metadata: authors: 0: author: Winkler,Deborah Elisabeth
1: author: Kruse,Hagen
2: author: Aguilar Luna,Luis Alejandro
3: author: Maliszewska,Maryla
count: World
docna: 0: docna: Linking Trade to Jobs, Incomes, and
            Activities : New Stylized Facts for Low- and Middle-Income Countries
docty: Policy Research Working Paper
theme: Inclusive Growth,Job Creation,Trade Facilitation,Economic Policy,Trade Policy,Green Growth,Economic Growth and Planning,Private Sector Development,Job Quality,Jobs,Trade
abstracts: cdata!: Trade expansion can create more and
            better jobs. This paper revisits the linkages between trade
            and jobs, focusing on employment, labor incomes, and job
            activities across a large sample of countries and sectors
            over 1995 to 2018. Instrumental variables regressions and
            new input-output measures of jobs and activities in exports
            highlight several patterns: Exports and especially imports
            of intermediate inputs are associated with more jobs and
            higher incomes, while final imports show weaker
            correlations. Manufacturing has the biggest potential for
            job and income creation both directly and indirectly in
            supplying sectors. As countries move from specialization in
            commodities to limited manufacturing to advanced
            manufacturing and services global value chains,
            export-employment and export-income elasticities increase.
            Global value chain&#x2013;intensive developing countries
            tend to have larger shares of production activities in
            exports compared to resource-intensive countries. As
            countries get richer, nonproduction activities in exports,
            such as support, engineering, and managerial services,
            become increasingly important. Finally, the paper explores
            the role of policy for the export job share across countries.
display_title: Linking Trade to Jobs, Incomes, and
            Activities : New Stylized Facts for Low- and Middle-Income Countries
listing_relative_url: /research/2023/12/34212650/linking-trade-jobs-incomes-activities-new-stylized-facts-low--middle-income-countries
topicv3: Global Value Chains(GVC) m1326472 767,Trade Policy and Integration m1327407 775,Labor Incomes and Poverty m1503852 2676,Jobs in Middle Income Countries m1504016 2713,Trade Linkages, Spillovers and
            Connectivity m1504235 2601
publishtoextweb_dt: 2023-12-11T00:00:00Z
dois: 10.1596/1813-9450-10635
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 53
author_keys: 0: author_key: 1048582
1: author_key: 2257975
2: author_key: 1727480
3: author_key: 545393
model_extractions: Policy Research Working Paper 10635 Linking Trade to Jobs, Incomes, and Activities New Stylized Facts for Low- and Middle-Income Countries _Deborah Winkler Hagen Kruse Luis Aguilar Luna Maryla Maliszewska_ Macroeconomics, Trade and Investment Global Practice December 2023
Policy Research Working Paper 10635

# **Abstract**

Trade expansion can create more and better jobs. This paper revisits the linkages between trade and jobs, focusing on employment, labor incomes, and job activities across a large sample of countries and sectors over 1995 to 2018. Instrumental variables regressions and new input-output measures of jobs and activities in exports highlight several patterns: Exports and especially imports of intermediate inputs are associated with more jobs and higher incomes, while final imports show weaker correlations. Manufacturing has the biggest potential for job and income creation both directly and indirectly in supplying sectors. As countries move from specialization in commodities to limited manufacturing to advanced manufacturing and services global value chains, export-employment and export-income elasticities increase. Global value chain–intensive developing countries tend to have larger shares of production activities in exports compared to resource-intensive countries. As countries get richer, nonproduction activities in exports, such as support, engineering, and managerial services, become increasingly important. Finally, the paper explores the role of policy for the export job share across countries.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at dwinkler2@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Linking Trade to Jobs, Incomes, and Activities: New Stylized Facts for Low- and Middle-Income Countries

Deborah Winkler<sup>1</sup> , Hagen Kruse<sup>2</sup> , Luis Aguilar Luna<sup>3</sup> , and Maryla Maliszewska<sup>4</sup> Keywords: Economic development, employment, international trade, global value chains, occupations, sectors JEL codes: F14, F63, O14

> 1 Corresponding author, Senior Economist, Trade and Regional Integration, World Bank. eMail: dwinkler2@worldbank.org.

> 2 PhD Student, Groningen Growth and Development Centre, University of Groningen.

> 3 Consultant, Trade and Regional Integration, World Bank.

> 4 Senior Economist, Trade and Regional Integration, World Bank.

> This paper was developed for the project “Leveraging trade for more and better job opportunities in developing countries” and financed by the Umbrella Facility for Trade Trust Fund. The authors thank Elcin Koten for her research assistance and are thankful for great comments provided by Sébastien Dessus, Mona Haddad, Mary Hallward-Driemeyer, Claire Hollweg, Gladys LopezAcevedo, Dino Merotto, Jorge Tudela Pye, Ben Shepherd, and Gaaitzen de Vries, as well as participants of the two authors’ workshops in May and November 2022. The work was carried out under the overall supervision of Sébastien Dessus and Antonio Nucifora. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank Group and its affiliated organizations, its Executive Directors or the governments they represent.
# 1. Introduction

Economists are largely in agreement that, at least at the aggregate level and over the long term, trade plays an important role in driving economic growth, job creation, and wage growth (Dutt, Mitra and Ranjan 2009; Hollweg et al. 2014; Brown et al. 2016). Recent empirical evidence, however, finds no impact of participation in global value chains (GVCs) on employment in low- and middle-income countries (LMICs) (Pahl and Timmer 2020). Empirical assessments across countries are still scarce, in large part because of the difficulty to establish causality in such models. Another strand of literature highlights the negative effects of import competition from low- and middle-income countries on workers at the local level in developed economies (e.g., Autor, Dorn, and Hanson 2013; Balsvik, Jensen, and Salvanes 2015; Hakobyan and McLaren 2016).

Recent evidence also points out that the gains are unequally distributed and losses more visible. Recent policy research concludes that (i) the gains from trade are unequally distributed across countries, sectors, regions, and workers (Engel et al. 2021), and (ii) the losses are often more concentrated and visible than the gains ( <mark>Artuç et al. 2019; 2021).</mark> Studies, for instance, find that trade liberalization could lead to heightened inequality and deteriorating labor market outcomes (Goldberg and Pavcnik 2007; Nicita 2009; Topalova 2010; De Loecker et al. 2016; Dix-Carneiro and Kovak 2017; Pavcnik 2017; Erten, Leight and Tregenna 2019).<sup>5</sup> Inconclusive findings can to some extent also be attributed to the different types of trade under study, with the labor market effects from import competition differing from those of GVC participation. While the former type of trade directly competes with domestic production over consumer demand, the latter emphasizes the role of imported inputs for export production. Given that over half of international trade happens within the boundaries of GVCs (World Bank 2020), it is critical to not only focus on exports and imports, but also assess the role of GVC participation for labor market outcomes. In addition, renewed attention has been devoted to assessing the role of technology versus trade as both can create and destroy jobs. In a world characterized by GVCs, the trade and technology nexus is increasingly merged, as producers play off trade, investment, and technology to maximize profits (Farole et al. 2018).

Drawing on novel datasets with a good coverage of developing countries, this paper re-visits the relationship between trade and jobs across countries at the level of sectors and activities. This study reexamines the relationship between trade and jobs both indirectly, i.e., through econometric analysis applying an instrumental variables (IV) approach, and directly relying on new employment, income and input-output data that allow to characterize changing jobs and job specializations in exports. The combination of these methodologies and different datasets not only allows us to address endogeneity concerns, but also to provide new insights into the various trade and labor relationships, in particular (i) how the type of trade shapes within-sector job creation, (ii) how exports create employment directly in the export sector and indirectly in its supplying sectors, and (iii) which job activities embodied in exports are performed across countries, sectors, and occupations.

Importantly, the analysis aims to disentangle some of the complexities characterizing trade-and-jobs relationships, in particular the role of different types of trade, sectors, activities, and labor market

> 5 At the firm level, evidence for LMICs is less ambiguous, suggesting a positive association between a firm’s trading status (especially GVC participation) and employment. While the positive link between exporting and productivity and to a lesser extent employment has been established at the firm-level in LMICs, recent research suggests that participation in GVCs magnifies the labor gains from traditional one-way trade. Demand for worker skills also tends to be higher among GVC participating firms relative to non-GVC firms because of higher global quality standards imposed by lead firms in GVCs (World Economic Forum 2015; Criscuolo and Timmis 2017). As a result, GVC-participating firms are on average more productive, larger and more skill-intensive than other types of firms, including firms that export or import only. These gains from trade at the firm level do not necessarily materialize at the aggregate level of sectors and places, if GVC or one-way trading firms pull away workers from domestic only firms.

