Considerable progress has been made in understanding the relationship between international trade and the environment since Gene Grossman and Alan Krueger published their now seminal working paper examining the potential environmental effects of the North American Free Trade Agreement in 1991. Their work articulated a simple framework through which international trade and economic growth could affect the environment by impacting: the scale of economic activity (the scale effect), the composition of production across industries (the composition effect), or the emission intensity of individual industries (the technique effect). GK provided preliminary evidence of the relative magnitudes of the scale, composition and technique effects, and reached a striking conclusion: international trade would not necessarily harm the environment.
Much of the subsequent literature examining the effects of international trade and the environment has adopted Grossman and Krueger’s simple framework and builds directly from their initial foray into the area. We now have better empirical evidence of the relationship between economic growth and environmental quality, of how environmental regulations affect international trade and investment flows, and of the relative magnitudes of the scale, composition and technique effects.
Yet, the need for further progress remains along three key fronts. First, despite significant advances in our understanding of how economic growth affects environmental quality, evidence of the interaction between international trade, economic growth, and environmental outcomes remains scarce. Second, while a growing body of evidence suggests that environmental regulations significantly alter trade flows, it is still unclear if these policies have a larger or smaller effect than traditional determinants of comparative advantage. Third, although it is clear the technique effect is the primary driver of changes in pollution, evidence as to how trade has contributed to the technique effect is limited. Addressing these Three Remaining Challenges is necessary for assessing whether Grossman and Krueger’s conclusion that international trade need not necessarily harm the environment still holds today.
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Jevan Cherniwchan and M. Scott Taylor
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Johannes Brumm, Christopher Krause, Andreas Schaab, and Simon Scheidegger
Solving dynamic economic models that capture salient real-world heterogeneity and nonlinearity requires the approximation of high-dimensional functions. As their dimensionality increases, compute time and storage requirements grow exponentially. Sparse grids alleviate this curse of dimensionality by substantially reducing the number of interpolation nodes, that is, grid points needed to achieve a desired level of accuracy. The construction principle of sparse grids is to extend univariate interpolation formulae to the multivariate case by choosing linear combinations of tensor products in a way that reduces the number of grid points by orders of magnitude relative to a full tensor-product grid and doing so without substantially increasing interpolation errors. The most popular versions of sparse grids used in economics are (dimension-adaptive) Smolyak sparse grids that use global polynomial basis functions, and (spatially adaptive) sparse grids with local basis functions. The former can economize on the number of interpolation nodes for sufficiently smooth functions, while the latter can also handle non-smooth functions with locally distinct behavior such as kinks. In economics, sparse grids are particularly useful for interpolating the policy and value functions of dynamic models with state spaces between two and several dozen dimensions, depending on the application. In discrete-time models, sparse grid interpolation can be embedded in standard time iteration or value function iteration algorithms. In continuous-time models, sparse grids can be embedded in finite-difference methods for solving partial differential equations like Hamilton-Jacobi-Bellman equations. In both cases, local adaptivity, as well as spatial adaptivity, can add a second layer of sparsity to the fundamental sparse-grid construction. Beyond these salient use-cases in economics, sparse grids can also accelerate other computational tasks that arise in high-dimensional settings, including regression, classification, density estimation, quadrature, and uncertainty quantification.
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John McLaren
When international trade increases, either because of a country’s lowering its trade barriers, a trade agreement, or productivity surges in a trade partner, the surge of imports can cause dislocation and lowered incomes for workers in the import-competing industry or the surrounding local economy. Trade economists long used static approaches to analyze these effects on workers, assuming either that workers can adjust instantly and costlessly, or (less often) that they cannot adjust at all. In practice, however, workers incur costs to adjust, and the adjustment takes time. An explosion of research, mostly since about 2008, has explored dynamic worker adjustment through change of industry, change of occupation, change of location, change of labor-force participation, adjustment to change in income, and change in marital status or family structure.
Some of these studies estimate rich structural models of worker behavior, allowing for such factors as sector-specific or occupation-specific human capital to accrue over time, which can be imperfectly transferable across industries or occupations. Some allow for unobserved heterogeneity across workers, which creates substantial technical challenges. Some allow for life-cycle effects, where adjustment costs vary with age, and others allow adjustment costs to vary by gender. Others simplify the worker’s problem to embed it in a rich general equilibrium framework.
