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ABSTRACT
Exports matter for domestic employment in both export-producing firms and upstream suppliers. Their total effect can be captured through an input–output-based indicator of export-sustained employment. However, as industry classifications used in regular input–output tables are based on product similarity, they fail to account for within-industry technological heterogeneity between exporters and other firms, which may lead to a bias in results for export-sustained employment. In this paper, we describe the breakdown of manufacturing industries into export-oriented and domestic-oriented firms in Belgian input–output tables and employment data based on detailed firm-level data for industry totals and input–output structures. Based on the resulting export-heterogeneous tables, we find that 585,000 jobs or 13% of economy-wide employment in Belgium is sustained by manufacturing exports. This is overestimated by 4% with regular tables. Moreover, we identify who contributes to and who gains from exports for groups of firms rather than aggregated industries.
Acknowledgements
The authors would like to thank Bart Hertveldt, Guy Trachez and three anonymous referees as well as participants of the 27th International Input-Output Association Conference in Glasgow in July 2019 for their comments that have helped to improve this article. We also acknowledge the invaluable support of Gaëtan De Menten, Geert Bryon and Alix Damman with the Larray module that they have created for Python and that was used for all calculations, and of Maritza Lopez-Novella and Bart Van den Cruyce with the employment data.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 We use the term export-sustained employment rather than employment generated by exports to remain neutral about the nature of the relationship between trade and employment. Alternatively, we also refer to this as employment embodied in exports.
2 In recent years, empirical evidence on within-industry firm heterogeneity has led to a regain of interest for the issue of representativity and relevance of industry-level technical coefficients derived from IOT (e.g. Ahmad et al., Citation2013; De Gortari, Citation2019). However, awareness of this issue dates back to much earlier contributions (e.g. Hatanaka, Citation1952, and McManus, Citation1956).
3 Supply-and-use and input–output tables (SUT and IOT) with a breakdown of industries into different categories of heterogeneous firms are generally referred to as extended SUT and IOT. Exporter status is by no means the only criterion for the disaggregation of industries, the other main criteria being ownership and size. Ahmad (Citation2018) provides a detailed general overview on extended SUT and IOT.
4 The OECD’s inter-country IOT take on board the distinction of processing traders for China. For Mexico, so-called global manufacturers are separated out. They comprise not only firms operating under special export regimes but also foreign-owned firms and exporters that mainly use imported intermediates. The aim of these disaggregations is to improve trade in value-added (TiVA) indicators (see oe.cd/icio).
5 Turnover stands for revenue in terms of the Belgian accounting norms.
6 This prepares for further analytical applications and allows us to integrate the Belgian exporter-heterogeneous IOT into a global multi-country IOT.
7 The single-country IOT must then include a disaggregation of exports by partner country.
8 We are fully aware that the choice of 25% for the exports-to-turnover threshold is arbitrary. Lowering the threshold to 20% would not have led to a massive change in the number of firms considered as export-oriented. There would have been approximately 200 extra export-oriented firms accounting for €2.5 billion of turnover. We have not produced an exporter-heterogeneous IOT based on a different threshold because of the substantial workload of doing so.
9 See Lopez-Novella and Sissoko (Citation2013) for a more detailed description of the NSSO database.
10 These data are publicly available on the FPB website (https://www.plan.be/databases/data-23-en-qualitative+employment+data+for+belgium+1999+2015). For details on how this database is constructed, see Bresseleers et al. (Citation2007) and Van den Cruyce and Hendrickx (Citation2017).
11 The social balance sheet is a separate section of the annual accounts in Belgium.
12 These are NACE Rev.2 industries. For codes and definitions, see Appendix B, Table A.4.
13 See Graphs A.2 and A.3 in Appendix D.
14 This value added per worker ratio is a rather rough measure of labour productivity. Among other things, it does not take into account elements such as hours worked, skill distributions, capital-intensity or differences in relative prices.
15 See Graphs A.4 and A.5 in Appendix D.
16 IO calculations are referred to as ex post accounting because of the underlying assumption of fixed cost proportions of labour, capital and intermediate inputs at any level of output. In terms of employment effects, it is therefore very different from a labour demand equation derived from a production function under cost minimisation (or profit maximisation), which allows for substitution between input factors. For an example of the estimation of a labour demand equation with industry-level data for Belgium, see Hertveldt and Michel (Citation2013).
17 The HEM is an IO method that was initially used for measuring the importance of an industry for an economy by extracting it, i.e. setting all values for this industry equal to 0 in the IO calculations (see Miller and Lahr (Citation2001) for an overview).
18 It is also possible to define double-counting based on the world perspective (Borin & Mancini, Citation2019), but this is not relevant in our case and would not alter our results for domestic employment (Miroudot & Ye, Citation2020).
19 The results provided in Appendix F show that the difference between the country perspective and the bilateral perspective is small for Belgium’s export-sustained employment. This is in line with findings reported in Los and Timmer (Citation2018) for other countries.
20 This information is also given in Table A.7 in Appendix G.
21 The patterns are similar for value-added embodied in exports. This is shown in Graph A.6 (and also Table A.8) in Appendix G. It can be read in the same way as Graph 1. Bars indicate the total value-added generated by the exports of each of the three groups of firms, and these totals are subdivided to show in which group of firms the value-added are generated.
22 Los et al. (Citation2015) mention that within-industry differences in skill intensities may imply that the use of regular IOT ‘understates the importance of exports for skill demand’ (p. 29).