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channels. The findings show that the employment effects vary strongly depending on the type of trade considered (exports, intermediate imports, final imports, GVC participation). Assessing the relationship for employment and labor value added separately, the analysis finds the income channel to be stronger than the employment channel. The trade-and-labor links also critically depend on the sector under study, with manufacturing sectors showing the highest job and income growth associated with expanding exports in a sector. Not surprisingly, the way in which countries engage in GVCs matters for the magnitude of export-employment elasticities. But a country’s sectoral specialization also matters for the indirect job creation potential in supplying sectors. Finally, this study sheds light on the types of job activities embodied in exports. From a GVC perspective, tracking job activities that countries specialize in for their export production over time allows to detect upgrading patterns and allows to study aspects of job quality.

This paper contributes to the literature in a number of ways. First, this study provides new descriptive analysis drawing on recent employment-in-exports data covering over 50 high- and middle-income countries (HMICs). A major strength of these employment estimates is that they account for indirect linkages of an export sector to domestic supplying sectors. Increases in exports can lead to domestic job creation not only within the export sector, but also in domestic supplying sectors, allowing for a more accurate representation of the trade and labor links. As our analysis shows, the indirect job creation from manufacturing exports is higher than the direct job creation in these sectors, while for business and especially other services exports the bulk of employment is created directly in these services sectors. Some studies have used direct measures of employment in exports or GVCs, but they focus on measurement aspects and do not cover more recent years (Calì et al. 2016, <mark>Horvát, Webb and Yamano 2020</mark> ) or a narrow set of countries (Timmer et al. 2014).

Second, while trade research focused on skills intensity, labor productivity or average wage rate to capture jobs quality, this paper introduces a novel characterization of job specializations in exports, namely of activities, ranging from managerial, to engineering, to production, to other services activities (Kruse, Timmer, de Vries, and Ye 2023). Such measures reflect the composition of activities in exports, and changes over time, across countries, income levels, sectors, occupations, and for specific countrysector combinations. In the context of GVCs, emphasizing activities that countries specialize in for their export production – rather than the goods and services they export – is meaningful from a measurement and conceptual perspective: (i) the latter could embody a large share of foreign value added from activities performed abroad, and (ii) the concept of a value chain involves a range of value-adding activities. It is also warranted from a development perspective. Case study evidence suggests that moving towards nonproduction activities offers scope for economic upgrading, both across and within sectors. Adding the occupational dimension to sectoral specialization patterns helps track development trajectories.

<mark>Third, conventional methods of assessing trade and labor links econometrically within sectors across countries remain valuable for at least four reasons. (1) First, direct employment in exports measures (e.g., from OECD) are not available for many developing countries, especially those at lower-income levels, while data coverage of trade and employment is better. (2) Second, direct measures focus on jobs embodied in exports only, while econometric analysis allows to link employment to other types of trade, including imports and GVC participation, for which correlates could vary. (3) Third, regression analysis also allows to estimate trade-income elasticities besides trade-employment elasticities to understand which of these two channels is stronger.</mark><sup>6</sup> <mark>If trade-income elasticities are larger than trade-employment elasticities, this implies that increases in trade benefit workers more strongly through higher average wage rates rather than through more employment.</mark><sup>7</sup> <mark>(4) Finally, comparing elasticities based on formal</mark>

> 6 This is because labor income or labor value added (LVA) is the product of employment L and the average wage rate w (LVA=L*w). 7 While the direct measures also allow to assess the income content of exports, a comparison with the employment content of exports is more difficult.

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<mark>employment with those based on informal employment allows to tentatively assess the role of the informal labor market.</mark> Finally, this study contributes to the econometric literature on the labor market effects of GVC <mark>participation at the country-sector level. The majority of earlier sectoral studies focused on the effect of outsourcing, based on national input-output linkages, on the relative demand for workers or total labor demand in one specific country (see, e.g., the seminal study by Feenstra and Hanson 1996), whereas our analysis covers LMICs and also uses GVC measures based on international input-output linkages.</mark><sup>8</sup> <mark>This study also relates to the literature on measuring social upgrading through GVC participation, especially with regards to job creation. More research has been dedicated to studying the economic rather than the social impacts of trade and GVC participation. Empirical evidence across and within countries confirms that GVC participation fosters productivity, value-added, and growth (Constantinescu, Mattoo, and Ruta 2019; World Bank 2019; Stolzenburg, Taglioni, and Winkler 2019; Pahl and Timmer 2020). Research suggests, however, that social upgrading does not necessarily follow economic upgrading (Milberg and Winkler 2013; Kruse 2023), for instance due to high labor market adjustment costs (Hollweg et al. 2014).</mark> In section 2, we apply econometric analysis to estimate trade-employment and trade-income elasticities within sectors across countries. Labor demand models can be derived from a variable unit cost function<sup>9</sup> and have been applied widely in the literature at the country-sector-year level (see Appendix 1). The analysis is based on two different data samples: a sample of 48 HMICs covering mainly formal employment and a sample of 37 LMICs capturing both formal and informal employment (for details, see Appendix 2). In addition, the dataset of HMICs enables us to estimate both trade-employment and tradeincome elasticities and therefore examine which of these channels is stronger.<sup>10</sup> We hypothesize that sectoral differences as well as countries’ type of engagements in trade and GVCs could explain differences in labor markets outcomes. For instance, recent work found the export-toemployment elasticities for business services to be larger than for manufacturing in a sample of 43 mostly high-income countries using the WIOD database (Goretti et al. 2019). We run the model by broad sector (agriculture, manufacturing, business services, other services) and also at the disaggregated industry level to identify possible differences across sectors. We also assess the role of a country’s type of GVC specialization and categorize countries into four basic GVC groups (World Bank 2020), differentiating between countries specialized in (1) commodities, (2) limited manufacturing GVCs, (3) advanced manufacturing and services, and (4) innovative tasks (for details, see Appendix 3).

Sections 3 and 4 use direct measures of employment and job activities in exports. We rely on the OECD Trade in Employment database for estimates of employment in exports for 45 goods and services sectors (based on ISIC Rev. 4 sectors) for over 50 countries for the period 1995-2018. (Appendix 4 describes the underlying computations in more detail). The novel database Job Activities in Exports adds the dimension of occupations and is thus able to provide estimates of jobs in exports for sector-occupation combinations which define the so-called activities in exports (Appendix 5 describes the underlying computations for job activities in exports).

Our paper is structured as follows. Section 2 estimates correlations between various types of trade and employment or labor income within sectors. Section 3 studies the role of job creation in supplying sectors versus export sectors, while section 4 examines job activities in exports across and within sectors. Section 5 explores the role of policy in job creation from exports, while section 6 summarizes and concludes.

> 8 The research by Farole et al. (2018) studied the role of GVC participation for the labor value added, the labor share and the relative demand for skills in a cross-country-sector model for selected years between 2001 and 2014. Our proposed work differs with regards to the chosen models, methodologies, datasets and labor market outcomes.

> 9 See Brown and Christensen (1981) and an application in Feenstra and Hanson (1996), among many others.

> 10 The sample of LMICs only contains employment data and thus prevents us from performing a similar assessment.

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2. Estimating trade and employment elasticities within sectors

# 2.1 Do trade-employment elasticities differ for exports and imports?

Analysis for a sample of 48 OECD and non-OECD countries covering 45 sectors for the period 19952018 finds that export-employment elasticities within sectors are positive.<sup>11</sup> Specifically, a 10 percent increase in exports is associated with a 3.1 percent increase in employment (Figure 1, left panel).<sup>12</sup> On the downside, the potential for exports to contribute to job growth within sectors in the country sample was driven by the period before the global financial crisis (i.e., 1995-2006), while estimates for the more recent period (i.e., 2007-2018) are either insignificant or the chosen instruments for the trade variable not valid.<sup>13</sup> A possible explanation may be a growing capital intensity of export production, including the use of laborsubstituting technologies, during the more recent period (Hallward-Driemeier and Nayyar 2017).

**Figure 1: Trade-employment (left) and trade-income elasticities (right), by type of trade**

<!-- Start of picture text --> 0.8 0.8<br>0.7 0.7<br>0.6 0.6<br>0.5 0.5<br>0.4 0.4<br>0.3 0.3<br>0.2 0.2<br>0.1 0.1<br>0.0 0.0<br>Exports Intermediate Final imports Exports Intermediate Final imports<br>imports imports<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE and TiVA data, covering 48 countries (see Appendix 2) and 45 sectors for the period 1995-2018. Note: Trade-employment (trade-income, resp.) elasticities at the country-sector level have been estimated using employment (labor income, resp.) (in natural logs) as dependent variable and the instrumented trade variables (in levels and natural logs) as independent variable. For more information on the instruments, see Appendix 1. The panel data regressions control for country-sector, country-time, and sector-time fixed effects. Only results significant at the 10% level and above the critical value for the Kleibergen-Paap test statistic are reported.

The average intermediate import-employment elasticity is 0.42 percent, while final imports show an elasticity of 0.18 percent – less than half that size (Figure 1, left panel). Intermediate goods and services can be used in domestic production destined either for final consumption or exports and in both cases support job growth. The lower correlation between final imports of goods and services and employment in a sector implies that they also compete with domestic production and therefore employment.

