Hiller, S. (2014). International knowledge spillovers: The benefits from employing immigrants (Working Paper Series in Economics 323). University of Lüneburg, Institute of Economics.

  10. Bratti, M., De Benedictis, L., & Santoni, G. (2014). On the pro-trade effects of immigrants. Review of World Economics/Weltwirtschaftliches Archiv, 150(3), 557–594. doi:10.1007/s10290-014-0191-8

    Article  Google Scholar 

  11. Brau, R., & Pinna, A. M. (2013). Movements of people for movements of goods? The World Economy, 36(10), 1318–1332. doi:10.1111/twec.12104

    Article  Google Scholar 

  12. Carayol, N., & Roux, P. (2009). Knowledge flows and the geography of networks: A strategic model of small world formation. Journal of Economic Behavior & Organization, 71(2), 414–427. doi:10.1016/j.jebo.2009.02.005

    Article  Google Scholar 

  13. Chamberlain, G. (1980). Analysis of covariance with qualitative data. The Review of Economic Studies, 47(1), 225–238.

    Article  Google Scholar 

  14. Choquette, E., & Meinen, P. (2015). Export spillovers: Opening the black box. The World Economy, 38(12), 1912–1946. doi:10.1111/twec.12225

    Article  Google Scholar 

  15. Coughlin, C. C., & Wall, H. J. (2011). Ethnic networks and trade: Intensive versus extensive margins. Economics Letters, 113(1), 73–75. doi:10.1016/j.econlet.2011.05.023

    Article  Google Scholar 

  16. Cristea, A. D. (2011). Buyer–seller relationships in international trade: Evidence from U.S. States’ exports and business-class travel. Journal of International Economics, 84(2), 207–220. doi:10.1016/j.jinteco.2011.02.003

    Article  Google Scholar 

  17. Denstadli, J. M., Gripsrud, M., Hjorthol, R., & Julsrud, T. E. (2013). Videoconferencing and business air travel: Do new technologies produce new interaction patterns? Transportation Research Part C: Emerging Technologies, 29, 1–13. doi:10.1016/j.trc.2012.12.009

    Article  Google Scholar 

  18. Dunlevy, J. A. (2006). The influence of corruption and language on the protrade effect of immigrants: Evidence from the American States. The Review of Economics and Statistics, 88(1), 182–186. doi:10.1162/003465306775565792

    Article  Google Scholar 

  19. Dunlevy, J. A., & Hutchinson, W. K. (1999). The impact of immigration on American import trade in the late nineteenth and early twentieth centuries. The Journal of Economic History, 59(4), 1043–1062. doi:10.2307/2566687

    Article  Google Scholar 

  20. Egger, P. H., von Ehrlich, M., & Nelson, D. R. (2012). Migration and trade. The World Economy, 35(2), 216–241. doi:10.1111/j.1467-9701.2011.01429.x

    Article  Google Scholar 

  21. Eichengreen, B. J., & Irwin, D. A. (1995). Trade blocs, currency blocs and the reorientation of world trade in the 1930s. Journal of International Economics, 38(1), 1–24. doi:10.1016/0022-1996(95)92754-P

    Article  Google Scholar 

  22. Eliasson, K., Hansson, P., & Lindvert, M. (2011). Tjänsteexporten allt viktigare för Sverige. Ekonomisk Debatt, 39(7), 28–40.

    Google Scholar 

  23. EU. (2013). Single market scoreborad—Performance by governance tool, Solvit. Brussells: European Commission.

    Google Scholar 

  24. European Commission. (2001). Final report: Barriers to trade in business services. Retrieved from http://ec.europa.eu/internal_market/economic-reports/docs/bus-servicesreport_en.pdf

  25. Eurostat. (2012a). All valid permits by reason, length of validity and citizenship on 31 December of each year. Luxembourg: European Commission.

    Google Scholar 

  26. Eurostat. (2012b). First permits issued for remunerated activities by reason, length of validity and citizenchip. Luxembourg: European Commission.

    Google Scholar 

  27. Exportutredningen. (2008). Svensk export och internationalisering—utveckling, utmaningar, företagsklimat och främjande. In Ministry for Foreign Affairs (Ed.). Stockholm.

  28. EY. (2009). Global mobility effectiveness survey 2009. London: Ernst & Young.

    Google Scholar 

  29. EY. (2013a). Global mobility effectiveness survey 2013: Your talent in motion. London: Ernst & Young.

    Google Scholar 

  30. EY. (2013b). Global tax policy and controversy briefing. London: Ernst & Young.

    Google Scholar 

  31. Felbermayr, G. J., Jung, B., & Toubal, F. (2010). Ethnic networks, information, and international trade: Revisiting the evidence. Annales d’Economie et de Statistique (97–98), 41–70. http://annales.ensae.fr/

  32. Foster-McGregor, N., & Pindyuk, O. (2013). Ethnic networks and services trade. Vienna Institute for International Economic Studies, mimeo.

