Rodrigo Adao

Why is Trade Not Free? A Revealed Preference Approach
Date Posted:Mon, 23 Oct 2023 10:41:57 -0500
A prominent explanation for why trade is not free is politicians? desire to protect some of their constituents at the expense of others. In this paper we develop a methodology that can be used to reveal the welfare weights that a nation?s import tariffs implicitly place on different groups of society. Applied in the context of the United States in 2017, this method implies that redistributive trade protection accounts for a significant fraction of US tariff variation and causes large monetary transfers between US individuals, mostly driven by differences in welfare weights across sectors of employment. Perhaps surprisingly, differences in welfare weights across US states play a much smaller role.

Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Why is Trade Not Free? A Revealed Preference Approach
Date Posted:Mon, 16 Oct 2023 14:26:04 -0500
A prominent explanation for why trade is not free is politicians? desire to protect some of their constituents at the expense of others. In this paper we develop a methodology that can be used to reveal the welfare weights that a nation?s import tariffs implicitly place on different groups of society. Applied in the context of the United States in 2017, this method implies that redistributive trade protection accounts for a significant fraction of US tariff variation and causes large monetary transfers between US individuals, mostly driven by differences in welfare weights across sectors of employment. Perhaps surprisingly, differences in welfare weights across US states play a much smaller role.

Putting Quantitative Models to the Test: An Application to Trump's Trade War
Date Posted:Mon, 12 Jun 2023 06:21:30 -0500
The primary motivation behind quantitative modeling in international trade and many other fields is to shed light on the economic consequences of policy changes. To help assess and potentially strengthen the credibility of such quantitative predictions we introduce an IV-based goodness-of-fit measure that provides the basis for testing causal predictions in arbitrary general-equilibrium environments as well as for estimating the average misspecification in these predictions. As an illustration of how to use our IV-based goodness-of-fit measure in practice, we revisit the welfare consequences of Trump's trade war predicted by Fajgelbaum, Goldberg, Kennedy and Khandelwal (2020).

Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Putting Quantitative Models to the Test: An Application to Trump's Trade War
Date Posted:Fri, 09 Jun 2023 08:47:32 -0500
The primary motivation behind quantitative modeling in international trade and many other fields is to shed light on the economic consequences of policy changes. To help assess and potentially strengthen the credibility of such quantitative predictions we introduce an IV-based goodness-of-fit measure that provides the basis for testing causal predictions in arbitrary general-equilibrium environments as well as for estimating the average misspecification in these predictions. As an illustration of how to use our IV-based goodness-of-fit measure in practice, we revisit the welfare consequences of Trump?s trade war predicted by Fajgelbaum et al. (2020).

Putting Quantitative Models to the Test: An Application to Trump?s Trade War
Date Posted:Wed, 31 May 2023 17:05:37 -0500
The primary motivation behind quantitative modeling in international trade and many other fields is to shed light on the economic consequences of policy changes. To help assess and potentially strengthen the credibility of such quantitative predictions we introduce an IV-based goodness-of-fit measure that provides the basis for testing causal predictions in arbitrary general-equilibrium environments as well as for estimating the average misspecification in these predictions. As an illustration of how to use our IV-based goodness-of-fit measure in practice, we revisit the welfare consequences of Trump?s trade war predicted by Fajgelbaum et al. (2020).

International Trade and Earnings Inequality: A New Factor Content Approach
Date Posted:Wed, 24 Mar 2021 03:50:49 -0500
We develop a new factor content approach to study the impact of trade on inequality. Our analysis generalizes the theoretical results of Deardorff and Staiger (1988) and improves on past empirical implementations of these results. Combined with unique administrative data from Ecuador, our approach yields measures of individual-level exposure to exports and imports, for both capital and labor income, as well as estimates of the incidence of such exposure across the income distribution. We find that international trade raises earnings inequality in Ecuador, especially in the upper-half of the income distribution. However, the drop in inequality experienced by Ecuador over the last decade would have been less pronounced in the absence of trade.

International Trade and Earnings Inequality: A New Factor Content Approach
Date Posted:Thu, 17 Dec 2020 22:14:42 -0600
We develop a new factor content approach to study the impact of trade on inequality. Our analysis generalizes the theoretical results of Deardorff and Staiger (1988) and improves on past empirical implementations of these results. Combined with unique administrative data from Ecuador, our approach yields measures of individual-level exposure to exports and imports, for both capital and labor income, as well as estimates of the incidence of such exposure across the income distribution. We find that international trade raises earnings inequality in Ecuador, especially in the upper-half of the income distribution. However, the drop in inequality experienced by Ecuador over the last decade would have been less pronounced in the absence of trade.