Comparing trade-employment with trade-income elasticities suggests that the income channel is stronger, especially for imports. A 10 percent increase in exports is associated with a 3.9 percent increase in labor incomes over the full period 1995-2018. This implies that while exports have the potential to expand the number of jobs within a sector, they raise incomes more strongly. One explanation could be the productivity gains associated with exports which increase the average wage rate and thus total labor value added. More strikingly, a 10 percent increase in intermediate imports is on average correlated with

> 11 We use the Kleibergen-Paap test statistic and reject the hypothesis of weak instruments if the test statistic exceeds 10, following the rule of thumb by Staiger and Stock (1997). 12 Importantly, this only takes into account direct employment effects within sectors but does not consider indirect effects through job creation in supplying sectors, implying even larger employment potential of exports through supply-chain linkages. 13 The results of this extended analysis are available upon request.

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a 7.3 percent higher labor income, while the gain for final imports is 4.9 percent. Additional analysis by region and country is shown in Appendix Figures 9.1 to 9.3.

# 2.2 Which sectors are associated with the highest job and income increases?

Manufacturing sectors show the highest job and income growth associated with expanding exports in a sector, in particular those with high-medium technology intensity. Focusing on broad sectors reveals that export-employment elasticities are driven by manufacturing. A 10 percent growth in manufacturing exports is related to a 5.3 percent job growth (Figure 2). The potential for job creation through exports is particularly high in high-medium technology intensity manufacturing, including in motor vehicles, electrical equipment and computer and electronics (Figure 3, upper panel). This is despite the higher capital intensity of high-tech sectors, implying that capital and labor in these sectors are complementary.<sup>14</sup> Similarly, intermediate import growth in high-medium tech manufacturing sectors is related with high job growth which, to a large extent, is also used for export production (Figure 2).

**Figure 2: Trade-employment elasticities, by broad sector**

<!-- Start of picture text -->
1.2<br>1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>-0.2<br>-0.4<br>Agriculture, Mining Manufacturing Mfg - low tech Mfg - medium Mfg - high- Business Other services<br>fishing tech med. tech services<br>Exports Intermediate imports Final imports<br><!-- End of picture text -->

Source: Own computations. Data: OECD TiE and TiVA data, covering 48 countries (see Appendix 2) and 45 sectors for the period 1995-2018. Note: Trade-employment (trade-income, resp.) elasticities at the country-sector level have been estimated using employment (in natural logs) as dependent variable and the instrumented trade variables (in levels and natural logs) as independent variable. For more information on the instruments, see Appendix 1. The panel data regressions control for country-sector, country-time, and sector-time fixed effects. Only results significant at the 10% level and above the critical value for the Kleibergen-Paap test statistic are reported.

While some low- and medium-tech manufacturing sectors create many jobs when exports rise, capitalintensive sectors show workforce contractions. Some low- and medium-tech manufacturing sectors, in particular exports of paper products as well as rubber and plastics, create many jobs. Surprisingly, we do not find a positive link with employment in the textiles and apparel sector, but only with labor incomes (Figure 3). Possible explanations include the strong reduction of apparel jobs in China, India and other emerging countries (as discussed further in section 3). Other sectors have negative export-employment elasticities, most notably machinery, food and beverages, fishing and aquaculture and mining which tend to be capital-intensive, explaining the decline in the number of jobs. This finding could also be partially explained by the country sample excluding low-income countries for which exports in sectors like fishing or small-scale and artisanal mining create job opportunities.<sup>15</sup>

> 14 Evidence for Greece during the second half of the 1990s found that high technology and capital-intensive manufacturing sectors contributed most strongly to net employment growth (Voulgaris, Papadogonas, Agiomirgianakis 2005).

> 15 - - Globally, around 40 million people are estimated to work in small-scale mining (https://www.reuters.com/article/us <u>mining asm/more-than-40-million-people-work-in-artisanal-mining-report-idUSKCN1S025C), while almost 60 million people work in</u> fisheries and aquaculture (https://www.fao.org/3/cc0461en/online/sofia/2022/fisheries-aquaculture-employment.html).

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**Figure 3: Export-employment (upper) and export-income elasticities (lower panel), by disaggregated sector**

<!-- Start of picture text --> 0.49 0.47<br>0.42<br>0.35 0.31<br>0.21 0.18 0.15 0.11 0.11<br>-0.11 -0.13 -0.16<br>-0.23<br>-0.30 -0.33<br>1.36<br>0.78 0.75 0.72 0.71 0.68 0.64 0.63 0.63<br>0.56 0.53 0.48<br>0.38 0.36 0.35 0.33 0.32 0.31 0.28<br>0.16<br>-0.25<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE and TiVA data, covering 48 countries (see Appendix 2) and 45 sectors for the period 1995-2018. Note: Trade-employment (trade-income, resp.) elasticities at the country-sector level have been estimated using employment (labor income, resp.) (in natural logs) as dependent variable and the instrumented trade variables (in levels and natural logs) as independent variable. For more information on the instruments, see Appendix 1. The panel data regressions controls for country and sector fixed effects. Only results significant at the 10% level and above the critical value for the Kleibergen-Paap test statistic are reported.

In sharp contrast to manufacturing, aggregate business services exports show no significant association with within-sector employment creation, while their potential to generate labor income is much higher. Across the sample of 45 disaggregated sectors, only wholesale and retail trade, land transport, and professional services exports are positively associated with employment growth in these sectors over the period 1995-2018. But the link with labor incomes is even stronger in these business services sectors, in the case of trade and transport more than six times higher. Exports of health services, on the other hand, can reduce employment within the sector, if medical services providers such as doctors or nurses temporarily move to another country to export services. In addition, health services can also be offered to foreign consumers within a country, known as medical tourism. It is therefore not surprising that health exports create higher labor income, as the relative supply of labor in the sector declines with export expansion, while the relative demand for health providers increases which is exacerbated in the case of medical tourism. Interestingly, accommodation and restaurant exports which are associated with tourism do not increase the number of jobs in the sector but raise labor incomes.

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# 2.3 How do GVCs shape the trade-jobs nexus?

A country’s type of GVC engagement matters for employment growth through exports. The World Bank (2020) proposed a GVC taxonomy that differentiates between four types of GVC participation: (1) commodities; (2) limited manufacturing; (3) advanced manufacturing and services; and (4) innovative activities. The classification is based on the extent of backward GVC participation of the manufacturing sector, the types of goods and services exported, and measures of innovation (see Appendix 3). Our analysis finds that the way in which countries engage in GVCs seems to matter for the magnitude of export-employment elasticities in the sample of 48 OECD and non-OECD countries (Figure 4). The link between exports and employment for countries participating in commodities (0.06 percent) and innovative tasks (0.02 percent) is less than half the magnitude of countries at the advanced manufacturing and services stage (0.14 percent). A similar and even stronger relationship is found for labor incomes.

**Figure 4: Export-employment, export-income elasticities and skills supply, by taxonomy group**

<!-- Start of picture text --> Export-employment and export-income elasticities Employment shares by skills, 2018<br>0.25 100%<br>16 20<br>30<br>0.20 80% 43<br>0.15 60%<br>72 64<br>0.10 40% 56<br>48<br>0.05 20%<br>0.00 0% 13 17 14 9<br>Commodities Limited Advanced Innovative Commodities Limited Advanced Innovative<br>manufacturing manufacturing activites manufacturingmanufacturing activities<br>and services and services<br>Employment Total labor income Low-skilled Medium-skilled High-skilled<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE and TiVA data, covering 48 countries (see Appendix 2) and 45 sectors for the period 1995-2018. Note: Export-employment (export-income, resp.) elasticities at the country-sector level have been estimated using employment (in natural logs) as dependent variable and the instrumented trade variables (in levels and natural logs) as independent variable. For more information on the instruments, see Appendix 1. The panel data regressions control for country-sector, country-time, and sector-time fixed effects. Only results significant at the 10% level and above the critical value for the Kleibergen-Paap test statistic are reported. GVC taxonomy group by World Bank (2020). Skills (right panel) are determined by ILO statistics depending on their skill levels with high-skilled referring to levels 3 and 4, mediumskilled to level 2 and low-skilled to level 1. See https://ilostat.ilo.org/resources/concepts-and-definitions/classification-occupation/.

