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Internationalisation and performance at the firm-level: what we learn from Italy

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Abstract

This paper surveys 71 contributions on internationalisation and performance of Italian enterprises. It covers empirical studies (including working papers), published between 1992 and 2014, taking a microeconomic perspective and analysing the potential links between firms’ global involvement and heterogeneity in economic, human capital and innovation and financial measures. The discussion is organised in an intuitive and non-technical way. At the same time, we devote particular attention to studying the different papers from many points of view, including their internationalisation measures, performance indicators, empirical approach, causality and results.

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Notes

  1. Throughout the paper, when we say that some firms perform better than others or, equivalently, that some firms are better than others we mean that, with respect to certain performance variable(s), the former enjoy a more favourable mean value than the latter. For the sake of completeness, we always mention the variable(s) according to which performance is evaluated. However, to economise on space, we do not specify whether higher or lower values of a certain indicator are associated with better or worse performance. This passage should be straightforward for the reader after reading Sect. 3 that describes in detail the available measures of performance. For instance, being better with respect to size means being larger.

  2. See Sect. 7 on this point.

  3. Some of the surveyed papers present also a theoretical model, adding to the empirical analysis. See, for instance, Basile (2001a, b), Becchetti and Gonzales (2001), Crinò and Epifani (2012) and Razzolini and Vannoni (2009, 2011).

  4. For a matter of comparison, the reader is referred to Wagner (2011) who provides a single-country survey of exports and firm characteristics in Germany. During the same decades, Wagner (2011) reviews 51 empirical studies on the topic. This suggests that the number of papers dealing with internationalisation and performance of Italian enterprises is exceptionally high.

  5. See Hayakawa et al. (2012) for more details.

  6. Only a couple of papers specify which part of the production process has to be carried out in a foreign country to have offshoring. For instance, Crinò (2010) considers the transfer abroad of service activities, while Lo Turco and Maggioni (2012) deal with intermediates.

  7. For instance, Serti and Tomasi (2008a) show that size, productivity, capital and wage are both the cause and the consequence of the export activity of Italian enterprises. See Sect. 5 for a discussion of causality issues.

  8. A few papers consider also some structural characteristics of the firm—such as group, district or consortium affiliation, ownership structure, and international experience—as potential determinants of internationalisation, adding to performance. To avoid ambiguities, in this section, we restrict attention only to performance measures. However, for the sake of completeness, our summary of results in Table 1 in the Electronic Supplementary Material Appendix covers also the structural characteristics of the firm.

  9. More details about TFP estimation can be found in Castellani and Giovannetti (2010) and Crinò and Epifani (2012), where several econometric techniques are compared.

  10. See Bell and Pavitt (1993).

  11. For more details, see Delgado et al. (2002).

  12. For more details, see Fligner and Policello (1981).

  13. 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. Alternative approaches to modelling firm heterogeneity and trade are Yeaple (2005), Bernard et al. (2003), Jean (2002) and Bustos (2011).

  14. For a survey, see Redding (2011).

  15. Countries matter also in Bernard et al. (2010). They develop a general equilibrium model of multi-product and multi-destination firms in which heterogeneity is measured in terms of productivity and consumer taste. A key result of this model is that firms with the highest productivity start exporting, and products with the highest attributes are exported to the largest number of foreign markets; on the contrary, products characterised by the worst attributes are sold only domestically.

  16. Notice that de Nardis and Pappalardo (2009) highlight a mechanism other than LI that is compatible with the same direction of causality. Interestingly, they show that multi-product exporters tend to experience various forms of product switching as a reaction to the competitive international arena. Product switching, in turn, positively and significantly affects firms’ performance given that resources are efficiently allocated within firms’ boundaries. Their analysis can be thought of as an extreme extension of the Melitz’s (2003) intuition since heterogeneity across firms brings about intra-industry adjustments in favour of more productive firms, and heterogeneity across products results in intra-firm adjustments in favour of more productive products.

  17. See Murray (2006) on this issue.

  18. As shown in Hansen (1982), every IV estimator - in linear and non-linear model, with cross-section, time series or panel data - can be thought of as a special case of the generalised method of moments estimator. The GMM is based on moment functions that depend on observable random variables and unknown parameters and that have zero expectations in the population when evaluated at the true parameter values.

