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Skilled Migration and Business Networks

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Abstract

The role of migrants’ networks in promoting cross border investments has been stressed in the literature, possibly making migration and FDI complements rather than substitutes in the long run. In this paper, we estimate the magnitude of such business network externalities in dynamic empirical models of FDI-funded capital accumulation. We use original data on capital and migration stocks rather than flows. Regarding migrants, we distinguish the total and skilled diasporas abroad. In both cross-sectional and panel frameworks, we find evidence of strong network externalities, mainly associated with the skilled diaspora.

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Notes

  1. See Stark et al. (1997, 1998), Mountford (1997), Beine et al. (2001, 2008), Stark and Wang (2002).

  2. See for example Gould (1994), López and Schiff (1998), Rauch and Trindade (2002), Rauch and Casella (1998), Wagner et al. (2002). On the contrary, focusing on the mechanisms through which NAFTA-related variables might work to reduce migration to the US, Aroca and Maloney (2004) used data on migration flows from and within Mexico without distinguishing between skilled and unskilled migrants. They found that both FDI and trade variables are substitutes for labor flows (FDI and trade reduce migration).

  3. For a more precise definition see Barba Navaretti and Venables (2004).

  4. In our analysis we use the command xtabond2 implemented in STATA. We used the robust two-step variant. We know that, though asymptotically more efficient, the two-step estimates can be downward biased. But xtabond2 makes available a finite-sample correction to the two-step covariance matrix derived by Windmeijer. STATA guide suggests this variant for system GMM estimator, because more efficient. However, we tried all the regressions using only the robust one-step variant. The main results of interest did not change very much.

  5. For the exogenous variables they enter as their own instruments in the regressions, two periods and earlier lagged values of endogenous variables, one period and earlier lagged values of predetermined or weakly exogenous variables can be used as instruments.

  6. We prefer the model with the High Income dummy to the model with GDP per capita since GDP per capita exhibit a strong correlation with other regressors. Hence, standard errors can be inflated. Moreover, the two-step estimated covariance matrix of moment conditions was singular in model 2. The number of instruments may be large relative to the number of groups. A generalized inverse must be used to calculate optimal weighting matrix in the two-step estimation.

  7. Instead of using the lagged value of the interaction terms, we separately use as instruments the time dummies and the lagged migration stocks (in logs).

  8. The significance of the interaction variables may simply reflect omitted variables and specification errors, so in this case it can only mean that we don’t have omitted variables and specification problems and not that the impact on migration on FDI growth has been stable over time.

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Authors and Affiliations

  1. National Fund for Scientific Research, Wallonia, Belgium

    Frédéric Docquier

  2. IRES, Department of Economics, Université Catholique de Louvain, 3 Place Montesquieu, 1348, Louvain-La-Neuve, Belgium

    Frédéric Docquier & Elisabetta Lodigiani

  3. Université du Luxembourg, CREA, 162A avenue de la Faïencerie, 1511, Luxembourg, Luxembourg

    Elisabetta Lodigiani

Authors
  1. Frédéric Docquier
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  2. Elisabetta Lodigiani
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Correspondence to Frédéric Docquier.

Additional information

This paper is a part of the research projects “People and firms” and “Sustainable Development in a Diverse World” conducted by the Centro Studi Luca d’Agliano (Italy). Helpful remarks and suggestions from anonymous referees were appreciated. We also thank Giorgio Barba Navaretti, Alok Bhargava, Matteo Manera, Matteo Picchio and Hillel Rapoport for their comments. The usual disclaimers apply.

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Docquier, F., Lodigiani, E. Skilled Migration and Business Networks. Open Econ Rev 21, 565–588 (2010). https://doi.org/10.1007/s11079-008-9102-8

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