Several explanations can be offered for the skewed inverted U-shape of elasticities along the GVC taxonomy groups. Once countries upgrade from exporting mainly commodities (notably agricultural staples) to participation in limited manufacturing GVCs, this boosts export-induced demand for jobs in the manufacturing sector, as workers move out of informal (subsistence farming) into low-wage manufacturing jobs in apparel, electronics and other labor-intensive sectors. Higher exports of countries specializing in advanced manufacturing and services GVCs are linked to the highest employment growth within sectors due to additional demand for jobs alongside low-tech manufacturing jobs, especially in medium-tech manufacturing but also business services (such as trading and transport). Countries specializing in innovative GVC tasks, however, see their elasticities decline. Possible factors for the lower potential of exports to create jobs in these countries include the higher capital intensity of high-tech manufacturing production sectors, increased automation of routine tasks replacing certain types of workers, and offshoring of low-skill intensive tasks to low-cost countries. The composition of labor supply by skill-intensity of occupations for the different country types confirms the described pattern, showing a notable expansion of high-skilled occupations along taxonomy groups (right panel).

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Focusing on the type of GVC participation across HMICs (regardless of their specialization in GVCs) suggests a stronger employment and income boost from forward GVC participation. Expanding imports of intermediates used for export production (i.e., backward GVC participation) is positively related to employment and income growth in a sector (Figure 5). A higher share of domestic value added used in third countries’ exports (i.e., forward GVC participation) has stronger benefits which seems surprising, given the low elasticities for commodity exporters that are characterized by high forward GVC participation (Figure 4). The lack of low-income countries in the country sample may explain the large positive elasticity of forward GVC participation, as intermediate exports used for further export production in other countries contain higher value-added inputs such as research or design services, as opposed to raw commodities. This confirms earlier results by Stolzenburg et al. (2019) suggesting a stronger correlation between forward GVC participation and value added within sectors in HMICs. The findings confirm the larger strength of the income channel relative to the employment channel.

**Figure 5: GVC participation-employment and GVC participation-income elasticities, by sectors, 1995-2018**

<!-- Start of picture text --> GVC participation-employment elasticities<br>1.0<br>0.5<br>0.0<br>-0.5<br>Total Agriculture, Mining Manufacturing Mfg - low tech Mfg - medium Mfg - high-med. Business Other services<br>fishing tech tech services<br>Backward GVC Forward GVC<br>GVC participation-income elasticities<br>1.00<br>0.50<br>0.00<br>-0.50<br>Total Agriculture, Mining Manufacturing Mfg - low tech Mfg - medium Mfg - high- Business Other services<br>fishing tech med. tech services<br>Backward GVC Forward GVC<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE and TiVA data, covering 48 countries (see Appendix 2) and 45 sectors for the period 1995-2018. Note: GVC participation-employment (GVC participation-income, resp.) elasticities at the country-sector level have been estimated using an instrumental variables regression approach with employment (in natural logs) as dependent variable and the instrumented trade variables (in levels and natural logs) as independent variable. The panel data regressions control for country-sector, country-time, and sector-time fixed effects. Only results significant at the 10% level and above the critical value for the Kleibergen-Paap test statistic are reported. For more information, see appendix 1.

A closer look at broad sectors suggests that the employment and income benefits from GVC participation are driven by manufacturing. Manufacturing job growth linked to export growth is higher when those exports are re-exported by a country’s trade partners (i.e., forward GVC participation) as opposed to job growth linked to growth of imported inputs in exports (i.e., backward GVC participation), as evidenced by the higher trade-employment elasticities for the former type of trade engagement (0.57 percent vs. 0.32 percent in Figure 5, top panel). The difference is most striking in the high-tech manufacturing sector which includes electronics, machinery, transport equipment and chemicals. In 9
medium- and low-tech manufacturing sectors, the labor market gains through the income channel appear to be stronger (bottom panel). Higher forward GVC participation in mining also shows a strongly positive association with labor incomes (but not employment). Both forward and backward GVC participation show a negative correlation with employment (but not labor incomes) for agriculture/fishing and business services. Increases in agricultural or business services exports in MICs possibly go hand in hand with laborsaving skill-intensive machinery and technology, thus reducing the demand for workers.<sup>16</sup> Additional analysis by region is shown in Appendix Figure 9.4.

# 2.4 How are trade-job linkages characterized in lower-income countries?

In LMICs, manufacturing exports – especially of low-tech manufactured goods – are associated with larger employment increases than exports within agriculture or mining. This section focuses on the sample of 37 LMICs in EAP, SA, LAC, MENA and SA from the ETD database, differentiating between commodity exporters and countries specialized in limited manufacturing (see Appendix 2). For commodity exporters, total goods exports show a positive association with within-sector employment, although it is very small (coefficient of 0.03 percent). The link is insignificant in agriculture which is land-intensive, but positive in both mining and manufacturing, with a slightly larger coefficient for the latter (Figure 6). For countries specialized in limited manufacturing, exports show a negative relationship with employment in agriculture, possibly driven by more intensive use of agricultural machinery in such countries complementing the increase in land use. By contrast, there is a positive and larger export-employment link in low-tech manufacturing.

However, the link between low-tech manufactured exports in lower-income countries and job creation is substantially smaller than for the full sample of HMICs, possibly driven by the stronger role of informality. A 10 percent increase in exports of low-tech manufactured goods in LMICs specialized in limited manufacturing is associated with a 1.3 percent rise in employment – both formal and informal – within sectors (Figure 6). Compared with the sample of HMICs (Figure 2), the elasticity is only about onethird their magnitude. This can be explained by the fact that informal workers account for a large portion of employment in lower-income countries due to the lack of unemployment benefits. Export expansion thus leads to substitution effects, where workers move from informal to formal employment (including within sectors) resulting in lower net gains for overall employment numbers. As shown in Appendix Figure 9.5, export growth of goods and services over the period 1991-2019 is indeed positively correlated with increases in the share of paid (wage and salaried workers) in total employment across a large set of countries.<sup>17</sup>

> 16 Examples for labor-saving technology in agricultural production include tomato harvesters, shake-and-catch systems to harvest tree nuts, and wine grape harvesting machines. In Asia and Africa, agricultural production also increasingly relies on outsourced services providers of agricultural machines such as tractors (Christiaensen, Rutledge, and Taylor 2020). A similar argument could be made for business services exports which increasingly depend on information technology (e.g., travel services exports now rely less on travel agents).

17 Studies assessing local labor market effects of exports for South Asia and Mexico do not find any effect on the average employment rate, but confirm a reduction in informality (e.g., Artuc et al. 2019, Robertson et al. 2020, Vazquez and Winkler 2023). Second, a large number of manufacturing jobs in SSA have been created in the informal sector. A study by Kruse, Mensah, Sen, and de Vries (2023) based on the same ETD dataset suggests that these SSA countries experienced a ‘renaissance’ of their manufacturing employment share between 2000 and 2018, driven by unregistered firms that likely serve domestic or regional demand. On the other hand, Diao, Ellis, McMillan, and Rodrik (2021) find that large manufacturing firms in SSA are productive and participate in GVCs, but do not expand employment. The large role of informal activity in creating jobs may be rooted in differences in the enabling environment, a bias against low-wage workers in GVCs, or a combination thereof. A recent study suggests that while GVC participation and manufacturing output shares are positively associated in a large sample of 91 countries, this is driven by HMICs and is insignificant for many low-income countries many of which being commodity exporters. The study 10
**Figure 6: Goods export-employment elasticities in lower-income countries, by type of GVC specialization**

<!-- Start of picture text --> 0.15<br>0.10<br>0.05<br>0.00<br>-0.05<br>-0.10<br>Total goods Agriculture Mining Manufacturing Low-tech mfg<br>Commodity exporters Limited manufacturing<br><!-- End of picture text --> Source: Own computations. Data: ETD and Comtrade data, covering 37 countries (see Appendix 2) and 35 sectors for the period 1995-2018. Note: Export-employment elasticities at the country-sector level have been estimated using employment (in natural logs) as dependent variable and the instrumented trade variables (in levels and natural logs) as independent variable. For more information on the instruments, see Appendix 1. The panel data regressions control for country-sector, country-time, and sector-time fixed effects. Only results significant at the 10% level and above the critical value for the Kleibergen-Paap test statistic are reported. GVC taxonomy group by World Bank (2020).

# 3. Measuring jobs in exports: The role of supplying sectors

## 3.1 Do jobs in exports grow more strongly than other jobs?

Countries’ share of employment in exports in total employment varies considerably and is larger in small economies, but smaller in commodity-exporting countries. Analysis based on the OECD TiE database finds that smaller economies tend to show higher shares of employment in exports in their total employment, because their smaller market size dictates more openness to trade in the first place (Figure 7). The share of employment that is dependent on exports, including employment in supplying sectors, was 50 percent or higher in Ireland, Malta and Luxembourg in 2018, contrasting sharply with the United States where the share was less than 9 percent. However, commodity-exporting countries, even smaller ones, show a smaller dependence on employment in exports. Employment shares in exports range only between 10 and 15 percent in Saudi Arabia, Argentina, Colombia, Brazil and Australia. These low shares imply that exports of extractives in high- and middle-income countries are less labor-intensive, which is further aggravated by the “Dutch disease” reducing the competitiveness of non-commodity sectors or other constraints to diversifying the economy. The case of Argentina illustrates how closely the employment share supported by exports correlates with a country’s endowments of natural resources (Figure 8, left panel).

also highlights the role of rigid labor markets, low levels of human capital, underdeveloped capital markets, or an ineffective policy environment as possible factors (Kruse 2023).