New: International Trade and Earnings Inequality: A New Factor Content Approach
Date Posted:Thu, 17 Dec 2020 12:17:12 -0600
We develop a new factor content approach to study the impact of trade on inequality. Our analysis generalizes the theoretical results of Deardorff and Staiger (1988) and improves on past empirical implementations of these results. Combined with unique administrative data from Ecuador, our approach yields measures of individual-level exposure to exports and imports, for both capital and labor income, as well as estimates of the incidence of such exposure across the income distribution. We find that international trade raises earnings inequality in Ecuador, especially in the upper-half of the income distribution. However, the drop in inequality experienced by Ecuador over the last decade would have been less pronounced in the absence of trade.

Aggregate Implications of Firm Heterogeneity: A Nonparametric Analysis of Monopolistic Competition Trade Models
Date Posted:Tue, 17 Nov 2020 20:33:46 -0600
We measure the role of firm heterogeneity in counterfactual predictions of monopolistic competition trade models without parametric restrictions on the distribution of firm fundamentals. We show that two bilateral elasticity functions are sufficient to nonparametrically compute the counterfactual aggregate impact of trade shocks, and recover changes in economic fundamentals from observed data. These functions are identified from two semiparametric gravity equations governing the impact of bilateral trade costs on the extensive and intensive margins of firm-level exports. Applying our methodology, we estimate elasticity functions that imply an impact of trade costs on trade flows that falls when more firms serve a market because of smaller extensive margin responses. Compared to a baseline where elasticities are constant, firm heterogeneity amplifies both the gains from trade in countries with more exporter firms, and the welfare gains of European market integration in 2003-2012.

New: Aggregate Implications of Firm Heterogeneity: A Nonparametric Analysis of Monopolistic Competition Trade Models
Date Posted:Tue, 17 Nov 2020 10:35:52 -0600
We measure the role of firm heterogeneity in counterfactual predictions of monopolistic competition trade models without parametric restrictions on the distribution of firm fundamentals. We show that two bilateral elasticity functions are sufficient to nonparametrically compute the counterfactual aggregate impact of trade shocks, and recover changes in economic fundamentals from observed data. These functions are identified from two semiparametric gravity equations governing the impact of bilateral trade costs on the extensive and intensive margins of firm-level exports. Applying our methodology, we estimate elasticity functions that imply an impact of trade costs on trade flows that falls when more firms serve a market because of smaller extensive margin responses. Compared to a baseline where elasticities are constant, firm heterogeneity amplifies both the gains from trade in countries with more exporter firms, and the welfare gains of European market integration in 2003-2012.

Aggregate Implications of Firm Heterogeneity: A Nonparametric Analysis of Monopolistic Competition Trade Models
Date Posted:Mon, 16 Nov 2020 05:49:37 -0600
We measure the role of firm heterogeneity in counterfactual predictions of monopolistic competition trade models without parametric restrictions on the distribution of firm fundamentals. We show that two bilateral elasticity functions are sufficient to nonparametrically compute the counterfactual aggregate impact of trade shocks, and recover changes in economic fundamentals from observed data. These functions are identified from two semiparametric gravity equations governing the impact of bilateral trade costs on the extensive and intensive margins of firm-level exports. Applying our methodology, we estimate elasticity functions that imply an impact of trade costs on trade flows that falls when more firms serve a market because of smaller extensive margin responses. Compared to a baseline where elasticities are constant, firm heterogeneity amplifies both the gains from trade in countries with more exporter firms and the welfare gains of European market integration in 2003-2012.

Technological Transitions with Skill Heterogeneity Across Generations
Date Posted:Mon, 06 Jan 2020 18:48:21 -0600
We study how inequality, skills, and economic activity adjust over time to technological innovations. We develop a theory of technological transitions where economies adjust through two margins: (i) within-generation reallocation of workers with heterogeneous skills, and (ii) cross-generation changes in the skill distribution driven by entering generations investing in skills. We then characterize the equilibrium dynamics, showing that they resemble those of a q-theory of skill investment where q is lifetime inequality. Technological transitions are slower and more unequal whenever innovations are biased towards economic activities intensive in skills which differ more from those used in the rest of the economy?i.e., technology-skill specificity is higher. This is because the first margin is weaker and the second stronger. Lastly, we document that recent cognitive-biased innovations caused responses in occupational composition and training which were strong for younger generations but weak for older ones. This evidence is consistent with high technology-skill specificity, implying that cognitive-biased transitions are particularly slow and unequal because they are mainly driven by changes in the skill distribution across generations.