  33. Genc, M., Gheasi, M., Nijkamp, P., & Poot, J. (2011). The impact of immigration on international trade: A meta-analysis (Norface Discussion Paper 2011020). Norface Research Programme on Migration, Department of Economics, University College London.

  34. Girma, S., & Kneller, R. (2008). Trade creation, replacement, and destruction in regional trade agreements: Micro-level evidence for the UK. Review of International Economics, 16(1), 142–158. doi:10.1111/j.1467-9396.2007.00732.x

    Article  Google Scholar 

  35. Gómez-Herrera, E. (2013). Comparing alternative methods to estimate gravity models of bilateral trade. Empirical Economics, 44(3), 1087–1111. doi:10.1007/s00181-012-0576-2

    Article  Google Scholar 

  36. Gould, D. M. (1994). Immigrant links to the home country: Empirical implications for U.S. bilateral trade flows. Review of Economics and Statistics, 76(2), 302–316.

    Article  Google Scholar 

  37. Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438.

    Article  Google Scholar 

  38. Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380. doi:10.2307/2776392

    Article  Google Scholar 

  39. Greenaway, D., & Kneller, R. (2007). Firm heterogeneity, exporting and foreign direct investment. The Economic Journal, 117(517), F134–F161. doi:10.2307/4625478

    Article  Google Scholar 

  40. Gustafson, P. (2012). Managing business travel: Developments and dilemmas in corporate travel management. Tourism Management, 33(2), 276–284. doi:10.1016/j.tourman.2011.03.006

    Article  Google Scholar 

  41. Haller, S., Damijan, J., Kaitila, V., Kostevc, Č., Maliranta, M., Milet, E., et al. (2014). Trading firms in the services sectors: Comparable evidence from four EU countries. Review of World Economics/Weltwirtschaftliches Archiv, 150(3), 471–505. doi:10.1007/s10290-014-0190-9

    Article  Google Scholar 

  42. Harvard Business Review. (2009). Managing across distance in today’s economic climate: The value of face-to-face communication. Harvard Business Review, Analytic Services.

  43. Hatzigeorgiou, A., & Lodefalk, M. (2014). The role of foreign networks for trade in services: Firm-level evidence. Swedish Entrepreneurship forum (Working Paper 27).

  44. Hatzigeorgiou, A., & Lodefalk, M. (2016). Migrants' influence on firm-level exports. Journal of Industry, Competition and Trade. doi:10.1007/s10842-015-0215-7

    Google Scholar 

  45. Head, K., Li, Y. A., & Minondo, A. (2014). Networks, geography, and knowledge flows: Evidence from citation patterns in mathematics (University of British Columbia Working Paper).

  46. Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica, 47(1), 153–161, http://www.econometricsociety.org

  47. Helpman, E., Melitz, M., & Rubinstein, Y. (2008). Estimating trade flows: Trading partners and trading volumes. The Quarterly Journal of Economics, 123(2), 441–487.

    Article  Google Scholar 

  48. Herander, M. G., & Saavedra, L. A. (2005). Exports and the structure of immigrant-based networks: The role of geographic proximity. Review of Economics and Statistics, 87(2), 323–335. http://www.mitpressjournals.org/loi/rest

  49. Heritage Foundation. (2014). 2014 index of economic freedom. Washington.

  50. Hiller, S. (2013). Does immigrant employment matter for export sales? Evidence from Denmark. Review of World Economics/Weltwirtschaftliches Archiv, 149(2), 369–394. http://springerlink.metapress.com/content/112760

  51. Hiller, S. (2014). The export promoting effect of emigration: Evidence from Denmark. Review of Development Economics, 18(4), 693–708. doi:10.1111/rode.12112

    Article  Google Scholar 

  52. Holm, N. (2014). Jakten på spelsnillen hindras av byråkrati. (12 February). Sydsvenskan.

  53. Inkpen, A. C., & Tsang, E. W. K. (2005). Social capital, networks, and knowledge transfer. The Academy of Management Review, 30(1), 146–165.

    Article  Google Scholar 

  54. Jansen, M., & Piermartini, R. (2009). Temporary migration and bilateral trade flows. The World Economy, 32(5), 735–753.

    Article  Google Scholar 

  55. Kapelko, N., & Volchkova, N. (2013). Export costs of visa restrictions: Evidence from Russia. New Economic School, Russia, mimeo.

