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FDI and heterogeneous performance of European enterprises

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Abstract

This paper investigates the link between Foreign Direct Investment (FDI) and performance of European enterprises. Drawing on a large longitudinal database, we introduce a sophisticated taxonomy of FDI that accounts for both the FDI direction—inward versus outward—and the number of FDI. Our estimates suggest that there are systematic performance differences among firms with heterogeneous FDI involvement. Interestingly, firms experiencing some FDI enjoy a superior performance compared with purely domestic enterprises. Moreover, within the FDI class, the deeper the firm’s involvement in FDI, the larger the performance difference with purely domestic enterprises. These results are consistent through several econometric models, performance measures and definitions of FDI; moreover, they are robust to many alternative specifications including firm, industry and country controls.

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Notes

  1. For a survey, see: Lopez (2005), Wagner (2007, 2012), Greenaway and Kneller (2007), Singh (2010), Hayakawa et al. (2012).

  2. We focus on Melitz (2003) because of its theoretical influence and empirical success. However, it is not the only model pointing to a causal link between export and productivity. See, for instance: Yeaple (2005), Bernard et al. (2003), Jean (2002) and Bustos (2011).

  3. For a survey, see: Redding (2011).

  4. Put another way, if most FDIs are horizontal, one could not really expect to find a significant positive impact on performance.

  5. The impact of inward FDI on the other domestic firms, namely those that are not receiving any foreign participation, is designated “spillover effect”. It is the subject of another literature. For more details, see: Hayakawa et al. (2012).

  6. The complete list of national administrative sources is reported in Pinto Ribeiro et al. (2010).

  7. Unfortunately, Orbis presents also a number of shortcomings. A major motive of concern regards its coverage. Indeed, Orbis is not an exhaustive database of all companies around the world: it rather covers a sample of countries and, within each country, specific sectors and size classes are likely to be under-represented. This is because administrative data typically reflect the population of enterprises that meet the requirements for the inclusion, such as the registration at a Chamber of Commerce, or activity above a certain threshold. Another concern regards the quality of the data. As argued in Pinto Ribeiro et al. (2010), missing values are quite frequent, especially on variables—such as employment—that are not mandatory in balance sheet data. Moreover, financial data are available only with 1- or 2-year lags and, even though they cover a 10-year period, it is quite hard to track the same firms over time. This is because every year firms are selected based on a rotating sample to minimize response burdens; hence, the probability of being surveyed continuously is quite low. Lastly, there are likely to be some inconsistencies across countries about the unit of analysis and the main definitions from the System of National Accounts. To cope with these issues, Orbis is gradually increasing its coverage and it is implementing several programs to verify the quality of the data. For an extensive discussion about the pros and cons of Orbis, the reader is referred to Pinto Ribeiro et al. (2010) and Kalemli-Ozcan et al. (2015).

  8. Listed companies’ additional sections include information regarding cash flow, customers, competitors and outlook, description and history, full scanned annual, interim and quarterly reports, Corporate and Social Responsibility Reports, more detailed accounts and interim accounts, daily updated ratings, segment data and stock data (Bureau van Dijck 2009). Moreover, additional information about ownership is derived from the listed companies’ database and shareholders’ register, thus being available only for the group of listed firms (Pinto Ribeiro et al. 2010). Lastly, listed firms are assigned a ticker unique identifier, which can be downloaded together with economic, financial and ownership data. This is quite useful for practical reasons. Indeed, downloads of large files from Orbis are not allowed. A simple way of overcoming the existing cap is to download data sequentially, splitting the sample into many sub-samples. In the end, sub-samples can be merged by ticked unique identifier in order to build the whole database.

  9. Orbis is known for under-representing small and medium enterprises. However, in most European countries, it is a regulatory requirement to file most of the balance sheet variables for firms of any size. Therefore, firm coverage is superior in Europe than elsewhere (Kalemli-Ozcan et al. 2015).

  10. In Sect. 5, we check the robustness of our results with respect to a stricter definition of inward FDI and outward FDI based on the number of foreign shareholders and the number of foreign subsidiaries respectively. This allows us to capture different degrees of FDI involvement. Unfortunately, we cannot exploit other dimensions—such as the percentage of foreign ownership—due to missing values. We thank an anonymous Referee for this suggestion.

  11. More results are available from authors upon request.

  12. Unfortunately, Orbis provides no information on the export or the import status, therefore we cannot control for them.

  13. See Sect. 3 on this point.

  14. More results are available from authors upon request.

  15. Our choice of performance variables to be included in the same specification draws directly on the correlation matrix displayed in Table 14. For instance, we cannot enter all performance variables together, because some of them are highly correlated with one another.

  16. For more information, see: Amemiya (1981) and Maddala (1983).

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Authors and Affiliations

  1. University of Milano-Bicocca, DEMS, Piazza Ateneo Nuovo 1, 20126, Milan, Italy

    Valeria Gattai

  2. University of Milano-Bicocca, Piazza Ateneo Nuovo 1, 20126, Milan, Italy

    Giorgia Sali

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  1. Valeria Gattai
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Correspondence to Valeria Gattai.

Appendix

Appendix

This section provides a complete variables description (Table 13) and the correlation matrix of performance variables (Table 14).

Table 13 Variables description
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Table 14 Correlation matrix of performance variables
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Gattai, V., Sali, G. FDI and heterogeneous performance of European enterprises. Econ Polit Ind 43, 25–65 (2016). https://doi.org/10.1007/s40812-015-0022-5

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