11
<!-- Start of picture text --> a |<br><!-- End of picture text -->

<!-- Start of picture text --> 20 6<br>15<br>4<br>10 2<br>5 0<br>1995 2000 2005 2010 2015<br>Yeear<br>——— Export job share in %, left scale<br>———— Resource rent share in GDP in %, right scale<br><!-- End of picture text --> <!-- Start of picture text --> .25<br>SsLolN SVK<br>c CHN POL<br>-2<br>o LKA ROU<br>% TUR hay aR vn<br>c MEX K<br>2 45 PAK GHA iru<br>s . BGD Ipy<br>Qa LVA<br>25 1 aro BEALINI iD cRI KHM<br>2 . ETH oF<br>& PHL GRC<br>2 INPL cue<br>= 05<br>4 2 3 4 5<br>Export job share in 2017<br>R-squared= 0.24<br><!-- End of picture text -->
manufacturing sector which is associated with a higher share of jobs in exports (Figure 8, right panel). In Poland, for instance, shares increased from 19 to over 34 percent; in other words, over a third of the workforce is now supported by Poland’s exports. By contrast, the share of employment in exports stagnated in Cyprus and across many commodity-exporting countries, including in Canada, New Zealand, Chile, Colombia, Norway, and Indonesia. The latter is driven by declines after the commodity boom of the 2000s. Overall, employment growth in exports exceeded employment growth sustained by domestic demand between 1995 and 2018 (Figure 9).

**Figure 9: Export-driven vs. domestic demand-driven employment growth, 1995-2018 (CAGR)**

<!-- Start of picture text --> Export-driven vs. domestic demand-driven employment growth 1995-2018 (CAGR)<br>SAU<br>ISR LUX<br>CYP COLNZLIDN CHLAUS CRIZAF ARG<br>CAN MLT IRL<br>FINUSANORSWEBELGBR NLDKORCHEINDISL TURBRA ESPMEX<br>EST RUSCHNDNKITA FRA AUT<br>DEU<br>SVN SVK PRTHUNJPN GRC<br>CZE HRV POL<br>LTU LVA<br>BGR<br>ROU<br>-2 0 2 4 6<br>Employment growth sustained by exports (%)<br>EAP ECA LAC MENA<br>NA SA SSA y=x<br>R-squared= 0.12<br>4<br>2<br>0<br>-2<br>Employment growth sustained by domestic demand (%)<br><!-- End of picture text --> Source: Winkler, Aguilar-Luna, Kruse and Maliszewska (2023). Data: OECD TiE data, covering 51 countries and 45 sectors for the period 19952018. The country sample covers 38 OECD countries plus 13 non-OECD countries. The red line indicates employment growth in exports equals employment growth sustained by domestic demand.

# 3.2 In which countries and sectors are jobs in exports created?

Until the global financial crisis the number of jobs in exports increased strongly in emerging markets, dominated by jobs linked to manufacturing exports, but have started to decline since. Figure 10 plots the development of employment in exports for the sample of 51 countries by broad sector over the period 1995-2018, differentiating between high-income (top left panel) and LMICs (right panel) using the 1995 income categorization (see Appendix 8). In the sample of emerging countries, the number of jobs in exports increased from 177 million to 310 million between 1995 and 2007. This compares with total employment expanding from 1,343 million to 1,642 million over the same period in these countries. China and India alone added over 80 million and 30 million jobs in exports, respectively (bottom left and right panels). The number of jobs in manufacturing exports almost doubled from 107 million to 210 million over this period, representing an increase from 60 to 67 percent of the total, and driven in large part by China and India. However, jobs in exports dropped strongly in 2009 and continued to decline hovering around 255 million jobs between 2016 and 2018. Jobs linked to agriculture and mining exports combined now represent 9 percent of the total in emerging markets, while employment sustained by business services exports makes up over 27 percent. Here, China and India differ strongly, with India’s share of jobs in business services exports representing 36 percent in 2018, while China’s share makes up less than 20 percent.

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**Figure 10: Employment in exports (million), by broad sector and income category, 1995-2018**

<!-- Start of picture text --> High-income countries (as of 1995) Low- and middle-income countries (as of 1995)<br>100 350<br>90<br>300<br>80<br>70 250<br>60<br>200<br>50<br>40 150<br>30 100<br>20<br>50<br>10<br>0 0<br>Agriculture Mining Manufacturing Agriculture Mining Manufacturing<br>Business services Other services Business services Other services<br>China India<br>180 80<br>160 70<br>140<br>60<br>120<br>50<br>100<br>40<br>80<br>30<br>60<br>40 20<br>20 10<br>0 0<br>Agriculture Mining Manufacturing Agriculture Mining Manufacturing<br>Business services Other services Business services Other services<br>1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018<br>1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE data, covering 51 countries and 45 sectors for the period 1995-2018. Income categories as of 1995 are used to classify countries into high- and low- and middle-income countries (see Appendix 8).

Several underlying factors could explain the decline of export-linked employment in emerging markets over the past decades. While country experiences differ and the data sample does not cover all LMICs, the trend of declining jobs in exports has been linked to increased technology-intensity of production especially within GVCs because new technologies are related to higher-quality standards and high-skilled labor, raising the barriers for low-skilled labor in LMICs to participate in GVCs (Rodrik 2018). As part of their own upgrading efforts, some countries have started to outsource labor-intensive production themselves, most notably China, to lower-cost locations within the region, also increasing intra-regional trade. In fact, the number of jobs sustained by manufacturing exports in China plummeted after the global financial crisis, plateaued at the new lower level until 2015 and declined further (Figure 10, bottom left panel). The emergence of new low-wage countries on the global trade landscape, not included in the dataset, such as Vietnam has further helped this development.

By contrast, the number of jobs in exports increased steadily in high-income countries, driven by business services exports, showing only a brief dip after the global financial crisis. The number of jobs in 14
exports in our sample of high-income countries (as per their 1995 income category) grew from almost 60 million to around 90 million over the period 1995-2018 (Figure 10, upper left panel). Looking at the composition of employment in exports by broad sector highlights the importance of manufacturing and business services. However, while the share of manufacturing in total employment in exports of highincome countries contracted from roughly 55 to 44 percent over this period, the percentage of business services expanded from 39 to 48 percent. By contrast, other services, mining and agriculture only made up 6 to 7 percent of jobs in exports throughout the period.

Country experiences varied, with jobs in manufacturing exports falling rather in industrialized countries, while jobs sustained by business services exports expanded throughout the sample. Across the sample only roughly a quarter of the 51 countries have faced job losses in manufacturing exports since 1995, especially in industrialized Western European countries, most notably Cyprus, the Russian Federation, the United Kingdom and Romania, as well as the United States (Figure 11). At the same time, the number of jobs in business services exports grew strongly across all countries, in particular Ireland, South Africa, Iceland, Luxembourg, and Poland, reflecting the structural transformation in industrialized and emerging countries away from manufacturing and towards services. A few emerging countries showed higher growth of manufacturing-linked jobs than business services-linked jobs in exports, including Türkiye, Mexico, Chile, Czechia, Indonesia, Slovak Republic, and China, while Saudi Arabia’s job growth in exports stood out in both sectors.

**Figure 11: Export-driven employment growth, manufacturing vs. business services, 1995-2018**

<!-- Start of picture text --> 7<br>IRL SAU<br>6 ZAF<br>5 ISL LUX POL<br>4 PRTISRBRACRI INDGRCJPN ESPDEU COL ARG<br>321 CYP GBRRUSROU CANESTDNKUSANORSWEFINBELMLTAUSBGRSVNLTUFRANLD NZLITALVACHEHRVAUTKORSVKIDN HUN MEXTUR<br>CHL CZE<br>0<br>CHN<br>-1<br>-3 -2 -1 0 1 2 3 4 5 6 7<br>Manufacturing, 1995-2018 (CAGR)<br>EAP ECA LAC MENA NA<br>SA SSA All y=x Linear (y=x)<br>Business services, 1995-2018 (CAGR)<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE data. Note: The country sample covers 38 OECD countries plus 13 non-OECD countries. The orange line indicates the y=x line. CAGR = Compound annualized growth rate.

This trend is also visible at the detailed sector level, with emerging countries expanding more jobs sustained by manufacturing exports and high-income countries creating more jobs linked to business services exports. The top 15 expanding sectors between 1995 and 2018 in terms of jobs in exports (in % change) for low- and middle- versus high-income countries (as per their 1995 income categories) reflects the stronger role of manufacturing for the first group and the stronger role of business services for the latter group (Figure 12). In emerging countries, most jobs sustained by manufacturing exports were created in computer and electronics, whole and retail trade, machinery and equipment, electrical equipment and motor vehicles (left panel). In high-income countries, job creation was strongest in exports of administrative, professional, IT and financial and insurance services (right panel).

