Abstract
Based on matching techniques in combination with a difference-in-difference estimator, this paper estimates the effects at home of initiating production abroad through the establishment of a foreign production affiliate. The analysis covers manufacturing and service firms active in France during the period 1987–1999. We show that the motivation to start producing abroad is an important determinant of its impact at home. Market-seeking foreign direct investment (FDI) in manufacturing is associated with significant scale effects, resulting in job creation. By contrast, factor-seeking FDI in manufacturing has no significant effect on employment. However, there is some evidence that this type of FDI is associated with technology effects, in the form of greater capital-intensity and efficiency, as well as larger exports. Finally, FDI in service sectors is associated with significant positive employment effects, presumably reflecting the importance of the market-seeking motive in these sectors.
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Notes
Another reason why vertical FDI usually raises more important social concerns than horizontal FDI is that the jobs destroyed as a result of relocation tend to be very different from those created as a result of indirect effects.
As we are only interested in firms that establish a first foreign affiliate, complex forms of foreign direct investment necessarily reflect establishments which are likely to be motivated by both horizontal and vertical motives. While theoretically the effects of complex forms, as defined here, on observable outcomes at home simply present a linear combination of the two pure investment strategies, failure to disentangle those different forms empirically does not allow one to grasp their implications appropriately.
As discussed below, this is true with very few exceptions, which we classify as investors in a high-income location.
Nevertheless, the improvement of information and communication technologies has rendered the proximity requirement less systematic, as illustrated by the growing concerns surrounding services offshoring. Moreover, given the importance of producer services for manufacturing production, the increasing international fragmentation of production has tended to go hand-in-hand with FDI in services, since multinational firms often need their service providers to extend in parallel to them. However, the link between FDI in manufacturing and FDI services does not appear to have much bearing on the impact of FDI in services on the parent firm, except perhaps an additional need for co-ordination, a rather skill-intensive activity.
However, it would still be interesting to analyze how the impact of services FDI differs across services activities since the nature of FDI is likely to differ substantially across say business services, transportation services and hotels and restaurants. Unfortunately, the relatively small number of foreign-direct investments in services and their concentration in business and computing services does not allow us to make meaningful comparisons of the impact of services FDI across sectors. The sectoral breakdown of the estimation sample of matched firm pairs is shown in "Appendix 2" Table 3.
As emphasized below, the sector classification concerns the activity of the investing firms, not of its affiliates. Our analysis thus concerns investment by service firms. However, it is not clear how important that difference is in practice. We implicitly assume that services firms invest in services sectors abroad.
See Blundell and Costa Dias (2002) for a survey of the alternative approaches to evaluation problems.
Consequently, in contrast to ordinary least squares, matching does not rely on assumptions regarding functional form (i.e. linearity) and homogenous treatment effects (that the treatment effect is identical across individuals).
More specifically, the survey conducted by Direction des Relations Economiques Extérieures on French affiliates abroad is used to sort out the treated from the untreated, while the EAE is used to analyse why firms decide to establish a foreign affiliate abroad and how this affects their performance. See below for details on data sources.
More recently, Hahn (1998) has shown that using the propensity score may also improve the efficiency of ATT by reducing the number of dimensions.
In practical terms, implementing the DID estimator involves estimating a fixed effects model on the difference in the means between treated and untreated firms.
The sampling method used in services since 1997 is based upon a threshold. This threshold is generally set at 30 employees or a turnover of at least 5 million euros. All firms beyond the threshold are systematically surveyed each year, while only a sample of other firms below the threshold are surveyed each year.
Strictly speaking, a sufficient condition would have been to require the panel to be balanced up to t-star, the year in which firms switch. However, having a completely balanced panel facilitates the interpretation of the results as it removes any effects which are due to changes in the composition of firms after t-star. Barba Navaretti et al. (2010) also use a balanced panel but do not define cohorts.
A similar methodology is used in Jacobson et al. (1993).
Only 12 such examples are found in the matched estimation sample for manufacturing, 9 for services.
When imposing the common support, not all treated firms have a control on the common support. Accordingly, 286 matched firm pairs are studied below in manufacturing and 151 in services.
The definition of multinationals is restricted here to firms having invested abroad at least 3 years before.
In a manner similar to the Ashenfelter dip in the labour economics literature.
Since differences in average wage are more likely to result from differences in the composition of the workforce than pay differences across firms for similar workers we interpret this variable as a measure of skill-intensity.
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Acknowledgments
We like to thank Richard Upward for very helpful comments and suggestions on an earlier draft as well as an anonymous referee and participants of the ISIT Conference in Stockholm, the COMPPRESS workshop in Budapest and seminar participants in Nottingham and Paris. The opinions expressed in this paper are those of the authors and do not necessarily reflect those of the OECD or its member states. All remaining errors are our own.
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Appendices
Appendix 1
1.1 Measuring TFP
In order to measure TFP we apply the mean value theorem as suggested by Klette (1999). In practice this means that we transform the data in differences from the industry median within each year. There are two advantages to this transformation: (i) it increases the flexibility to deal with firm heterogeneity within the industry; (ii) it removes the need to use industry-level price deflators which are difficult to obtain for services. After transforming the data we estimate TFP as the residual of a Cobb–Douglas production function of capital, labour and materials. The production function controls for the possible correlation between input-choice and time-invariant productivity shocks by including individual-specific fixed effects.
1.2 Data management
In order to follow individual firms through time we organise the data around cohorts. Cohorts are defined as 6-year windows around year t [t − 2; t + 3] in which domestic firms establish a foreign presence. We impose the condition that within a 6-year window the panel should be balanced. After having defined the cohorts we stack them together in order to create a ‘panel of cohorts’ running from 1988–1998 for manufacturing. Bender and Von Wachter (2006) observe that this effectively gives a system of seemingly unrelated regressions with cross-equation restrictions.
Appendix 2: Additional results
See Tables 3, 4, 5, and 6 and Fig. 6.
Impact of foreign investment on skill-intensity, by income level of the recipient country and by sector. Notes: As in Fig. 2. Average labour skill is measured as the average yearly wage in the firm
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Hijzen, A., Jean, S. & Mayer, T. The effects at home of initiating production abroad: evidence from matched French firms. Rev World Econ 147, 457–483 (2011). https://doi.org/10.1007/s10290-011-0094-x
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DOI: https://doi.org/10.1007/s10290-011-0094-x