Technological Transitions with Skill Heterogeneity across Generations
Date Posted:Fri, 03 Jan 2020 16:28:47 -0600
Why are some technological transitions particularly unequal and slow to play out? We develop a theory to study transitions after technological innovations driven by worker reallocation within a generation and changes in the skill distribution across generations. The economy?s transitional dynamics have a representation as a q-theory of skill investment. We exploit this in two ways. First, to show that technology-skill specificity and the cost of skill investment determine how unequal and slow transitions are by affecting the two adjustment margins in the theory. Second, to connect these determinants to measurable, short-horizon changes in labor market outcomes within and between generations. We then empirically analyze the adjustment to recent cognitive-biased innovations in developed economies. Strong responses of cognitive-intensive employment for young but not old generations suggest that cognitive-skill specificity is high and that the supply of cognitive skills is more elastic for younger generations. This evidence indicates that cognitive-biased transitions slowly unfold over many generations. As such, naively extrapolating from observed changes at short horizons leads to overly pessimistic views about their welfare and distributional implications.

New: Technological Transitions with Skill Heterogeneity Across Generations
Date Posted:Fri, 03 Jan 2020 06:28:55 -0600
Why are some technological transitions particularly unequal and slow to play out? We develop a theory to study transitions after technological innovations driven by worker reallocation within a generation and changes in the skill distribution across generations. The economy’s transitional dynamics have a representation as a q-theory of skill investment. We exploit this in two ways. First, to show that technology-skill specificity and the cost of skill investment determine how unequal and slow transitions are by affecting the two adjustment margins in the theory. Second, to connect these determinants to measurable, short-horizon changes in labor market outcomes within and between generations. We then empirically analyze the adjustment to recent cognitive-biased innovations in developed economies. Strong responses of cognitive-intensive employment for young but not old generations suggest that cognitive-skill specificity is high and that the supply of cognitive skills is more elastic ...

General Equilibrium Effects in Space: Theory and Measurement
Date Posted:Tue, 12 Feb 2019 16:03:19 -0600
How do international trade shocks affect spatially connected regional markets? We answer this question by extending shift-share empirical specifications to incorporate general equilibrium effects that arise in spatial models. In partial equilibrium, regional shock exposure has a shift-share structure: it is the average shock weighted by regional exposure shares in revenue and consumption. General equilibrium responses of employment and wages in each market are the sum, across all regions, of these shift-share measures times bilateral reduced-form elasticities determined by the economy's spatial links. We use this reduced-form representation of the model to efficiently estimate the bilateral elasticities exploiting exogenous variation in shock exposure across markets. Finally, we study the general equilibrium impact of the ?China shock? on U.S. CZs using our model-consistent generalization of the specification in Autor et al. (2013). We find that indirect effects from the shock exposure of other markets reinforce the negative impact of the market's own shock exposure, leading to employment and wage losses that are significantly larger than those reported in the existing literature.

Spatial Linkages, Global Shocks, and Local Labor Markets: Theory and Evidence
Date Posted:Tue, 12 Feb 2019 14:14:25 -0600
How do shocks to economic fundamentals in the world economy affect local labor markets? In a framework with a flexible structure of spatial linkages, we characterize the model-consistent shock exposure of a local market as the exogenous shift in its production revenues and consumption costs. In general equilibrium, labor outcomes in any market respond directly to the market's own shock exposure, and indirectly to other markets shocks exposures. We show how spatial linkages control the size and the heterogeneity of these indirect effects. We then develop a new estimation methodology ? the Model-implied Optimal IV (MOIV) ? that exploits quasi-experimental variation in economic shocks to estimate spatial linkages and evaluate their counterfactual implications. Applying our methodology to US Commuting Zones, we find that difference-in-difference designs based on model-consistent measures of local shock exposure approximate well the differential effect of international trade shocks across CZs, but miss around half of the aggregate effect, partly due to the offsetting action of indirect effects.

