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Performance of small- and medium-sized enterprises in services trade: evidence from French firms

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Abstract

This paper empirically investigates the key firm- and industry-specific restrictions to the performance of small- and medium-sized enterprises (SMEs) in services trade. For this purpose, we use firm-level data from firms in France operating in different services sectors over the time period 1998–2007 and formulate two-part models consisting of (1) (dynamic) export equations and (2) (dynamic) export share equations. Our results confirm the view that a relatively low share of SMEs engages in services trade. In line with the new-new trade theory, our results also corroborate that more productive SMEs have a higher export probability. The key finding of this paper is that the export decisions of SMEs in services sectors are estimated to be extremely persistent, implying that trade policy efforts, including the allocation of scarce trade promotion budgets, should be directed at addressing the barriers faced in establishing the first export operation. Finally, our sub-sectoral estimates reveal considerable heterogeneity across different types of services.

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Notes

  1. Only recently, some new research results highlight the dominant role of newly created firms for overall job creation (Haltiwanger et al. 2013; Huber et al. 2013).

  2. The term new-new trade theory refers to models that incorporate firm-level heterogeneity in standard trade models in order to account for new stylized facts that are observed in firm-level data sets (Baldwin and Robert-Nicoud 2008).

  3. The literature review by Wagner (2012) exclusively focuses on contributions from the international economics literature, which mainly test predictions obtained from the new-new trade theory for data on service firms. In this section, we augment these findings by contributions from the small business economics literature.

  4. In a similar vein, the so-far available empirical evidence is mainly based on data that end prior to the last recession that have been triggered by the financial crisis. Accordingly, evidence on the impact of a world-wide decrease in GDP on the international engagement of services firms is still very scarce, and therefore, surveys that explicitly focus on such questions could be very helpful.

  5. The AMADEUS database does not provided a matched employer–employee dataset, and therefore, we are not able to observe worker-specific characteristics such as wages and the skill level. Accordingly, we are not able to include this information in our empirical analysis. More details on the available data are presented in Sect. 3.2.

  6. Accordingly, small and newly created firms typically have only limited access to (internal and external) financial resources (see, e.g., Fazzari et al. 1988; Cabral and Mata 2003).

  7. For French manufacturing firms, Stiebale (2011), however, is able to show that once observed and unobserved firm heterogeneity is taken into account, financial constraints have no significant effects on the export probability and the export shares.

  8. This ‘pecking order’ of productivity with regard to the choice of internationalization strategies has been confirmed by a huge bulk of empirical contributions (see, e.g., Head and Ries 2004; Greenaway and Kneller 2007; Aw and Lee 2008; Oberhofer and Pfaffermayr 2012; Temouria et al. 2013; Vogel and Wagner 2013). However, it is worth noting, that the vast majority of these investigations rely on manufacturing firms only Wagner (2012).

  9. While Bhattacharya et al. (2012) test their theory for the software industry in India, Wagner (2013) provides the first empirical test of this theory for a developed country, namely Germany.

  10. Below we estimate two different models, where the former assumes that conditional on all other covariates a firm’s export decision is independent of its past exporter status. By contrast, our second model allows to test for this by additionally including the lagged exporter status. More details on the differences between both models will be discussed below.

  11. For the econometric analysis, we also apply alternative definitions for exporting firms in order to check the robustness of the baseline results. Correspondingly, we classify firms as exporters if a non-negligible share of overall revenues (i.e., 10 and 25  %, respectively) is generated through exports.

  12. This also implies that we are not able to distinguish between goods and service exports within firms. For this reason our definition of service firms is based on revision 2 of the NACE industry classification as well as the W120 services classification of the World Trade Organization.

  13. For our sectoral estimates reported in Sect. 4.3 we apply the W120 services classification of the World Trade Organization as an alternative. For more details on this industry classification see, e.g., World Trade Organization (1991).