  56. Kneller, R., & Pisu, M. (2011). Barriers to exporting: What are they and who do they matter to? World Economy, 34(6), 893–930. http://www.blackwellpublishing.com/journal.asp?ref=0378-5920

  57. Koenig, P., Mayneris, F., & Poncet, S. (2010). Local export spillovers in France. European Economic Review, 54, 622–641.

    Article  Google Scholar 

  58. Kulendran, N., & Wilson, K. (2000). Is there a relationship between international trade and international travel? Applied Economics, 32(8), 1001–1009. doi:10.1080/000368400322057

    Article  Google Scholar 

  59. Labanca, C., Molina, D., & Muendler, M.-A. (2014). Preparing to export. University of California San Diego, mimeo.

  60. Lewer, J. J. (2006). The impact of immigration on bi-lateral trade: OECD results from 1991–2000. Southwestern Economic Review, 33(1), 9–22.

    Google Scholar 

  61. Liu, X. (2009). GATT WTO promotes trade strongly: Sample selection and model specification. Review of International Economics, 17(3), 428–446. doi:10.1111/j.1467-9396.2009.00816.x

    Article  Google Scholar 

  62. Ljunge, M. (2012). Trust issues: Evidence from second generation immigrants (IFN Working Paper No. 946). Stockholm: Research Institute of Industrial Economics.

  63. Lodefalk, M. (2013). Servicification of Manufacturing–Evidence from Sweden. International Journal of Economics and Business Research, 6(1), 87–113. http://www.inderscience.com/ijebr

  64. Lodefalk, M. (2014). The role of services for manufacturing firm exports. Review of World Economics/Weltwirtschaftliches Archiv, 150(1), 59–82. doi:10.1007/s10290-013-0171-4

    Article  Google Scholar 

  65. Lopez, R. A. (2009). Do firms increase productivity in order to become exporters? Oxford Bulletin of Economics and Statistics, 71(5), 621–642.

    Article  Google Scholar 

  66. Magdeleine, J., & Maurer, A. (2008). Measuring GATS Mode 4 trade flows (WTO Staff Working Paper ERSD 2008-05). Geneva: Economic Research and Statistics Division, World Trade Organization.

  67. Malchow-Møller, N., Munch, J. R., Seidelin, C. A., & Skaksen, J. R. (2013). Immigrant workers and farm performance: Evidence from matched employer–employee data. American Journal of Agricultural Economics, 95(4), 819–841. doi:10.1093/ajae/aat010

    Article  Google Scholar 

  68. Malchow-Møller, N., Munch, J. R., & Skaksen, J. R. (2011). Do foreign experts increase the productivity of domestic firms? (IZA Discussion Papers 6001). Bonn: Institute for the Study of Labor.

  69. Markusen, J. R., & Trofimenko, N. (2009). Teaching locals new tricks: Foreign experts as a channel of knowledge transfers. Journal of Development Economics, 88(1), 120–131. doi:10.1016/j.jdeveco.2008.02.002

    Article  Google Scholar 

  70. Mayer, T., & Zignago, S. (2011). Notes on CEPII’s distances measures: The GeoDist database (CEPII Working Papers 2011–25). Paris: Centre d’Etudes Prospectives et d’Informations Internationales.

  71. Melitz, J., & Toubal, F. (2014). Native language, spoken language, translation and trade. Journal of International Economics, 93(2), 351–363. doi:10.1016/j.jinteco.2014.04.004

    Article  Google Scholar 

  72. Milgram, S. (1967). The Small-World Problem. Psychology Today, 1(1), 61–67.

    Google Scholar 

  73. Minondo, A. (2011). Learning to export with new managers. Empirical Economics Letters, 10(1), 7–11. http://www.eel.my100megs.com/

  74. Miroudot, S., Sauvage, J., & Shepherd, B. (2013). Measuring the cost of international trade in services. World Trade Review, 12(4), 719–735. doi:10.1017/S1474745613000049

    Article  Google Scholar 

  75. Munch, J. R., & Skaksen, J. R. (2008). Human capital and wages in exporting firms. Journal of International Economics, 75(2), 363–372.

    Article  Google Scholar 

  76. Mundlak, Y. (1978). On the pooling of time series and cross section data. Econometrica, 46(1), 69–85. doi:10.2307/1913646

    Article  Google Scholar 

  77. Murat, M. (2014). Out of sight, not out of mind. Education networks and international trade. World Development, 58, 53–66. doi:10.1016/j.worlddev.2013.12.013

    Article  Google Scholar 

  78. National Board of Trade. (2013a). Att flytta till Sverige—hinder för den fria rörligheten för EU-medborgare. National Board of Trade, Report, Stockholm.

