Annual Review of Economics - Volume 9, 2017

We are very sad to report that Professor Sir Tony Atkinson died on the first of January, 2017, at the age of 72. Tony Atkinson was an extraordinarily distinguished academic whose works changed our understanding of poverty, inequality, mobility, public policy, and economic growth. His publications, from his first book in 1969 to his last in 2015, showed how he approached his work throughout his career: define the issues, examine the facts, analyze what forces shaped the outcomes, and ask what we can or should do in the way of policy. His longtime friend, Professor Lord Nicholas Stern, interviewed Sir Tony about his life and work on August 17, 2016, in Oxford.

The observed uneven distribution of economic activity across space is influenced by variation in exogenous geographical characteristics and endogenous interactions between agents in goods and factor markets. Until the past decade, the theoretical literature on economic geography had focused on stylized settings that could not easily be taken to the data. This article reviews more recent research that has developed quantitative models of economic geography. These models are rich enough to speak to first-order features of the data, such as many heterogeneous locations and gravity equation relationships for trade and commuting. At the same time, these models are sufficiently tractable to undertake realistic counterfactual exercises to study the effect of changes in amenities, productivity, and public policy interventions such as transport infrastructure investments. We provide an extensive taxonomy of the different building blocks of these quantitative spatial models and discuss their main properties and quantification.

We review recent research linking international trade to the environment, with a focus on new results and methods. The review is given structure by a novel decomposition linking changes in emissions to changes in productive activity at the plant, firm, industry, and national levels. Although some new results have emerged from the application of a Melitz-style approach to trade and the environment, the full potential of this approach has not yet been realized. We discuss existing empirical and theoretical work, introduce three new hypotheses, and suggest paths for future researchers to follow.

Innovations in information technology have increased the prevalence of markets with large numbers of products. Each week, for example, an average of over 800 books are published, and an average of over 1,100 iOS apps are released in Apple's App Store. This review summarizes existing research about how consumers learn about new products in such markets, focusing on mechanisms like bestseller lists and user-generated product reviews. In addition to reviewing research findings about how these mechanisms directly influence sales, this article also discusses how these mechanisms affect broader market outcomes, such as the shape of the success distribution and the likelihood that good products are discovered.

For the past 10 years, the topic of set identification has been much studied in the econometric literature. Classical inference methods have been generalized to the case in which moment inequalities and equalities define a set instead of a point. We review several instances of partial identification by focusing on examples in which the underlying economic restrictions are expressed as linear moments. This setting illustrates the fact that convex analysis helps not only for characterizing the identified set but also for inference. From this perspective, we review inference methods using convex analysis or inversion of tests and detail how geometric characterizations can be useful.

Many people care about how they are perceived by those around them. Several recent field experiments in economics have found that such social image concerns can have powerful effects on a range of behaviors. In this article, we first review this recent literature aimed at identifying social image concerns or social pressure. We then highlight and discuss two important areas that have been comparatively less well explored in this literature: understanding social pressure, including the underlying mechanisms, and whether such pressure can be shaped or influenced.

Since Quetelet's work in the nineteenth century, social science has iconified the average man, that hypothetical man without qualities who is comfortable with his head in the oven and his feet in a bucket of ice. Conventional statistical methods since Quetelet have sought to estimate the effects of policy treatments for this average man. However, such effects are often quite heterogeneous: Medical treatments may improve life expectancy but also impose serious short-term risks; reducing class sizes may improve the performance of good students but not help weaker ones, or vice versa. Quantile regression methods can help to explore these heterogeneous effects. Some recent developments in quantile regression methods are surveyed in this review.

Historically, the trade research field has usually ignored dynamic adjustment of workers, but a recent wave of work has developed a rich set of theoretical and empirical tools to analyze this factor. Empirical approaches have ranged from reduced-form regressions to the structural estimation of underlying parameters, which is necessary to understand welfare effects. A major distinction is that between models that do and those that do not allow for unobserved heterogeneity across workers; these models are useful for different purposes. Consistent findings across methods and countries indicate that costs of switching sectors and occupations are high and that both switching costs and option value are crucial in computing the welfare effects of globalization for workers.

This article reviews recent research regarding high-skilled migration. We adopt a data-driven perspective, bringing together and describing several ongoing research streams that range from the construction of global migration databases, to the legal codification of national policies regarding high-skilled migration, to the analysis of patent data regarding cross-border inventor movements. A common theme throughout this research is the importance of agglomeration economies for explaining high-skilled migration. We highlight some key recent findings and outline major gaps in the literature that we hope will be tackled in the near future.

This article provides a review of recent research on agricultural insurance (AI) in developing countries. Agricultural producers face a variety of significant risks; historically, only government-subsidized products have achieved widespread adoption. A recent contractual innovation, which links insurance payouts to realized weather rather than farmer indemnity, has spurred substantial research in the past decade. This review begins by describing the experience in developed economies and then turns to developing countries, covering the following topics: farmers' adoption of AI, how AI affects their decision to invest in risky assets, and the extent to which AI helps farmers smooth income and consumption. We conclude with suggestions for future research and practice related to AI in developing countries.

