An NBER conference on Economic Consequences of Trade took place April 5-6 in Cambridge. Research Associate Stephen J. Redding of Princeton University organized the meeting, sponsored by the Smith Richardson Foundation. These researchers' papers were presented and discussed:
Ryan Kim, Johns Hopkins University, and Jonathan Vogel, University of California, Los Angeles and NBER
Trade and Inequality across Local Labor Markets: The Margins of Adjustment
Empirical research has documented the importance of non-wage margins of adjustment in the response of local labor markets to trade shocks. To formalize this observation empirically, Kim and Vogel decompose the differential impact of a trade shock across U.S. local labor markets (by labor group) on per capita labor income into wage, hours worked per employee, unemployment, and labor force participation margins of adjustment. The results highlight the importance of heterogeneous treatment effects and quantify the relative importance of non-wage margins of adjustment. To understand the economic mechanisms generating observed effects of trade on regional inequality, the researchers provide a unifying trade framework (featuring frictional unemployment and a labor/leisure tradeoff) and comparative static results across local labor markets by labor group and margin of adjustment. The theory highlights the importance of heterogeneity in the elasticity of labor supply and the elasticity of matches to vacancies for understanding heterogeneous effects identified in empirical research. The researchers recover these for each labor group by combining their empirical and theoretical results and show that the estimates are broadly in line with vast literatures in labor, public finance, and macroeconomics -- where results differ, the researchers suggest a path forward.
Gene M. Grossman, Princeton University and NBER, and Elhanan Helpman, Harvard University and NBER
Identity Politics and Trade Policy (NBER Working Paper No. 25348)
Grossman and Helpman characterize trade policies that result from political competition when assessments of wellbeing include both material and psychosocial components. The material component reflects, as usual, satisfaction from consumption. Borrowing from social identity theory, the researchers take the psychosocial component as combining the pride and self-esteem an individual draws from the status of groups with which she identifies and a dissonance cost she bears from identifying with those that are different from herself. In this framework, changes in social identification patterns that may result, for example, from increased income inequality or heightened racial and ethnic tensions, lead to pronounced changes in trade policy. The researchers analyze the nature of these policy changes.
Paula Bustos, CEMFI; Joan Monras, Universitat Pompeu Fabra; Jacopo Ponticelli, Northwestern University; and Juan Manuel Castro Vincenzi, Princeton University
Structural Transformation, Industrial Specialization, and Endogenous Growth
The introduction of new technologies in agriculture can foster structural transformation by freeing workers who find occupation in other sectors. The traditional view is that this increase in labor supply in manufacturing can lead to industrial development. However, when workers moving to manufacturing are mostly unskilled, this process reinforces a country's comparative advantage in low-skill intensive industries. To the extent that these industries undertake less R&D, this change in industrial composition can lead to lower long-run growth. Bustos, Monras, Ponticelli, and Castro Vincenzi provide empirical evidence of this mechanism using a large and exogenous increase in agricultural productivity due to the legalization of genetically engineered soy in Brazil. The results indicate that improvements in agricultural productivity, while positive in the short-run, can generate specialization in less-innovative industries and have negative effects on productivity in the long-run.
Alonso de Gortari, Princeton University
Disentangling Global Value Chains
The patterns of production underlying the recent rise of global value chains (GVCs) have become increasingly complex. NAFTA supply chains, for example, are now deeply integrated: Using Mexican customs data, de Gortari finds that exports to the U.S. use a much higher share of American inputs than exports to other countries. However, the conventional framework used to measure GVCs ignores this heterogeneity since it assumes that all output uses the same input mix. De Gortari develops a new framework that combines input-output data with additional information on supply chain linkages in order to construct GVCs reflecting the use of inputs observed in the latter. Improving measurement matters quantitatively since it affects both value-added trade measures and counterfactual experiments: De Gortari shows that incorporating Mexican customs data raises the estimated share of U.S. value in U.S. imported Mexican manufactures from 17% to 30% and doubles the U.S. welfare cost of a NAFTA trade war.
Kevin Lim, University of Toronto; Daniel Trefler, University of Toronto and NBER; and Miaojie Yu, Peking University
Trade and Innovation: The Role of Scale and Competition Effects
Lim, Trefler, and Yu study the effects of trade on firm-level innovation in China. Using both econometrics and a calibrated structural model, they disentangle the mechanisms via which trade affects innovation, focusing on scale effects (impact on market size) and competition effects (impact on markups). The structural model also examines heterogeneity of these affects across firms and studies a new mechanism for competition effects: Firms can escape the competition by innovating into a market segment where competition is less intense. The econometric estimates and simulations of the calibrated structural model indicate that both scale and competition effects are important for understanding how trade affects innovation in China. In particular, scale effects of trade on innovation are positive in the aggregate, whereas competition effects are negative. However, when firms can innovate to escape the competition, greater competition induced by lower trade barriers can lead firms to increase innovation rather than reduce it.
Kirill Borusyak, Princeton University, and Xavier Jaravel, London School of Economics
The Distributional Effects of Trade: Theory and Evidence from the United States
Borusyak and Jaravel quantify the distributional effects of trade shocks in the U.S. through consumer prices (expenditure channel) and wages (earnings channel). A quantitative trade model links these channels to compositional differences in expenditures and earnings across household groups. New data reveal that spending shares on imports are similar across education and income groups, implying a neutral expenditure channel. Estimated differences in workers' exposure to import competition, exporting, and income effects indicate that the earnings channel favors college graduates. Overall, a uniform trade cost reduction generates welfare gains that are 25% larger for college graduates. Similar results apply to trade with China.