  19. For a comprehensive discussion of these techniques, see Becker and Ichino (2002), Caliendo and Hujer (2006), Caliendo and Kopeinig (2008) and Imbens and Wooldridge (2009).

  20. For the sake of clarity, note that the specific patterns identified below should be regarded as a convenient way of grou** papers according to their main topic, not as a way of grou** topics across papers. This implies that each paper is assigned to a single pattern or, equivalently, that the sum of the papers per pattern equals 71. One may argue that this mutually exclusive map** of papers into patterns comes at the expenses of completeness. However, we believe it provides a neater overview of the existing lines of research, given the large number of the surveyed contributions.

  21. In a contemporaneous paper, Lo Turco et al. (2013) study the relationship between offshoring and job stability in Italy in the period 1995–2001 by using an administrative dataset on manufacturing workers. International fragmentation of production is shown to negatively affect job stability. Interestingly, service offshoring and material purchases from developed countries foster job-to-job transitions of all workers and white collar employees within the manufacturing sector. On the contrary, material offshoring to low-income countries drives blue collar workers out of manufacturing. We do not cover this paper in detail since internationalisation measures are based on industry- rather than firm-level data, so it goes beyond the scope of the present survey.

  22. The effects of international trade on labour market outcomes are analysed also in Accetturo et al. (2013) at the industry-level. Notably, they show that exports cause a sizeable skill upgrading in the local labour force by increasing the average level of education of the workforce and the share of white collars. Although this paper complements other contributions on the topic, it is not covered in detail because it provides no empirical evidence at the micro level.

  23. This is the case of ownership structure and management practices.

  24. This notion of “product switching” differs from that of “product drop**” adopted in De Nardis and Ventura (2010) because it covers both the case of drop** and the case of adding new products. Notice also that De Nardis and Ventura (2010) do not really study the links between internationalisation and performance, but rather ask whether product drop** has an impact on productivity for a sub-sample of Italian exporters. Hence, the causal relationship, if any, involves product drop** and productivity and not product drop** and internationalisation; for this reason, we do not survey De Nardis and Ventura (2010), while we focus on De Nardis and Pappalardo (2009).

  25. For instance, the data reported in Mayer and Ottaviano (2008) reveal that the top 1 % of exporters is responsible for more than 45 % of the overall export volume, the top 5 % accounts for 70 % and the top 10 % for roughly 80 %.

  26. In this case, results are probably driven by the massive presence of exporters in the respective datasets.

  27. For instance, according to ICE (2013), exporters are only 4 % of the total number of enterprises in Italy. The higher percentages reported in the literature of interest probably depend on the characteristics of the respective samples. For more information on the data sources, please refer to Sect. 4.1. Data limitations are discussed in Sect. 7.

  28. Grazzi (2012) does not find a performance discount for firms engaged in export activities; however, he documents the absence of any premiums related to profitability and growth rate. Similar results are reported in Vivarelli and Piva (2001) where the increased demand for skilled workers over the 1990s is the result of organisational changes rather than innovation and FDI.

  29. For more information, see Castellani and Koch (2015).

  30. See Wagner (2012b) for a practical guide on the implementation of these techniques.

  31. This is the case, for instance, of export promotion policies.

  32. In doing this, particular attention should be devoted to detecting instances of conscious self-selection, i.e., the decision by which certain firms purposefully increase their productivity with the clear intention of becoming exporters and benefiting from export promotion policies (Lopez 2005).

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Acknowledgments

The author is grateful to the Editor, two anonymous Referees, Davide Castellani, Piergiovanna Natale, Gianmarco Ottaviano and Les Oxley for useful comments and insightful discussions that greatly improved the quality and readability of the paper. Financial support from Università di Milano-Bicocca and MIUR (Italian Ministry of University and Education) is gratefully acknowledged. The usual disclaimer applies.

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  1. DEMS, Università di Milano-Bicocca, Piazza Ateneo Nuovo 1, 20126, Milan, Italy

    Valeria Gattai

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Gattai, V. Internationalisation and performance at the firm-level: what we learn from Italy. Econ Polit Ind 42, 475–509 (2015). https://doi.org/10.1007/s40812-015-0019-0

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