International Trade and Investment
March 31 - April 1, 2017
Treb Allen, Dartmouth College and NBER, and Costas Arkolakis, Yale University and NBER
In this paper, Allen and Arkolakis develop a framework to characterize the impact of infrastructure investment on welfare. They suppose infrastructure investment affects the cost of shipping goods between directly connected locations and the total bilateral cost between any two locations is determined by traders optimally traveling across the complete transportation network. The researchers' approach comprises two distinct but complementary characterizations: First, they characterize how infrastructure investment between any two connected locations decreases the total trade costs between all pairs of locations. Second, they characterize how the cost reduction between any two locations affects welfare. The researchers apply these results to shipment level data between U.S. cities to calculate the welfare effects of improving each portion of the U.S. Interstate Highway System (IHS). They find very heterogeneous welfare effects of improvements to different sections of the IHS — reducing the travel time by 30 minutes on I-95 South from New York to Philadelphia would increase aggregate U.S. welfare by 0.02%, whereas reducing the travel time by 30 minutes from Seattle to Salt Lake City along I-84 East would only increase aggregate U.S. welfare by one-hundredth of that.
Giulia Brancaccio, Princeton University; Myrto Kalouptsidi, Harvard University and NBER; and Theodore Papageorgiou, McGill University
Brancaccio, Kalouptsidi, and Papageorgiou build a framework that models the behavior of both exporters and transportation agents (ships); its spatial equilibrium determines world trade costs and flows. The researchers' framework has two novel features: (i) trade costs are endogenous and determined jointly with trade flows and as a result they depend on the entire network of trade linkages across countries; (ii) search frictions between exporters and ships limit trade. The model features geography, search frictions, and forward-looking optimizing ships and exporters. The researchers collect a unique dataset of shipping contracts, global vessel movements from satellites and sea weather conditions. The data reveal large trade imbalances and asymmetric trade costs. The researchers provide an empirical strategy to flexibly obtain the matching process between ships and exporters in a setup where searching exporters are unobserved and the researcher takes no stance on the presence of search frictions. Their estimated framework is then used to address a number of questions: What are the world trade elasticities with respect to transport costs? How do shocks propagate through the network of countries? The researchers consider the impact of a slow-down in China as well as the opening of the Northwest Passage. Finally, they quantify the trade lost due to search frictions.
Raymond Owens and Pierre-Daniel Sarte, Federal Reserve Bank of Richmond, and Esteban Rossi-Hansberg, Princeton University and NBER
Owens, Rossi-Hansberg, and Sarte study the urban structure of the City of Detroit. Following several decades of decline, the city's current urban structure is clearly not optimal for its size, with a business district immediately surrounded by a ring of largely vacant neighborhoods. The researchers propose a model with residential externalities that features multiple equilibria at the neighborhood level. In particular, developing a residential area requires the coordination of developers and residents, without which it may remain vacant even if its fundamentals are sound. The researchers embed this mechanism in a quantitative spatial economics model and use it to rationalize current city allocations. They then use the model to evaluate existing strategic visions to revitalize Detroit, and to design alternative plans that rely on "development guarantees" to yield better outcomes. The widespread effects of these policies underscore the importance of using a general equilibrium framework to evaluate policy proposals.
Dávid Krisztián Nagy, CREI
Nagy presents a dynamic model of the U.S. economy with trade, labor mobility, endogenous growth and realistic geography to examine the relationship between spatial frictions, city formation and aggregate development. In the model, a subset of locations endogenously specialize in innovative industries that are subject to economies of scale. This leads to the formation and development of cities. Spatial frictions affect innovation, thus aggregate growth, by shaping the locations and sizes of cities. Nagy takes the model to historical U.S. data at a 20 by 20 arc minute spatial resolution. He shows that the model can quantitatively replicate the large population reallocation toward the West and the rapid urbanization in the 19th century, as well as various moments of the location and growth of newly forming cities. Nagy uses the model to quantify how the construction of the U.S. railroad network affected city formation, aggregate output, and growth. Results indicate that railroads were responsible for 27% of U.S. growth before the Civil War, increasing U.S. real GDP by 9.3% in 1860. Nagy also shows that the formation and development of cities amplified the effects of railroads on real GDP by at least 18%.