  79. National Board of Trade. (2013b). Making trade happen. National Board of Trade, Report, Stockholm.

  80. National Board of Trade (2015). Sveriges utrikeshandel med varor och tjänster samt direktinvesteringar—helåret 2014. National Board of Trade, Report, March 2016, Stockholm.

  81. Neumayer, E. (2010). Visa restrictions and bilateral travel. Professional Geographer, 62(2), 171–181. doi:10.1080/00330121003600835

    Article  Google Scholar 

  82. Nunn, N. (2007). Relationship-specificity, incomplete contracts, and the pattern of trade. The Quarterly Journal of Economics, 122(2), 569–600. doi:10.1162/qjec.122.2.569

    Article  Google Scholar 

  83. OECD. (2010). International migration outlook 2010. Paris: OECD Publishing.

    Book  Google Scholar 

  84. OECD. (2013). International migration outlook 2013. Paris: OECD Publishing.

    Book  Google Scholar 

  85. OECD. (2014). Services trade restrictiveness index regulatory database. Paris: OECD Publishing.

    Google Scholar 

  86. O’Mahony, M., & van Ark, B. (2003). EU productivity and competitiveness: An industry perspective. Can Europe resume the catching-up process?. Luxembourg: Office for Official Publications of the European Communities.

    Google Scholar 

  87. Parrotta, P., Pozzoli, D., & Pytlikova, M. (2014a). Labor diversity and firm productivity. European Economic Review, 66, 144–179. doi:10.1016/j.euroecorev.2013.12.002

    Article  Google Scholar 

  88. Parrotta, P., Pozzoli, D., & Pytlikova, M. (2014b). The nexus between labor diversity and firm’s innovation. Journal of Population Economics, 27(2), 303–364. doi:10.1007/s00148-013-0491-7

    Article  Google Scholar 

  89. Parsons, C., & Vézina, P.-L. (2014). Migrant networks and trade: The Vietnamese boat people as a natural experiment (IMI Working Paper 91). University of Oxford.

  90. Peneder, M. (2007). A sectoral taxonomy of educational intensity. Empirica, 34(3), 189–212. doi:10.1007/s10663-007-9035-2

    Article  Google Scholar 

  91. Peri, G. (2012). The effect of immigration on productivity: Evidence from US states. Review of Economics and Statistics, 94(1), 348–358.

    Article  Google Scholar 

  92. Peri, G., & Requena-Silvente, F. (2010). The trade creation effect of immigrants: Evidence from the remarkable case of Spain. Canadian Journal of Economics, 43(4), 1433–1459. http://economics.ca/cje/

  93. Podolny, J. M., & Page, K. L. (1998). Network forms of organization. Annual Review of Sociology, 24(1), 57–76. doi:10.1146/annurev.soc.24.1.57

    Article  Google Scholar 

  94. Poole, J. (2009). Business travel as an input to international trade. University of California, Santa Cruz, mimeo.

  95. Quinn, M. A. (2009). Movies and the mystery of the missing trade: Is hollywood good for U.S. exporters? The International Trade Journal, 23(2), 231–254. doi:10.1080/08853900802388019

    Article  Google Scholar 

  96. Rauch, J. E. (1999). Networks versus markets in international trade. Journal of International Economics, 48(1), 7–35. http://www.elsevier.com/wps/find/journaldescription.cws_home/505552/description-description

  97. Riker, D., & Belenkiy, M. (2012). Face-to-face exports: The role of business travel in trade promotion. Journal of Travel Research, 51(5), 632–639. doi:10.1177/0047287512437857

    Article  Google Scholar 

  98. Sala, D., & Yalcin, E. (2015). Export experience of managers and the internationalisation of firms. The World Economy, 38(7), 1064–1089.

    Article  Google Scholar 

  99. Swedish Trade Council. (2010). Tjänsteexporten—Den snabbast växande sektorn i svensk ekonomi. Stockholm: Swedish Trade Council.

    Google Scholar 

  100. Tadesse, B., & White, R. (2010). Does cultural distance hinder trade in goods? A comparative study of nine OECD member nations. Open Economies Review, 21(2), 237–261. doi:10.1007/s11079-008-9090-8

    Article  Google Scholar 

  101. The Economist. (2013). Exports and the economy: Paying its way. The Economist.

  102. The Economist. (2014a). A plea for open doors—But governments are averting their ears. [Special report: Companies and the state]. The Economist.

