and Weber (2018) find that impacts tend to be larger during a recession. Training also affects women more than men, as well as participants who are returning from longterm unemployment. McKenzie (2017) finds only a modest impact, especially given the high cost of these programs,6 but Escudero et al. (2019) find that, in Latin America, these programs have been especially effective at increasing employment (including formal employment). It is nonetheless important to recognize that, even with the best policy responses in place, there are likely to be many who permanently lose from trade adjustment. For these groups, safety net measures may be the only possible response.
Implementing a Policy Agenda for Inclusive Trade Address Distributional Impacts through Preparation, Sequencing, and Consultation Understand potential distributional impacts ex ante On top of the complementary policies that governments employ to maximize gains from trade and ensure better distributional outcomes, there is significant scope to address many of these issues before undertaking reforms. In recent years, there have been big improvements in the availability of microdata and in computing power, and a growing number of real-time data sources (see chapter 2). Furthermore, a better understanding of the firm structure within value chains and production networks has improved our ability to predict how the impact of shocks (whether related to trade policy or other sources) is likely to propagate across borders, sectors, and population groups (Carvalho and Tahbaz-Salehi 2019; Huneeus 2018). Additionally, the availability of highly granular geospatial data enables analysis of the subnational distribution of economic activity at a very fine geographical scale. Increasingly precise big data sources from cell phones provide a much greater understanding of agglomeration dynamics, mobility, and population responses to shocks. These advances promise to continue to enhance our understanding of distributional impacts related to trade (Redding 2020). Governments now have numerous tools to support this analytical process. They increasingly use gender impact assessments, for example, to determine whether policy outcomes are likely to have differentiated outcomes for men and women (World Bank and WTO 2020). As demonstrated in the Sri Lanka case study in chapter 3, disaggregated analysis is also possible for the distributional outcomes between different regions within a country, across industries, and between high-skill and low-skill workers (Maliszewska, Osorio-Rodarte, and Gupta 2020). Such simulation exercises can make the process of developing complementary policies more proactive and data-driven and can also highlight trade-offs, such as when efficiency and equity objectives do not align. Even so, there is a quite limited understanding of what works best in different national contexts. Despite a growing number of randomized experiments looking
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The Distributional Impacts of Trade
