Finally, we combine the direct and indirect channels to assess the total (net) contribution of GVC participation to wage inequality within countries (Figure 5c).<sup>12</sup> We find that GVC participation is linked to higher wage inequality in the top high-income countries, such as the US and Ireland, which in most cases is driven by the indirect contribution of GVCs through its links with worker RTI. At the same time, GVC participation is associated with reduced wage inequality in most low- and middle-income countries (in particular Kenya and Ghana, but also Mexico), as well as the bottom high-income countries (Central Eastern and Southern Europe, in particular, Czechia and Poland) where the direct reduction in wage inequality is stronger than the indirect contribution.

The findings can be interpreted as follows. Our results suggest that in countries that mostly receive offshored jobs, GVC participation reduces wage inequality, despite widening the gap in the RTI of work between offshorable and non-offshorable occupations. However, in rich countries that mostly offshore jobs, GVC participation widens wage inequality as it benefits mainly workers in non-offshorable occupations in services.<sup>13</sup>

# 5. Conclusions and policy implications

In this paper, we investigated the relationship between GVC participation and the RTI of workers and its contribution to within-country wage inequality. We used a unique dataset combining worker-level, countryspecific RTI measures based on a pooled sample of survey data for 47 (38, resp.) countries at all development levels, applying the methodology of Lewandowski et al. (2022), with measures of backward and forward GVC participation at the country-sector level based on the method of Borin and Mancini (2019, 2015). We find that the relationship between GVC participation and the RTI of workers is complex and depends on the nature of GVCs, occupations and sectors. This study also finds that GVC participation contributes to wage inequality within countries directly and indirectly through its relationship with workers’ RTI.

First, we found that the relationship between GVC participation and RTI differs between types of GVC participation: higher forward GVC participation correlates with more RTI of workers, while higher backward GVC participation does not. Importantly, these associations differ across occupational groups. In countries and sectors with higher GVC participation of either type, workers in offshorable occupations perform more routineintensive work, with weaker associations for higher-income countries. At the same time, we find no such results among workers in non-offshorable occupations.

Second, the industrial sector, which produces primarily tradable goods, follows this general pattern, whereas business services, which are tradable to a lesser extent, do not. Higher backward GVC participation is associated with less routine-intensive tasks in business services, especially among workers in non-offshorable

> 12 As the Gini coefficient is a non-linear measure, the sum of Gini coefficients with two separate shocks (direct and indirect effect) does not necessarily equal the Gini coefficient simulated with the same two shocks jointly (total effect). The residual, however, is relatively small compared to the total contribution (see Figure B1 in Appendix A).

> 13 Our approach may raise the question if the RTI and wage regressions can be estimated separately. We use seemingly unrelated regression (SUR) to test the validity of our results. We find that separate estimation is correct. First, we find no correlation between the residuals from RTI and wage models, suggesting that they are unrelated. Additionally, we confirm that error terms have fairly symmetric distributions required for the estimator to be unbiased in small samples. Second, the point estimates are consistent with those obtained from separate estimations. Minor differences occur due to slight differences in the estimation sample. Some individuals do not report their wages, resulting in slightly smaller sample sizes than RTI models (see Tables 3 and 4). The SUR approach requires samples of both models to be equal, so the RTI sample must be reduced to a wage sample. The SUR estimates are available upon request.

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