  103. The Economist. (2014). Schumpeter: Bumpkin bosses. The Economist.

    Google Scholar 

  104. The Economist. (2014c). Undercover on a Segway—Tourists beware. The Economist.

  105. UHR (2014). Reglerade yrken–yrken med särskilda krav. http://www.uhr.se/sv/Bedomning-av-utlandsk-utbildning/Utlandsk-yrkesutbildning/Reglerade-yrken/. Accessed May 21, 2014.

  106. UCDP Battle-related Deaths Dataset. (2014a). http://www.pcr.uu.se/research/ucdp/datasets/ucdp_battle-related_deaths_dataset/. Accessed Retrieved January 20, 2014.

  107. UCDP Non-state Conflict Dataset. (2014b). http://www.pcr.uu.se/research/ucdp/datasets/ucdp_non-state_conflict_dataset_/. Accessed Retrieved January 20, 2014.

  108. UCDP One-sided Violence Dataset. (2014c). http://www.pcr.uu.se/research/ucdp/datasets/ucdp_one-sided_violence_dataset/. Accessed Retrieved January 20, 2014.

  109. UCDP Prio Armed Conflict Dataset. (2014d). http://www.pcr.uu.se/research/ucdp/datasets/ucdp_prio_armed_conflict_dataset/. Accessed Retrieved January 20, 2014.

  110. Walmsley, T. L., Winters, A., & Ahmed, A. (2011). The impact of the movement of labour: Results from a model of bilateral migration flows. Global Economy Journal, 11(4), 1–24. http://www.bepress.com/gej/

  111. Westermark, K. (2013). Proximity and learning in internationalisation: Small Swedish IT firms in India. Stockholm: Acta Universitatis Stockholmiensis.

    Google Scholar 

  112. White, R. (2007). Immigrant-trade links, transplanted home bias and network effects. Applied Economics, 39(7–9), 839–852. http://www.tandf.co.uk/journals/routledge/00036846.html

  113. World Bank. (2011a). Doing business database. Washington: World Bank.

    Google Scholar 

  114. World Bank. (2011b). World development indicators database. Washington: World Bank.

    Google Scholar 

  115. WTO. (2009). Presence of natural persons (Mode 4)—Background note by the secretariat. In Council for Trade in Services (Ed.). Genèva: World Trade Organization.

  116. Yasar, M., & Lisner, D. (2012). Bilateral trade impacts of temporary foreign visitor policy. Review of World Economics/Weltwirtschaftliches Archiv, 148(3), 501–521. doi:10.1007/s10290-012-0122-5

    Article  Google Scholar 

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Acknowledgments

We thank Nina Hasche, Sanne Hiller, Håkan Nordström, Roberta Piermartini, Linda Andersson and participants at the ETSG 2014 conference and at a seminar at Örebro University for helpful comments and suggestions. Moreover, we are indebted to Louise Johannesson for great research assistance, to Anna Graneli for excellent input into the first drafts, as well as to two anonymous reviewers for very helpful suggestions. Lodefalk acknowledges financial support from the Jan Wallander and Tom Hedelius Research Foundation and previously from the Swedish Agency for Economic and Regional Growth. The paper was initiated and partly completed while Lodefalk was a senior advisor at the Swedish National Board of Trade. The usual caveats apply.

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Appendix

Appendix

See Figs. 4, 5, 6 and Table 11.

Fig. 4
figure4

Temporary labor migration in OECD countries 2003–2011. Notes Authors’ calculations based on OECD(2010, 2013). These series overlap for the years 2006–2008, where there is a small discrepancy in the data

Fig. 5
figure5

Swedish exports of services, in 2014. Notes Authors’ calculations based on National Board of Trade (2015)

Fig. 6
figure6

Services trade restrictiveness index–movement of people. Notes Own computations of a GDP-weighted services trade restrictiveness index (STRI) that measures how far countries are from the benchmark country using data from the OECD (2014). The STRI is calculated for five policy areas and for individual service sectors. For each sector, policy areas are assigned different weights based on experts’ judgment. We computed a single average across sectors of the weighted index values for the policy area “Movement of People”. We then calculated its differences from “best practice” (min. value) as a proportion of “worst practice” (max. value) to attain a standardized (0, 1) index, which was then weighted by GDP to compute the average of the country group. BRICS stands for Brazil, Russia, India, China, and South Africa

Table 11 Data description and sources

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Lodefalk, M. Temporary expats for exports: micro-level evidence. Rev World Econ 152, 733–772 (2016). https://doi.org/10.1007/s10290-016-0254-0

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Keywords

  • Expats
  • Temporary movement of persons
  • Migration
  • Networks
  • Firm trade

JEL Classification

  • D80
  • F14
  • J61