  14. Among these sub-industries are manufacture of paper and paper products (NACE Rev. 2 codes: 17), manufacture of computer, electronic and optical products (NACE Rev. 2 codes: 26), water transport (NACE Rev. 2 codes: 50), programming and broadcasting activities (NACE Rev. 2 codes: 60), information service activities (NACE Rev. 2 codes: 63) and activities of membership organizations (NACE Rev. 2 codes: 94).

  15. Accordingly, a firm is classified as micro-firm if it employees less than ten employees. Small (medium) firms employ ten or more (50 or more) workers but less than 50 (250). Firms with at least 250 employees are classified as large firms.

  16. Here, it is worth noting that we exclude manufacturing firms from this analysis because in our econometric analysis below we solely focus in firms in these respective industries.

  17. A general discussion on one-part versus two-part fractional response variable (e.g., export shares) models is offered by, e.g., Ramalho et al. (2011) and Oberhofer and Pfaffermayr (2012).

  18. A very similar model for the exporter status and export shares of French manufacturing firms is presented by Stiebale (2011). In econometric terms, the main difference is that Stiebale (2011) applies a Tobit model for the second part, while we make use of a fractional response model. This latter model has the main advantage that it explicitly accounts for the bounded nature of the export share data at hand.

  19. In our application, we assume that only averages of time-varying covariates directly affect the random effects \(\alpha _i\). Otherwise, we would not be able to obtain (short-run) estimates for the impact of legal form and the number of subsidiaries, respectively. We also alternatively estimated the first part using a conditional (fixed effects) logit model. In this model the identification of the parameters of interest is only possible for time-variant covariates and solely relies on the subsample of firms that switch their exporter status during our observational period (see, e.g., Train 2003). The estimates for the time-varying covariates from the conditional logit model are virtually identical to our random effects probit estimates and are available from the authors upon request.

  20. More details on this estimation procedure and the parameter estimates for the Cobb–Douglas production function can be found in Lejárraga et al. (2014).

  21. Due to the inclusion of the lagged export information, the number of observations in the full sample is reduced to 276,039. There are two reasons for this. First, the inclusion of lagged information does not allow to include the first observed year. Second, the AMADEUS data set provides data with missing observations for some years leaving us with an unbalanced panel dataset which further reduces the number of available observations.

  22. The estimation results for other service industries are available from the authors upon request.

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Acknowledgments

We would like to thank Rui Baptista, two anonymous referees, the participants of the 5th FIW research conference in International Economics at the Vienna University of Economics and Business, the participants of the FIW-WIIW research seminar in International economics, and the participants of the Inter-American Development Bank-ELSNIT XI Annual Conference on “Internationalisation of SMEs.” The authors also thank the OECD Working Party of the Trade Committee and the OECD Working Party on SMEs and Entrepreneurship for useful comments and discussions.

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Authors and Affiliations

  1. Investment Division, Directorate for Financial and Enterprise Affairs, Organisation for Economic Co-operation and Development (OECD), 2, Rue André Pascal, 75775, Paris Cedex 16, France

    Iza Lejárraga

  2. Department of Economics, Vienna University of Economics and Business, Welthandelsplatz 1, 1020, Vienna, Austria

    Harald Oberhofer

  3. Austrian Institute of Economic Research, Arsenal, Object 20, 1030, Vienna, Austria

    Harald Oberhofer

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  1. Iza Lejárraga
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Correspondence to Harald Oberhofer.

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Disclaimer This paper builds on an earlier analysis that was published as part of the OECD Trade Policy Paper No. 165 ”Small- and medium-sized enterprises in global markets: A differential approach for services?” Lejárraga et al. (2014). The opinions expressed and arguments employed herein are those of the authors and do not necessarily reflect the official views of the OECD or of the governments of its member countries.

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See Table 9.

Table 9 Empirical studies on the export behavior of service firms
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Lejárraga, I., Oberhofer, H. Performance of small- and medium-sized enterprises in services trade: evidence from French firms. Small Bus Econ 45, 673–702 (2015). https://doi.org/10.1007/s11187-015-9647-z

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