One cannot exaggerate the importance of estimating how international trade responds to changes in income and prices. But there is a tension between whether one should use models that fit the data but that contradict certain aspects of the underlying theory or models that fit the theory but contradict certain aspects of the data. The essays in Estimating Trade Elasticities book offer one practical approach to deal with this tension. The analysis starts with the practical implications of optimising behaviour for estimation and it follows with a re-examination of the puzzling income elasticity for US imports that three decades of studies have not resolved. The analysis then turns to the study of the role of income and prices in determining the expansion in Asian trade, a study largely neglected in fifty years of research. With the new estimates of trade elasticities, the book examines how they assist in restoring the consistency between elasticity estimates and the world trade identity.

This paper focuses on the sluggish growth of world trade relative to income growth in recent years. The analysis uses an empirical strategy based on an error correction model to assess whether the global trade slowdown is structural or cyclical. An estimate of the relationship between trade and income in the past four decades reveals that the long-term trade elasticity rose sharply in the 1990s, but declined significantly in the 2000s even before the global financial crisis. These results suggest that trade is growing slowly not only because of slow growth of Gross Domestic Product (GDP), but also because of a structural change in the trade-GDP relationship in recent years. The available evidence suggests that the explanation may lie in the slowing pace of international vertical specialization rather than increasing protection or the changing composition of trade and GDP.

"This book is a brilliant exploration of the implications of recent theories of international trade for one of the most important questions in the field: how large are the gains from trade? Feenstra takes the models apart to shed light on the basic mechanisms at play and then masterfully uses the data to understand their quantitative significance."--AndrTs Rodriquez-Clare, Professor of Economics, Pennsylvania State University -- Book Jacket.

In this collection of 17 articles, top scholars synthesize and analyze scholarship on this widely used tool of policy analysis, setting forth its accomplishments, difficulties, and means of implementation. Though CGE modeling does not play a prominent role in top US graduate schools, it is employed universally in the development of economic policy. This collection is particularly important because it presents a history of modeling applications and examines competing points of view. - Presents coherent summaries of CGE theories that inform major model types - Covers the construction of CGE databases, model solving, and computer-assisted interpretation of results - Shows how CGE modeling has made a contribution to economic policy

The Melitz model highlights the importance of the extensive margin (the number of firms exporting) for trade flows. Using the World Bank’s Exporter Dynamics Database (EDD) featuring firm-level exports from 50 countries, we find that around 50 percent of variation in exports is along the extensive margin—a quantitative victory for the Melitz framework. The remaining 50 percent on the intensive margin (exports per exporting firm) contradicts a special case of Melitz with Pareto-distributed firm productivity, which has become a tractable benchmark. This benchmark model predicts that, conditional on the fixed costs of exporting, all variation in exports across trading partners should occur on the extensive margin. We find that moving from a Pareto to a lognormal distribution allows the Melitz model to match the role of the intensive margin in the EDD. We use likelihood methods and the EDD to estimate a generalized Melitz model with a joint lognormal distribution for firm-level productivity, fixed costs and demand shifters, and use “exact hat algebra” to quantify the effects of a decline in trade costs on trade flows and welfare in the estimated model. The welfare effects turn out to be quite close to those in the standard Melitz-Pareto model when we choose the Pareto shape parameter to fit the average trade elasticity implied by our estimated Melitz-lognormal model, although there are significant differences regarding the effects on trade flows.

In most macroeconomic models, the substitutability between domestic and foreign goods is calibrated using aggregated data. This imposes homogeneous elasticities across goods, and the calibration is only valid under this assumption. If elasticities are heterogeneous, the aggregate substitutability is a weighted average of good-specific elasticities, which in general cannot be inferred from aggregated data. We identify structurally the substitutability in US goods using multilateral trade data. We impose homogeneity, and find an aggregate elasticity similar in value to conventional macroeconomic estimates. It is more than twice larger with sectoral heterogeneity. We discuss the implications in various areas of international economics.

Trade flows and trade policies need to be properly quantified to describe, compare, or follow the evolution of policies between sectors or countries or over time. This is essential to ensure that policy choices are made with an appropriate knowledge of the real conditions. This practical guide introduces the main techniques of trade and trade policy data analysis. It shows how to develop the main indexes used to analyze trade flows, tariff structures, and non-tariff measures. It presents the databases needed to construct these indexes as well as the challenges faced in collecting and processing these data, such as measurement errors or aggregation bias. Written by experts with practical experience in the field, A Practical Guide to Trade Policy Analysis has been developed to contribute to enhance developing countries' capacity to analyze and implement trade policy. It offers a hands-on introduction on how to estimate the distributional effects of trade policies on welfare, in particular on inequality and poverty. The guide is aimed at government experts engaged in trade negotiations, as well as students and researchers involved in trade-related study or research. An accompanying DVD contains data sets and program command files required for the exercises. Copublished by the WTO and the United Nations Conference on Trade and Development

An integrated approach to the empirical application of dynamic optimization programming models, for students and researchers. This book is an effective, concise text for students and researchers that combines the tools of dynamic programming with numerical techniques and simulation-based econometric methods. Doing so, it bridges the traditional gap between theoretical and empirical research and offers an integrated framework for studying applied problems in macroeconomics and microeconomics. In part I the authors first review the formal theory of dynamic optimization; they then present the numerical tools and econometric techniques necessary to evaluate the theoretical models. In language accessible to a reader with a limited background in econometrics, they explain most of the methods used in applied dynamic research today, from the estimation of probability in a coin flip to a complicated nonlinear stochastic structural model. These econometric techniques provide the final link between the dynamic programming problem and data. Part II is devoted to the application of dynamic programming to specific areas of applied economics, including the study of business cycles, consumption, and investment behavior. In each instance the authors present the specific optimization problem as a dynamic programming problem, characterize the optimal policy functions, estimate the parameters, and use models for policy evaluation. The original contribution of Dynamic Economics: Quantitative Methods and Applications lies in the integrated approach to the empirical application of dynamic optimization programming models. This integration shows that empirical applications actually complement the underlying theory of optimization, while dynamic programming problems provide needed structure for estimation and policy evaluation.