The highest job losses in high-income countries are related to manufacturing exports, while emerging markets experienced their largest declines in labor-intensive jobs linked to services, manufacturing and 15
agricultural exports alike. In high-income countries (using the 1995 income classification), the share of jobs supported by computer and electronics exports as well as apparel and textiles experienced the strongest decreases (Figure 13, right panel). In emerging markets, the share of jobs sustained by textiles and apparel exports contracted most sharply between 1995 and 2018, but other labor-intensive jobs related to exports of other manufacturing, accommodation and food services, agriculture, and wood and wood products also showed strong contractions (left panel).

**Figure 12: Employment in exports, top 15 expanding sectors (% pt change), 1995-2018, emerging vs. HICs**

|**Top 15 expanding sectors (% pt change), LMICs**|**Top 15 expanding sectors (% pt change), HICs**|
|---|---|
|4.8%<br>Computer, electronic and...|3.1%<br>Administrative and support...|
|3.5%<br>Wholesale and retail trade;...|2.5%<br>Professional, scientific and...|
|1.7%<br>Machinery and equipment, nec|1.4%<br>IT and other information...|
|1.6%<br>Electrical equipment|0.8%<br>Financial and insurance...|
|1.5%<br>Motor vehicles, trailers and...|0.6%<br>Mining and quarrying,...|
|1.0%<br>IT and other information...|0.6%<br>Pharmaceuticals, medicinal...|
|0.9%<br>Mining and quarrying, energy...|0.5%<br>Wholesale and retail trade;...|
|0.5%<br>Fabricated metal products|0.5%<br>Accommodation and food...|
|0.4%<br>Chemical and chemical products|0.5%<br>Education|
|0.3%<br>Pharmaceuticals, medicinal...|0.3%<br>Coke and refined petroleum...|
|0.3%<br>Other transport equipment|0.3%<br>Publishing, audiovisual and...|
|0.1%<br>Food products, beverages and...|0.3%<br>Land transport and transport...|
|0.1%<br>Warehousing and support...|0.3%<br>Rubber and plastics products|
|0.1%<br>Financial and insurance...|0.2%<br>Warehousing and support...|
|0.1%<br>Air transport|0.2%<br>Arts, entertainment and...|

Source: Own computations. Data: OECD TiE data, covering 51 countries and 45 sectors for the period 1995-2018. Income categories as of 1995 are used to classify countries into high- and low- and middle-income countries (see Appendix 7).

**Figure 13: Employment in exports, ten most contracting sectors, (% pt change), 1995-2018, emerging vs. HICs**

|**Ten most contracting sectors (% pt c**|**hange), LMICs**|**Ten most contracting sectors (% p**|**t change), HICs**|
|---|---|---|---|
|-5.9%<br>Textiles, textile products,...||-3.4%<br>Computer, electronic and...||
|Manufacturing nec; repair and...|-2.4%|-3.0%<br>Textiles, textile products,...||
|Accommodation and food...|-2.1%|Paper products and printing|-1.0%|
|Agriculture, hunting, forestry|-1.9%|Machinery and equipment, nec|-0.9%|
|Wood and products of wood...|-1.1%|Agriculture, hunting, forestry|-0.6%|
|Land transport and transport...|-0.6%|Food products, beverages and...|-0.5%|
|Mining and quarrying, non-...|-0.4%|Wood and products of wood...|-0.5%|
|Administrative and support...|-0.4%|Motor vehicles, trailers and...|-0.5%|
|Water transport|-0.4%|Manufacturing nec; repair...|-0.4%|
|Professional, scientific and...|-0.3%|Basic metals|-0.4%|

Source: Own computations. Data: OECD TiE data, covering 51 countries and 45 sectors for the period 1995-2018. Income categories as of 1995 are used to classify countries into low- and middle-income countries (see Appendix 8).

Some of these trends can be explained by offshoring from high-income countries, but also from large emerging countries, most notably China. While part of the job shifts linked to computer and electronics exports may be substitution due to offshoring from high-income to emerging markets, the absolute numbers reveal that emerging markets in the sample added over 14 million jobs, while in high-income countries only 0.77 million jobs were lost. The strong decline in jobs sustained by apparel exports was 16
driven by the period after the global financial crisis with over 26 million jobs lost between 2007 and 2018, of which 22.5 million can be attributed to China and 4 million to India, while some countries added jobs linked to apparel exports, most notably Indonesia, Türkiye, South Africa, and Mexico.

# 3.3 Are more jobs created in exporting or supplying sectors?

The sources of employment in exports can be further decomposed into the direct and indirect portions as well as domestic demand. The decomposition of employment in exports allows to identify jobs (1) directly in the exporting sector and (2) indirectly in sectors supplying to the export sector, while (3) the contribution of reimported inputs is negligible. The difference between a country’s total employment and employment in exports to a large extent reflects jobs created by domestic demand.<sup>18</sup> Figure 14 plots the full decomposition, ranked by the total employment share in exports. While the contribution of other sources of job creation varies across countries (yellow bar), the indirect contribution of supplying sectors on average tends to be smaller than the direct contribution across all countries, masking strong sectoral differences.

**Figure 14: Decomposition of employment in exports and domestic demand, 2018**

<!-- Start of picture text --> 100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>direct exports indirect exports reimported exports other demand<br>LUX MLT IRL BGR SVN SVK CZE EST HUN NLD LTU LVA BEL POL HRV CHE AUT CYP ISL PRT CRI ROU DNK DEU SWE ESP GRC FIN ITA NZL KOR MEX ZAF FRA CAN GBR CHL ISR TUR RUS NOR IDN AUS CHN JPN BRA COL IND ARG SAU USA<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE. The country sample covers 38 OECD countries plus 13 non-OECD countries. Note: Employment in exports can be decomposed into its (1) direct contribution in the exporting sector, (2) indirect contribution in sectors supplying to the export sector, and (3) contribution of reimported inputs.

Linkages to supplying sectors have been traditionally high for manufacturing exports, exceeding 62 percent of jobs in exports on average in 2018 (Figure 15). These can include agricultural inputs used in the food and beverages export sectors (such as fruits and vegetables), agricultural inputs used in apparel and shoe exports (such as cotton or hides and skins), but importantly also business services used in all of manufacturing exports (ranging from research and development, to design, to transport and logistics, to marketing services) – which all create jobs. In other words, the high export-employment elasticities found in manufacturing (section 2) underestimated their potential to create jobs in other sectors. Similarly, mining exports are known to create jobs in other sectors, in particular supporting services industries.<sup>19</sup> Interestingly, the share of indirect jobs linked to mining exports has expanded from 46 to 64 percent between 1995 and 2018, or that of direct jobs declined from 54 to 36 percent. This may be linked to

> 18 While the computation of jobs sustained by domestic demand would require international input-output data, this is a reasonable estimate.

> 19 Estimates of job multipliers in non-mining sectors for Sweden’s mining sector range from 0.2 to 0.5 percent, i.e., one mining job supports between 0.2 to 0.5 jobs in other sectors. It is highest in services including retail trade, transport, and hotels and restaurants (Moritz et al. 2017).

17
increased capital intensity of mining, with the arrival of new labor-saving machines, technology and tools reducing the need for labor directly in the mining sector.<sup>20</sup> For business and other services exports and especially agricultural exports, the direct employment creation is much larger than the indirect job creation. Direct job creation represented 88 percent of jobs linked to agricultural exports, because linkages to supplying sectors in agriculture are restricted to few inputs such as fertilizers, other chemicals, seeds, and planting materials. However, the share of indirect jobs linked to agricultural exports has doubled since 1995 (not shown). Similarly, business and particularly other services exports create jobs mainly directly within the export sectors, with the indirect contribution representing one-third in business services and one-fifth in other services.

**Figure 15: Direct and indirect employment in exports, by broad sector and income level, 2018**

<!-- Start of picture text --> 100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>Agriculture & Mining Total Manufacturing Total Business Services Other Services<br>Fishing<br>direct indirect reimported<br>High Upper- middle Lower- middle High Upper- middle Lower- middle High Upper- middle Lower- middle High Upper- middle Lower- middle High Upper- middle Lower- middle<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE. The country sample covers 38 OECD countries plus 13 non-OECD countries. Note: Employment in exports can be decomposed into its (1) direct contribution in the exporting sector, (2) indirect contribution in sectors supplying to the export sector, and (3) contribution of reimported inputs.