New: Spatial Linkages, Global Shocks, and Local Labor Markets: Theory and Evidence
Date Posted:Tue, 12 Feb 2019 04:15:25 -0600
How do shocks to economic fundamentals in the world economy affect local labor markets? In a framework with a flexible structure of spatial linkages, we characterize the model-consistent shock exposure of a local market as the exogenous shift in its production revenues and consumption costs. In general equilibrium, labor outcomes in any market respond directly to the market's own shock exposure, and indirectly to other markets shocks exposures. We show how spatial linkages control the size and the heterogeneity of these indirect effects. We then develop a new estimation methodology — the Model-implied Optimal IV (MOIV) — that exploits quasi-experimental variation in economic shocks to estimate spatial linkages and evaluate their counterfactual implications. Applying our methodology to US Commuting Zones, we find that difference-in-difference designs based on model-consistent measures of local shock exposure approximate well the differential effect of international trade shocks across ...

Spatial Linkages, Global Shocks, and Local Labor Markets: Theory and Evidence
Date Posted:Wed, 06 Feb 2019 19:59:43 -0600
How do shocks to economic fundamentals in the world economy a?ect local labor markets? In a framework with a flexible structure of spatial linkages, we characterize the model-consistent shock exposure of a local market as the exogenous shift in its production revenues and consumption costs. In general equilibrium, labor outcomes in any market respond directly to the market?s own shock exposure, and indirectly to other markets shocks exposures. We show how spatial linkages control the size and the heterogeneity of these indirect e?ects. We then develop a new estimation methodology - the Model-implied Optimal IV (MOIV) - that exploits quasi-experimental variation in economic shocks to estimate spatial linkages and evaluate their counterfactual implications. Applying our methodology to US Commuting Zones, we ?nd that di?erence-in-di?erence designs based on model-consistent measures of local shock exposure approximate well the di?erential e?ect of international trade shocks across CZs, but miss around half of the aggregate e?ect, partly due to the o?setting action of indirect e?ects.

New: Spatial Linkages, Global Shocks, and Local Labor Markets: Theory and Evidence
Date Posted:Wed, 06 Feb 2019 10:01:35 -0600
How do shocks to economic fundamentals in the world economy a?ect local labor markets? In a framework with a flexible structure of spatial linkages, we characterize the model-consistent shock exposure of a local market as the exogenous shift in its production revenues and consumption costs. In general equilibrium, labor outcomes in any market respond directly to the market’s own shock exposure, and indirectly to other markets shocks exposures. We show how spatial linkages control the size and the heterogeneity of these indirect e?ects. We then develop a new estimation methodology - the Model-implied Optimal IV (MOIV) - that exploits quasi-experimental variation in economic shocks to estimate spatial linkages and evaluate their counterfactual implications. Applying our methodology to US Commuting Zones, we ?nd that di?erence-in-di?erence designs based on model-consistent measures of local shock exposure approximate well the di?erential e?ect of international trade shocks across CZs, ...

Shift-Share Designs: Theory and Inference
Date Posted:Tue, 28 Aug 2018 22:33:29 -0500
We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of observed sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. Commuting Zones. Tests based on commonly used standard errors with 5% nominal significance level reject the null of no effect in up to 55% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independently of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show that our methods yield substantially wider confidence intervals in popular applications of shift-share regression designs.

Shift-Share Designs: Theory and Inference
Date Posted:Tue, 21 Aug 2018 22:45:06 -0500
We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of observed sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. Commuting Zones. Tests based on commonly used standard errors with 5% nominal significance level reject the null of no effect in up to 55% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independently of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show that our methods yield substantially wider confidence intervals in popular applications of shift-share regression designs.

New: Shift-Share Designs: Theory and Inference
Date Posted:Tue, 21 Aug 2018 13:45:06 -0500
We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of observed sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. Commuting Zones. Tests based on commonly used standard errors with 5% nominal significance level reject the null of no effect in up to 55% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independently of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show that our methods yield substantially wider confidence intervals in popular applications of shift-share regression ...

Shift-Share Designs: Theory and Inference
Date Posted:Tue, 21 Aug 2018 12:12:26 -0500
We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of observed sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. Commuting Zones. Tests based on commonly used standard errors with 5% nominal significance level reject the null of no effect in up to 55% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independently of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show that our methods yield substantially wider confidence intervals in popular applications of shift-share regression designs.