Optimal Gradualism

This paper studies how gradualism affects the welfare gains from trade, technology, and reforms. When workers face adjustment frictions, gradual shocks create less adverse distributional effects in the short run. We show that there are welfare gains from inducing a more gradual transition via temporary taxes on trade and technology and provide formulas for the optimal path for taxes. Our formulas account for the possibility that reallocation effort responds to policy and for the existence of income taxes and assistance programs. Using these formulas, we compute the optimal temporary taxes needed to mitigate the distributional consequences of rising import competition from China and the deployment of automation technologies substituting for routine jobs. Our formulas can also be used to compute the optimal timing of economic reforms or trade liberalizations. We study Colombia’s trade liberalization in 1990 and conclude that optimal policy called for a more gradual reform. *Restrepo thanks the National Science Foundation for its support under award No. 2049427. We thank David Autor and Marcela Eslava for sharing their data and providing feedback on this project. We also thank Joao Guerreiro, Chad Jones, Michael Peters, and Nathan Zorzi for providing valuable comments and Nicolas Werquin for discussing our paper. Technological progress, trade, and economic reforms can generate periods of adjustment during which some workers fall behind, lose their jobs, experience wage declines, and see their livelihoods disrupted.1 Even if technology and trade are positive developments in the long run, dealing with these short-run disruptions remains an important policy concern, especially in the wake of rapid changes in the economy.2 Existing evidence points to large disruptions. Autor et al. (2014) document that an average US worker in an industry exposed to Chinese import competition experienced a cumulative income loss equal to half their annual earnings in 1990 over the 1992–2007 period relative to unexposed workers. Cortes (2016) shows that US workers who in 1985 held routine jobs—those that can be more easily automated—experienced a subsequent decline in wages of 16% by 2007 relative to similar workers in other occupations. How should policy respond during these adjustment periods? Do short-run disruptions imply that more gradual advances in technology and trade are preferable? This paper shows that short-run disruptions create potential gains from gradualism and justify temporary taxes on new technologies and trade or embracing gradual reforms. Our main contribution is to provide formulas for the optimal path for taxes on new technologies and trade that capture the gains from gradualism. We evaluate these formulas in a calibrated version of our model that matches the empirical estimates of Autor et al. (2014) for trade and Cortes (2016) for the automation of routine jobs. Our formulas call for temporary taxes on trade and automation technologies of 10%, phased out over time. We also use our formulas to study Colombia’s trade liberalization in 1990 and show that optimal policy called for a more gradual reform. We derive these formulas in a model where workers are displaced by technology or trade. Ex-ante identical workers are allocated across islands à la Lucas and Prescott (1974). Some islands represent jobs automated by new technologies (e.g., welding or data-entry clerks) or segments of industries disrupted by international trade (e.g., low-cost apparel or household electronics). At time t0, a new technology arrives, capable of replacing workers in these For evidence in the context of trade, see Autor and Dorn (2013); Autor et al. (2014). For evidence in the context of automation technologies, see Cortes (2016); Adão et al. (2021); Acemoglu and Restrepo (2020, 2022). Finally, see Goldberg and Pavcnik (2005) for evidence of how dismantling trade protection reduces the relative wages of workers in exposed industries. In the US, industrial robots installations and imports from China tripled in a few years (see Autor et al., 2013; Acemoglu and Restrepo, 2020, respectively), and the share of e-commerce in retail went from 0.6% to 10% from 1999 to 2019 (see US Census, 2022). As Erik Brynjolfsson and Andrew McAfee put it in The Second Machine Age, “People are falling behind because technology is advancing so fast and our skills and organizations aren’t keeping up” (Brynjolfsson and McAfee, 2014). Managing short-run disruptions is also a key policy concern when it comes to policy reforms (see, for example, Rodrik, 1995).