The analysis highlights different upgrading patterns along countries’ income levels for broad sectors. In business and other services, the indirect job creation loses importance for upper-middle and highincome countries (Figure 15). As countries develop, the range of possible services to be exported seems to increase and thus the amount of jobs linked to those exports. For instance, rather than exporting only support services more innovative countries offer sophisticated services exports including research and development, design, IT and programming, or financial services, among others. While the direct contribution is generally lower in manufacturing, it is highest for high-income countries amounting to 46 percent in 2018 compared to less than 30 percent in upper-middle income countries. It may be possible that as countries develop, exports create new job opportunities within the manufacturing sector, such as the increased need for technicians, engineers, and managers (see section 4).<sup>21</sup> The higher sophistication of services in high-income countries may also explain the patterns in agriculture and mining. In agriculture, the share of indirect jobs created in supplying sectors increases at higher income levels, in line with higher intermediate usage intensity of richer countries in the production of agriculture (Sposi 2019). While the contribution of supplying sectors to jobs in mining exports is much higher than in agriculture, their role increases slightly with higher income levels (Figure 15). Lower-middle income countries tend to create employment mainly in the agricultural export sectors with few linkages to upstream sectors such as necessary transport and logistics services to export these agricultural goods.

> 20 Technological progress in the U.S. copper sector, for instance, has been linked to labor productivity growth in the 1970s, 1980s and 1990s. It includes the use of solver extraction and electrowinning technology, larger trucks, shovels and drills, in-pit mobile crushers and conveyor belt systems, computerized scheduling of trucks, and real-time process controls (Sánchez and Hartlieb 2020).

> 21 If these activities are performed within the boundaries of the same company, rather than by an independent services provider, they should be statistically counted as part of the direct job contribution.

18
High-income countries are characterized by stronger linkages to supplying sectors in which jobs are created, such as in professional services (e.g., technicians or engineers to maintain machines or greenhouses), but also in research and development (e.g., to optimize the ripening process of fruits or to improve the quality of seeds). While mining exports create a much higher percentage of jobs in supplying sectors than agricultural exports, a similar explanation could hold. Additional analysis by broad sector and world region is shown in Appendix Figure 9.6.

Finally, focusing on detailed export sectors for emerging vs. high-income countries separately highlights stark differences, with high-income countries showing a larger direct contribution across most manufacturing and business services sectors. Figure 16 shows the decomposition of employment in exports into their direct, indirect and reimported shares for detailed industries, differentiating between the sample of high-income countries and that of emerging countries (using the 2018 income category).

**Figure 16: Direct and indirect employment in exports, detailed sector, 2018**

<!-- Start of picture text --> Middle-income countries High-income countries<br>Coke and refined petroleum...10.7% 88.7% Coke and refined petroleum...9.6% 89.2%<br>Food products, beverages and...14.3% 85.6% Water transport 28.6% 70.9%<br>Computer, electronic and... 19.0% 79.0% Mining and quarrying, energy... 28.8% 70.8%<br>Pharmaceuticals, medicinal... 20.3% 79.5% Chemical and chemical products 33.9% 65.3%<br>Chemical and chemical products 23.2% 76.4% Air transport 36.0% 63.7%<br>Basic metals 26.5% 73.1% Pharmaceuticals, medicinal... 36.2% 63.1%<br>Other transport equipment 27.7% 71.6% Food products, beverages and... 36.5% 63.1%<br>Mining support service activities 29.0% 70.6% Real estate activities 38.0% 61.9%<br>Electrical equipment 29.3% 70.0% Electricity, gas, steam and air... 38.4% 61.4%<br>Motor vehicles, trailers and... 29.8% 69.7% Motor vehicles, trailers and... 39.5% 59.0%<br>Rubber and plastics products 30.4% 69.2% Mining and quarrying, non-... 39.9% 60.0%<br>Telecommunications 31.4% 68.4% Basic metals 40.7% 58.4%<br>Air transport 31.5% 68.2% Telecommunications 43.3% 56.4%<br>Publishing, audiovisual and... 32.7% 67.2% Other transport equipment 43.7% 55.2%<br>Mining and quarrying, energy... 33.0% 66.8% Computer, electronic and... 46.4% 52.8%<br>Machinery and equipment, nec 34.7% 64.8% Paper products and printing 51.6% 48.0%<br>Water transport 38.8% 60.7% Electrical equipment 51.8% 47.4%<br>Paper products and printing 40.0% 59.8% Wood and products of wood... 52.4% 47.3%<br>Textiles, textile products,... 41.5% 58.2% Machinery and equipment, nec 53.1% 46.2%<br>Fabricated metal products 42.6% 57.0% Publishing, audiovisual and... 55.3% 44.5%<br>Mining and quarrying, non-... 42.8% 57.1% Rubber and plastics products 56.2% 43.2%<br>Other non-metallic mineral... 42.9% 56.8% Other non-metallic mineral... 56.7% 43.0%<br>Accommodation and food... 43.6% 56.4% Financial and insurance activities 57.9% 41.9%<br>IT and other information services 44.4% 55.5% Water supply; sewerage, waste... 60.6% 39.4%<br>Wood and products of wood... 44.4% 55.5% Warehousing and support... 60.8% 39.0%<br>Electricity, gas, steam and air... 44.5% 55.3% Manufacturing nec; repair and... 64.1% 35.5%<br>Real estate activities 45.7% 54.2% Textiles, textile products,... 65.4% 34.3%<br>Water supply; sewerage, waste... 53.4% 46.6% Fabricated metal products 66.7% 32.8%<br>Manufacturing nec; repair and... 54.4% 45.4% Construction 67.6% 32.3%<br>Financial and insurance activities 55.5% 44.4% Land transport and transport... 68.7% 31.1%<br>Construction 63.3% 36.7% IT and other information services 69.3% 30.5%<br>Land transport and transport via... 64.0% 35.9% Fishing and aquaculture 69.4% 30.5%<br>Warehousing and support... 66.6% 33.3% Mining support service activities 71.0% 29.0%<br>Public administration and... 70.3% 29.7% Public administration and... 72.7% 27.2%<br>Administrative and support... 71.6% 28.3% Agriculture, hunting, forestry 75.8% 24.0%<br>Professional, scientific and... 73.3% 26.6% Professional, scientific and... 76.1% 23.8%<br>Human health and social work... 77.5% 22.5% Accommodation and food... 77.3% 22.6%<br>Arts, entertainment and... 80.0% 20.0% Wholesale and retail trade;... 77.3% 22.5%<br>Fishing and aquaculture 80.4% 19.6% Arts, entertainment and... 77.4% 22.5%<br>Wholesale and retail trade;... 83.2% 16.7% Postal and courier activities 80.6% 19.3%<br>Postal and courier activities 83.6% 16.4% Administrative and support... 82.9% 17.0%<br>Education 89.5% 10.5% Other service activities 83.8% 16.2%<br>Other service activities 89.8% 10.2% Human health and social work... 84.6% 15.4%<br>Agriculture, hunting, forestry 91.4% 8.6% Education 88.6% 11.4%<br>0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100%<br>direct indirect reimported direct indirect reimported<br><!-- End of picture text --> Source: Own computations. Data: OECD TiE. The country sample covers 38 OECD countries plus 13 non-OECD countries. Note: Employment in exports can be decomposed into its (1) direct contribution in the exporting sector, (2) indirect contribution in sectors supplying to the export sector, and (3) contribution of reimported inputs. Income category of 2018 used (see Appendix 8).

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In electronics and computers, for example, jobs directly linked to exports make up 19 percent of total jobs in exports in the sector in emerging countries, but 46 percent in high-income countries. In motor vehicles, the direct contribution is around 30 percent for emerging but 40 percent for high-income countries. Similar differences can be found for electrical equipment (29 vs. 51 percent), machinery (35 vs. 53 percent), but also textiles and apparel (41 vs. 65 percent), and all other manufacturing sectors except for coke. Similarly, business services export sectors show a larger direct job contribution in high-income countries such as in IT or professional services than in emerging economies. The direct contribution is smaller in agriculture, mining, and non-tradable services in high-income countries. This again reflects the higher portion of sophisticated services activities directly embodied in such exports.

# 4. Measuring job activities in exports: The role of occupations

## 4.1 Upgrading of jobs in exports across sectors

Reporting job numbers created by exports alone masks differences in the activities that countries specialize in along the value chain. The distribution of job activities in exports across five occupation categories (see Appendix 5 for details) in a sample of 59 countries and 20 industries for the years 2000 and 2018 suggests a declining role of production activities (including craft workers, machine operators, and farm laborers, among others), as countries’ per capita income progresses (Figure 17, upper panels). For the poorest countries production activities represented almost 70 percent of their exports in 2018, but this percentage dropped by almost half in the richest countries (upper-right panel). In upper-middle income countries, non-production activities become increasingly important for their exports, in particular managerial occupations, but also engineering and support services. The role of support services activities in exports, such as sales representatives or office clerks, magnifies especially for high-income countries, with their share exceeding that of production activities for the richest countries.