Claudia Steinwender, Harvard University, and Cheng Chen, University of Hong Kong
Empirical evidence on the relationship between import competition and firm productivity is mixed. Chen and Steinwender re-investigate this question focusing on heterogeneous effects. Using rich Spanish firm-level data, they show that the response to import competition is mainly driven by family managed rather than professionally managed firms, and has a distinct, robust pattern: Family managers in firms with low initial productivity increase productivity whereas family managers in firms with high initial productivity decrease productivity. Productivity changes are driven by new organizational methods in process innovation, and by family management rather than family ownership. A model with heterogeneous preferences of managers over firm profits relative to private benefits and effort cost can rationalize the empirical evidence.
Andreas Moxnes, Karen Helene Ulltveit-Moe, and Federica Coelli, University of Oslo
Coelli, Moxnes, and Ulltveit-Moe estimate the effect of trade policy during the Great Liberalization of the 1990s on innovation in nearly 100 countries using international firm-level patent data. The empirical strategy exploits ex-ante differences in firms exposure to countries and industries, allowing the researchers to construct firm-specific measures of tariff cuts. This provides a novel source of variation that enables them to establish the causal impact of trade policy on innovation. The results suggest that trade liberalization has economically significant effects on innovation and, ultimately, technical change and growth. According to the researchers' estimates, a substantial share of global knowledge creation during the 1990s can be explained by trade policy reforms. Furthermore, they find that the increase in patenting reflects innovation, rather than simply more protection of existing knowledge. Both improved market access and more import competition contribute to the positive innovation response to trade liberalization.
George Alessandria, University of Rochester and NBER; Horag Choi, Monash University; and Dan Lu, University of Rochester
Alessandria, Choi, and Lu study the large rise in Chinese gross and net trade flows, summarized by its large positive net foreign asset position, in a dynamic stochastic general equilibrium model of China and the Rest of the World with endogenous trade participation, pricing-to-market, aggregate fluctuations, and incomplete financial markets. The model features an endogenous time-varying trade elasticity from producer-level investments in export market access. The researchers estimate the changes in technology, trade costs, and preferences accounting for the changes in China's gross and net trade flows, export participation, real GDP, and real exchange rate. They find that changes in trade barriers to be an important driver of the Chinese trade balance and the accumulation of foreign assets. They also find that the stagnation in trade growth since 2011 primarily reflects the completed transition to past trade reforms rather than to the increase in trade barriers or the reversal in the expected pace of future integration.
Kalina Manova, University of Oxford; Nicholas Bloom, Stanford University and NBER; John Van Reenen, MIT and NBER; Stephen Teng Sun, Peking University; and Zhihong Yu, Nottingham University
Bloom, Manova, Sun, Van Reenen, and Yu present a heterogeneous-firm model in which management ability increases both production efficiency and product quality. In particular, better managed firms use more sophisticated inputs and assembly technologies to more efficiently produce goods of higher quality. Combining six micro-datasets on management practices, production and trade in Chinese and American firms, the researchers find support for the model's predictions across both countries. First, better managed firms are more likely to export, sell more products to more destination countries, and earn higher export revenues and profits. Second, better managed exporters have higher prices, higher quality, and lower quality-adjusted prices. They also source more imported inputs, a wider range of inputs, more expensive inputs, and more inputs from advanced economies. The structural estimates from the researchers' model suggest that management is important for improving production efficiency and product quality in both countries, but it matters more in China than in the U.S., especially for product quality. Poor management practices may thus hinder trade, growth and entrepreneurship in developing countries.