Some key results include: (a) Switching either industry or occupation tends to be very costly; usually more than a year’s average wages on average. (b) Given that moving costs change over time and workers are able to time their moves, realized costs are much lower, but the result is gradual adjustment, with a move to a new steady state that typically takes several years. (c) Idiosyncratic shocks to moving costs are quantitatively important, so that otherwise-identical workers often are seen moving in opposite directions at the same time. These shocks create a large role for option value, so that even if real wages in an industry are permanently lowered by a trade shock, a worker initially in that industry can benefit. This softens or reverses estimates of worker losses from, for example, the China shock. (d) Switching costs vary greatly by occupation, and can be very different for blue-collar and white-collar workers, for young and old workers, and for men and women. (e) Simple theories suggest that a shock results in wage overshooting, where the gap in wages between highly affected industries and others opens up and then shrinks over time, but evidence from Brazil shows that at least in some cases the wage differentials widen over time. (f) Some workers adjust through family changes. Evidence from Denmark shows that some women workers hit by import shocks withdraw from the labor market at least temporarily to marry and have children, unlike men.
Promising directions at the frontier include more work on longitudinal data; the role of capital adjustment; savings, risk aversion and the adjustment of trade deficits; responses in educational attainment; and much more exploration of the effects on family.
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David Kohn, Fernando Leibovici, and Michal Szkup
This article reviews recent studies on the impact of financial frictions on international trade. We first present evidence on the relation between measures of access to external finance and export decisions. We then present an analytical framework to analyze the impact of financial frictions on firms’ export decisions. Finally, we review recent applications of this framework to investigate the impact of financial frictions on international trade dynamics across firms, across industries, and in the aggregate. We discuss related empirical, theoretical, and quantitative studies throughout.
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Alessandra Bonfiglioli, Rosario Crinò, and Gino Gancia
International trade is dominated by a small number of very large firms. Models of trade with heterogeneous firms have been developed to study the causes and consequences of this observation. The canonical model of trade with heterogeneous firms shows that trade leads to between-firm reallocations and selection: It shifts employment toward firms with the best attributes and forces marginal firms to exit. The model also illustrates the role of heterogeneity, and its various sources, in explaining the volume of trade and the firm-level margins of adjustment. Consistent with the model, the empirical literature has documented that exporting is a rare activity, that exporting firms are larger and more productive than other firms, and that trade liberalization reallocates market shares toward the best-performing firms in various countries. Studies using transaction-level data have unveiled additional salient features of trade flows. First, sales by foreign firms are very heterogeneous and highly concentrated. Second, both the extensive margin (number of exporting firms) and the intensive margin (average export per firm) are important in explaining the level of exports and its changes over time. More heterogeneity in sales across firms is associated with a higher volume of trade along both margins. Third, increased foreign competition reallocates market shares toward top firms and hence can increase concentration from any country of origin. Numerous extensions of the benchmark model have been proposed to study other important aspects, such as the relevance of multi-product and multinational firms, the import behavior of firms, and the extent to which heterogeneity is endogenous to firms’ choices, but some open challenges still remain.
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Wolfgang Keller
This article explores knowledge spillovers, positive externalities that augment the information set of an economic agent, and reviews the evidence on such spillovers in the context of international economic transactions. The entry discusses trade channels of knowledge transfer associated with purchases from abroad (imports) and sales to abroad (exports). Another focus is on the foreign direct investment (FDI) channel through purchases from abroad (inward FDI) and sales to abroad (outward FDI). The entry also distinguishes knowledge flows from foreign to domestic agents and from domestic to foreign agents. The entry underlines the importance of empirical methodology and data characteristics that determine the quality of econometric identification. Even though spillovers are by their very nature—as externalities—difficult to identify, over recent decades a number of advances have produced robust evidence that both trade and foreign direct investment lead to sizable knowledge spillovers. These advances have been both conceptual as well as in the areas of empirical methodology and new data.
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Peter M. Morrow
Models of comparative advantage in international trade explain specialization using differences in autarky relative prices. This literature has traditionally focused on the Heckscher–Ohlin and Ricardian models. The former emphasizes differences in factor abundance across countries and in factor intensity across goods; the latter focuses on relative productivity differences across countries and goods. However, unrealistic assumptions and stark assumptions have hindered empirical assessment of these models. Contemporary models now allow researchers to overcome these hurdles. New models of Ricardian comparative advantage incorporate realistic geography and multiple countries. Similar advances have freed the Heckscher–Ohlin model from some of its theoretical straightjackets. In addition, researchers have started to provide microfoundations for the Ricardian model and to formalize how institutions and factor market distortions might generate patterns of comparative advantage. Trade economists have also started to think about magnitudes in a different way; that is, through general equilibrium counterfactual experiments.