Several channels help explain the changing distribution of jobs in exports across occupational groups as countries develop. First, as countries become richer their comparative advantage and thus composition of their export basket changes. Second, GVC upgrading can foster a structural transformation of jobs (World Bank forthcoming). Once countries upgrade into more advanced segments of manufacturing and services GVCs, for instance, more non-production activities are embodied in a country’s exports relative to production activities, including managerial, engineering and especially other support services activities. Third, supply linkages between sectors also adjust, with the “servicification” of manufacturing exports gaining in importance as countries develop (Nayyar, Hallward-Driemeier, and Davies 2021). For instance, while food exports in low-income countries often consist of raw commodities or staples, food exports in middle- and high-income countries increasingly rely on sophisticated services embodied in those food exports beyond logistics, transportation and trade services, and include engineering, support and other services (e.g., health inspections).

In addition, changes in productivity trigger changes in relative wages across occupations which are reflected in incomes in exports (rather than jobs in exports) measures. Not surprisingly, managerial and engineering services activities account for a larger share in lower-income countries when using the income in exports measure as opposed to the jobs in exports measure (Figure 17, lower panels). This is because average incomes (and productivity levels) are higher for managers and engineers relative to workers in production and support services occupations in lower-income countries, as they are endowed with a larger relative supply of low-skilled workers (e.g., de Vries, Timmer, and de Vries 2015; McMillan, Rodrik, and Sepulveda 2017). However, such differences decline as countries get richer because relative wage gaps between these occupation categories fall.

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<!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>2,500 5,000 10,000 20,000 40,000<br>GDP per capita, log scale<br><!-- End of picture text --> <!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>2,500 5,000 10,000 20,000 40,000<br><!-- End of picture text --> <!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>2,500 5,000 10,000 20,000 40,000<br>GDP per capita, log scale<br><!-- End of picture text --> <!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>2,500 5,000 10,000 20,000 40,000<br>GDP per capita, log scale<br><!-- End of picture text --> <!-- Start of picture text --> HEE Engineering ME Managerial<br>MEE Support services [EJ Production<br>HE «Others<br><!-- End of picture text -->
grow rich, their relative demand switches from agricultural and basic manufactured goods (which tend to be production-intensive) towards more advanced manufactured goods and services (which tend to be cognitive/non-production-intensive). While incomes expanded in both country groups, many LMICs moved from consuming agricultural to basic manufacturing activities (so production-intensity not changing much), whereas high-income countries monotonically move into paying more for nonproduction activities (Kongsamut et al. 2001, Comin et al. 2021).

As a result of these different underlying channels, the composition of job activities in exports across select countries varies.<sup>22</sup> The analysis for select countries suggests that resource-intensive countries, like Indonesia, Kyrgyz Republic, Brazil, and Ghana, tend to have smaller shares of production activities in exports compared to GVC-intensive countries such as Vietnam, Mexico, Poland, and Ethiopia (Figure 18). It is well established that countries with a large mining sector depend on a strong services support system, as evidenced by the relatively large shares of support services jobs and other jobs (which mainly consist of services occupations). Managerial and engineering jobs matter more strongly for countries like Poland, Mexico and Sri Lanka that have successfully participated in manufacturing GVCs for several decades. While Vietnam’s GVC entry – especially in electronics – has been praised as a success story (World Bank 2020), its main challenge remains to upgrade into more non-production activities in exports with only little progress in the aggregate. Sector-specific analysis reveals even stronger differences between Vietnam and other countries (see section 4.3). Despite its dominance of agriculture, Ethiopia has been considered the posterchild of successful GVC integration, driven largely by the textiles and apparel industry (Fernandes et al. 2023). While in 2000 production activities dominated its jobs in exports with a share of 94 percent, this share dropped to 77 percent by 2018, lower than in Vietnam, whereas support services and other activities gained in importance.

While most countries underwent a transition towards more non-production activities in exports between 2000 and 2018, China’s stark upgrading experience was an exception. China’s jobs in exports underwent a significant transition between 2000, the year before its accession to the World Trade Organization, and 2018. While over 70 percent of China’s jobs in exports were production-related activities in 2000, this share fell to roughly 50 percent by 2018. At the same time, the percentage of nonproduction activities, especially of support services and engineering, went up (see Appendix 10). China’s upgrading trajectory differs from that of Mexico and Poland in two main aspects. First, they differ with respect to the types of activities that are embodied in their exports. While Poland’s upgrading trajectory also relied on support services activities, engineering and managerial activities already accounted for important shares of exports in 2000, also owing to its highly educated workforce. Mexico has increased its share of support services (especially in and engineering activities (especially in other manufacturing, machinery and transport equipment) in exports after 2004,<sup>23</sup> while reducing its share of other activities and production activities (Figure 18). Second, China’s fast transition pace over just 18 years is remarkable, given that activity employment shares move more slowly than sectoral employment shares. The reason is that workers move from production in agriculture to production in manufacturing at early developmental stages which reflects a sector shift but not a shift in the job activity itself.

> 22 One further way of exploring heterogeneity of activity specializations (instead of over income levels or specific countries) is to compare world regions. This is reported for the aggregate economy in 2000 and 2018 as well as within four broad industries in Appendix Figures 9.7 and 9.8. The results are broadly similar to the income-specific findings.

> 23 The increase in support services activities is driven by business services and that in engineering activities by other manufacturing, machinery and transport equipment.

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<mark>M</mark> EE Engineering (Manage <mark>rial</mark> MEE Support services [EJ Prod <mark>uction</mark> EE Others
<!-- Start of picture text --> 50<br>40<br>30<br>20<br>10<br>0<br>2,500 5,000 10,000 20,000 40,000<br>GDP per capita, log scale<br><!-- End of picture text --> <!-- Start of picture text --> 3<br>2<br>1<br>0<br>2,500 5,000 10,000 20,000 40,000<br>GDP per capita, log scale<br><!-- End of picture text --> <!-- Start of picture text --> 30<br>20<br>10<br>0<br>2,500 5,000 10,000 20,000 40,000<br>GDP per capita, log scale<br><!-- End of picture text --> <!-- Start of picture text --> 30<br>20<br>10<br>0<br>2,500 5,000 10,000 20,000 40,000<br>GDP per capita, log scale<br><!-- End of picture text --> <!-- Start of picture text --> HEE Engineering ME Managerial<br>MEE «Support services [EJ Production<br>HE Others<br><!-- End of picture text -->
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<mark>M</mark> EE Engineering MEE «Support services HE «Others ME Mana <mark>gerial</mark> [EM Production
<mark>M</mark> EE Engineering ME Mana <mark>gerial</mark> MEE «Support services [EM Prod <mark>uction</mark> HE «Others
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Examining patterns of total jobs in exports highlighted the importance of domestic supplying sectors in creating jobs and different patterns of sectoral specialization in high-income versus emerging countries. In manufacturing, employment in exports is higher in supplying sectors (e.g., services or agriculture) than in the exporting sectors themselves. Emerging countries added more jobs in manufacturing exports, while high-income countries created more jobs linked to business services exports. The latter made up for falling jobs in manufacturing exports (e.g., the US and Western Europe). The findings also highlight the growing number of jobs in business services exports across all countries, reflecting the structural transformation away from manufacturing and towards services in the sample of HMICs. A few emerging countries showed higher growth of manufacturing-linked jobs than business services-linked jobs in exports, including Türkiye, Mexico, Chile, Czechia, Indonesia, the Slovak Republic, and China.

Adding the occupational dimension to sectoral specialization patterns allowed us to assess different upgrading trajectories at the level of activities. Services activities in exports, such as support, engineering, and managerial services, are becoming increasingly important as countries get richer, while production activities continue to dominate the exports of lower-income countries. The analysis highlighted the fundamental shift in manufacturing activities taking place between 2000 and 2018, offering more opportunities for structural change in lower-income countries. The analysis also suggested that GVCintensive countries such as Vietnam, Mexico, Poland, and Ethiopia tend to have larger shares of production activities in exports compared to resource-intensive countries, like Indonesia, Kyrgyz Republic, Brazil, and Ghana. Even among countries that export similar products, the activities that workers perform have different implications for growth. For example, in Cambodia, textile workers have been stuck in low value-added production activities for two decades. On the other hand, in Türkiye, the labor composition of textile exports is more diverse and includes sophisticated managerial and engineering services.

Tailored policies are essential to harness the job creation benefits from trade. While trade policies are a fundamental instrument, long-term success also relies on minimizing worker adjustment costs influenced by macroeconomic conditions, labor markets, and infrastructure. Education plays a crucial role in enabling economies to seize trade opportunities by shaping skill supply and comparative advantage. Countries with a highly skilled workforce are better poised to engage in knowledge-intensive trade activities. Labor market flexibility, characterized by fewer regulations, supports worker mobility and correlates with higher export-driven employment. Lowering tariffs and non-tariff measures enlarges market size, especially in non-commodity exporting developing countries. Foreign direct investment in export sectors can boost labor demand and productivity, especially in countries with limited resources. Strong institutions, effective competition policies, and infrastructure are vital for generating high-quality jobs. Considering these factors can help policy makers maximize the job creation potential from trade while minimizing adjustment costs for workers.

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