sector (implication of this assumption for our results is explored in Appendix C). At the most disaggregated level, the underlying data that we use to estimate models (1) and (2) correspond to 7604 greenfield FDI projects in a new production or processing facility made by 3919 parent companies located in 83 source (developed and developing) countries, in 13 broad manufacturing sectors of 125 (developed and developing) destination countries during the period 2003-2006.<sup>38</sup> A potential drawback of the _fDi Markets_ database is that it only covers investment in a new physical operation. That means that mergers and acquisitions (M&A) FDI flows are excluded from the database. While we do not expect our results to be different across establishment modes of foreign affiliates, we nevertheless wish to validate this hypothesis empirically in robustness checks. We do so in Appendix C, using data on the number of bilateral M&A transactions.

Figure 1 plots the cumulated values of outward and inward greenfield FDI over the period 2003-2006 against FDI inflows compiled by UNCTAD on the basis of BOP statistics. The latter include information on both greenfield and M&A FDI. There is a strong correlation between the values of these two sources of FDI statistics. This suggests that the greenfield FDI data that we use in this paper are not affected by gross inconsistencies and are potentially representative of trends in both greenfield and M&A FDI.

# **4.2 Financial development**

Our main measure of financial development ( _SFDit−_ 1; _DFDit−_ 1) is the domestic credit allocated to the private sector by banks and other financial intermediaries, normalized by GDP. This financial development measure, using unit-level data (Rabe-Hesketh and Skrondal, 2012). An analogous result can be found in the discrete choice location literature. Guimaraes et al. (2003) demonstrate that the conditional logit model and the Poisson regression model share the same log-likelihood function with purely location-specific determinants. This implies that the estimation of a Poisson regression model with a sample where data are aggregated by location will yield the same estimates as a conditional logit model applied on project-level data. Some evidence that MNEs are heterogeneous can be found in section 5.1.2 (ED of young vs. mature firms).

> 38Firms can invest abroad in other “functions”, e.g. logistics, sales/customer support, or retail. We prefer to exclude these FDI projects from our sample because the broad sectoral classification adopted by fDi Intelligence may lead some projects to be included in a manufacturing sector even when their purposes are only to provide support services to this sector or to facilitate the distribution and sale of its products. By focusing on FDI in a new production or processing manufacturing facility (the ‘manufacturing function’ in the _fDi Markets_ database), we strongly increase the likelihood that the parent firm truly belongs to the manufacturing industry. Nevertheless, our main results hold when we use an enlarged sample including FDI in all functions by parent firms which invest at least once in the manufacturing function during the period 2003-2010. We also show in Appendix C that our results are robust to the use of

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