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Devashish Mitra
While the role of lobbying in trade policy determination has been studied in a formal way since the early 1980s, it was the pathbreaking 1994 work by Grossman and Helpman in the following decade that led many scholars, using that framework (often with some modifications), to study many interesting political economy issues in the trade policy arena. Importantly, Grossman and Helpman were also the first to provide microfoundations to lobbying within a multisectoral, specific-factors framework. Moreover, the industry-level protection they derive is an empirically estimable function of measurable industry characteristics and other political and economic factors. With everything else held constant, organized sectors are able to obtain higher protection than unorganized sectors, with organized-sector protection inversely related to import penetration and import demand elasticity. Grossman and Helpman’s work gave an impetus to theory-driven empirical work in the political economy of trade policy, including the empirical investigation of the Grossman–Helpman model itself and its many extensions. There is now also a fairly large literature trying to explain the unrealistically high empirical estimates of the model’s parameters (representing the proportion of population politically organized and the weight the government attaches to aggregate welfare relative to political contributions). Extensions for empirical investigation that include bringing in competition between upstream and downstream lobbies, imperfect capturing of nontariff barrier (NTB) rents by the government, foreign lobbies, the possibility of misclassfication of sectors into organized and unorganized, and so forth partially correct the unrealistic parameter estimates. In addition, there are extensions that have been applied toward explaining policy changes and puzzles. Those extensions deal with lobby formation, trade agreements, unilateralism versus reciprocity in trade policy, lobbying for protection in declining industries, firm-level lobbying, the choice of policy instruments, and so forth. Despite so much work already done on lobbying and trade policy, the existing literature is deficient in the study of the choice of instruments, the antitrade bias in trade policy, and informational lobbying.
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International transactions are riskier than domestic transactions for several reasons, including, but not limited to, geographical distance, longer shipping times, greater informational frictions, contract enforcement, and dispute resolution problems. Such risks stem, fundamentally, from a timing mismatch between payment and delivery in business transactions. Trade finance plays a critical role in bridging the gap, thereby overcoming greater risks inherent in international trade. It is thus even described as the lifeline of international trade, because more than 90% of international transactions involve some form of credit, insurance, or guarantee. Despite its importance in international trade, however, it was not until the great trade collapse in 2008–2009 that trade finance came to the attention of academic researchers.
An emerging literature on trade finance has contributed to providing answers to questions such as: Who is responsible for financing transactions, and, hence, who would need liquidity support most to sustain international trade? This is particularly relevant in developing countries, where the lack of trade finance is often identified as the main hindrance to trade, and in times of financial crisis, when the overall drying up of trade finance could lead to a global collapse in trade.
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Xenia Matschke
The political economy of protection is a field within economics, but it has significant overlap with its sister discipline, political science. For a political economy of protection, one needs at a minimum two types of economic agents: political decision makers who provide protection, and economic agents who are protected or even actively seek protection. The typical political economy scenario leads to an economic outcome that is not Pareto-optimal: From a general welfare perspective, the political interaction is not desirable. An important task of political economy research is to explain why and how political interaction takes place. For the first part of the question, it appears clear that if protection is actively sought, the protection seeker intends to benefit from his activities. However, if the policymakers were truly interested in Pareto optimality and welfare maximization, they would refuse to protect. Hence a crucial assumption in the political economy literature is that the politicians’ objective function differs from the general welfare function. For the second part of the question, theoretical political economy models consider either the election campaign phase when politicians are eager to win a majority of votes (preelection models) or the phase when the politicians have been elected and may benefit from the spoils associated with holding office (postelection models). Whereas in the election phase, politicians have an incentive to cater to the interests of that part of the electorate that is considered pivotal for the election outcome, in the postelection phase they may be open to, for example, special interest group (SIG) influences from which they derive utility.
A first wave of theoretical political economy models originates from the 1980s. Building on these early advances, more elaborate models have been proposed. The most prominent one is the Grossman–Helpman protection for sale (PfS) model. It delivers a postelection general equilibrium framework of trade policy determination. In this common agency model, industry interest groups act as principals and offer the government a menu of contracts of campaign contributions in exchange for trade policy. The PfS model predicts that industries that lobby for protection will obtain trade protection in equilibrium, whereas nonlobbying industries will face import subsidies. Numerous papers have evaluated the PfS model empirically and found that the implied weight on contributions in the governmental welfare function and the implied share of the population represented by lobbies are both very high. Remedies for this surprising result exist, but it has also been argued that the found empirical regularities may be spurious.
At the beginning of the 21st century, the majority of political economy literature is still theoretical, but better data availability increasingly offers the opportunity to empirically test theoretical results. A number of challenges remain for the political economy literature, however. In particular, more work is required to better understand policymaker interests. Moreover, an incorporation of political economy aspects into the new trade theory models that allow for intra-industry trade and firm diversity appears to be a promising avenue for future research.