Donald R. Davis, Columbia University and NBER, and Eric Mengus and Tomasz K. Michalski, HEC Paris
Labor Market Polarization and the Great Divergence: Theory and Evidence
Two of the most important features of advanced labor markets in the past quarter century are labor market polarization and the great divergence. The first of these concerns the growth of jobs in high and low wage categories and the disappearance of middle wage jobs. The second is an explicitly spatial theory about the intensification of development particularly at the high end in large, already developed cities relative to smaller, less developed cities. Davis, Mengus, and Michalski address how the two phenomena are interrelated. The great divergence is typically contemplated in a two factor setting with skill-biased technical change. Labor market polarization is instead considered in an explicitly three-factor setting, specifically rejecting the simpler framework. The researchers develop a theory in which the driving forces of labor market polarization alone give rise to both phenomena, building on Autor and Dorn (2013), Davis and Dingel (2014) and Davis and Dingel (forthcoming). Key to this is that the productivity advantages in large cities are biased toward high skilled tasks, so that a uniform shock to technology leads to labor market polarization with a biased impact on cities of different sizes, giving rise to the great divergence. The researchers examine the model using detailed data for a sample of 117 French cities and find the patterns in the period 1994-2015 accord well with the theory.
Spencer Lyon, New York University, and Michael E. Waugh, New York University and NBER
Quantifying the Losses from International Trade
Did trade with China harm the U.S. economy in the 2000s? A popular narrative suggests that the rapid rise in Chinese import penetration lead to an expanding trade deficit and negative impacts on wages and employment within narrowly defined labor markets. Lyon and Waugh provide an alternative interpretation of this evidence by developing a dynamic, standard incomplete market model with Ricardian trade and frictional labor markets and calibrated to match local-labormarket evidence. Despite being consistent with the evidence of Autor et al. (2013), rising trade exposure induces a boom: an increase in GDP and employment, a modest increase in consumption, and an improving trade deficit. Much heterogeneity in the gains from trade underlays the aggregate effects -- however, very few actually lose from trade.
David Baqaee, University of California, Los Angeles, and Emmanuel Farhi, Harvard University and NBER
Networks, Barriers, and Trade
Baqaee and Farhi study a large non-parametric class of trade models with global production networks. They characterize their properties in terms of interpretable and measurable sufficient statistics. They provide both reduced-form results for measuring the sources of growth and structural results for conducting counterfactuals. The main objectives are to show how commonly-used stylized models can give misleading results because of simplifying assumptions regarding intermediate inputs, factors, elasticities, and distortions, to show how more complex models that do not rest on these assumptions work. As an example, accounting for nonlinear (non-Cobb-Douglas) production networks, with realistic complementarities in production, significantly raises the gains from trade relative to estimates in the literature. As another example, models with value-added production functions, no matter how well-calibrated, are incapable of simultaneously predicting the costs of tariff and non-tariff barriers to trade. Better quantitative accuracy demands the use of more complicated, oftentimes computational, models. The research seeks to help bridge the gap between computation and theory.
Rui Costa, Swati Dhingra, and Stephen J. Machin, London School of Economics
Trade and Worker Deskilling
Costa, Dhingra, and Machin present new evidence on the impact of international trade on worker outcomes, by examining a big world event that produced an unprecedentedly large shock to the UK exchange rate. In the 24 hours in June 2016 during which the UK electorate unexpectedly voted to leave the European Union, the value of sterling plummeted. It recorded the biggest depreciation that has ever occurred in any of the world’s four major currencies since the collapse of Bretton Woods. Exploiting this variation, the researchers study the impact of trade on wages and future earnings potential measured by job related education and training. Wages and training fell for workers employed in sectors where the intermediate import price rose by more as a result of the massive sterling depreciation. Calibrating the estimated wage elasticity with respect to intermediate import prices to theory uncovers evidence of complementarity between workers and intermediate imports. This provides new direct evidence that, in the modern world of global value chains, the cost of intermediate imports acts as an important driver of the impact of globalization on worker welfare.
Nicholas Bloom, Stanford University and NBER; Kyle Handley, University of Michigan; André Kurmann, Drexel University; and Philip A. Luck, University of Colorado, Denver
The Impact of Chinese Trade on U.S. Employment: The Good, The Bad, and The Apocryphal
Using Census micro data Bloom, Handley, Kurmann, and Luck find that the impact of Chinese import competition on U.S. manufacturing had a striking regional variation. In high-human capital areas (for example, much of the West Coast or New England) most manufacturing job losses came from establishments industry switching to services. The establishment remained open but changed to research, design, management or wholesale. In the low human-capital areas (for example, much of the South and mid-West) manufacturing job-losses came from plant closure without much offsetting gain in service employment. Offshoring appears to drive these manufacturing job losses -- the Chinese trade impact arose primarily in large importing firms that were simultaneously expanding service sector employment. Hence, the researchers' data suggest Chinese trade redistributed jobs from manufacturing in lower income areas to services in higher income areas. Finally, the impact of Chinese imports appear to have disappeared after 2007. The researchers find strong employment impacts from 2000 to 2007, but nothing from 2008 to 2015.