In this review, we examine the links between economic development and social conflict. By economic development, we refer broadly to aggregate changes in per capita income and wealth or in the distribution of that wealth. By social conflict, we refer to within-country unrest, ranging from peaceful demonstrations, processions, and strikes to violent riots and civil war. We organize our review by critically examining three common perceptions: that conflict declines with ongoing economic growth; that conflict is principally organized along economic differences rather than similarities; and that conflict, most especially in developing countries, is driven by ethnic motives.

Applied general equilibrium (AGE) models, which feature multiple countries, multiple industries, and input–output linkages across industries, have been the dominant tool for evaluating the impact of trade reforms since the 1980s. We review how these models are used to perform policy analysis and document their shortcomings in predicting the industry-level effects of past trade reforms. We argue that, to improve their performance, AGE models need to incorporate product-level data on bilateral trade relations by industry and better model how trade reforms lower bilateral trade costs. We use the least-traded-products methodology of Kehoe et al. (2015) to provide guidance on how improvements can be made. We provide further suggestions on how AGE models can incorporate recent advances in quantitative trade theory to improve their predictive ability and better quantify the gains from trade liberalization.

A large body of literature exists on the impact of family structure on children's outcomes, typically focusing on average effects. In this review, we build on this with an economic framework that has heterogeneous predictions regarding the potential benefit for children of married parents. We propose that the gains due to marriage from a child's perspective depend on a mother's own level of resources, the additional net resources that her partner brings, and the outcome-specific returns to resources. Data from the Panel Study of Income Dynamics are consistent with the heterogeneous predictions of this framework. In terms of high school completion or avoiding poverty at age 25, the so-called marriage premium for children is highest for children of mothers with high school degrees and mothers in their early to mid-20s. For the more advanced outcomes of college completion or high income at age 25, the marriage premium monotonically increases with observed maternal age and education.

Brands and brand capital have long been theorized to play an important role in the formation of the industrial market structure of consumer goods industries. We summarize several striking empirical regularities in the concentration, magnitude, and persistence of brand market shares in consumer goods categories. We then survey the theoretical and empirical literatures on the formation of brand preferences and the ways in which brand preferences contribute to our understanding of these empirical regularities. We also review the literature on how brand capital creates strategic advantages to firms that own established brands.

The degree to which retirement decisions are driven by health is a key concern for both academics and policy makers. In this review, we survey the economic literature on the health–retirement link in developed countries. We describe the mechanisms through which health affects labor supply and discuss how these mechanisms interact with public pensions and public health insurance. The historical evidence suggests that health is not the primary source of variation in retirement across countries and over time. Furthermore, the decline of health with age can only explain a small share of the decline in employment near retirement age. Health considerations nonetheless play an important role, especially in explaining cross-sectional variation in employment and other outcomes within countries. We review the mechanisms through which health affects retirement and discuss recent empirical analyses.

Due to rapid technological advances, researchers are now able to collect and analyze ever larger data sets. Statistical inference for big data often requires solving thousands or even millions of parallel inference problems simultaneously. This poses significant challenges and calls for new principles, theories, and methodologies. This review provides a selective survey of some recently developed methods and results for large-scale statistical inference, including detection, estimation, and multiple testing. We begin with the global testing problem, where the goal is to detect the existence of sparse signals in a data set, and then move to the problem of estimating the proportion of nonnull effects. Finally, we focus on multiple testing with false discovery rate (FDR) control. The FDR provides a powerful and practical approach to large-scale multiple testing and has been successfully used in a wide range of applications. We discuss several effective data-driven procedures and also present efficient strategies to handle various grouping, hierarchical, and dependency structures in the data.

Although patent systems have been widely used both historically and internationally, there is nonetheless a tremendous amount of controversy over whether patent systems, in practice, improve the alignment between private returns and social contributions. In this article, I describe three parameters—how the disclosure function affects research investments, how patent strength affects research investments in new technologies, and how patents on existing technologies affect follow-on innovation—needed to inform the question of how patents affect research investments, and review the available evidence that has attempted to empirically estimate these parameters.

Recent developments in nonlinear panel data analysis allow the identification and estimation of general dynamic systems. We review some results and techniques for nonparametric identification and flexible estimation in the presence of time-invariant and time-varying latent variables. This opens up the possibility of estimating nonlinear reduced forms in a large class of structural dynamic models with heterogeneous agents. We show how such reduced forms may be used to document policy-relevant derivative effects and to improve the understanding and implementation of structural models.

This review provides an overview of the operations and impacts of mobile money in the developing world. Over the past decade, mobile money has become a ubiquitous tool in some developing economies, allowing individuals to digitally transact money without formal bank accounts. The impacts, where documented, have been sizeable: For example, poverty decreased by two percentage points in Kenya. However, adoption still lags in many economies and, even where there is universal adoption, product innovation over the rails of these digital accounts has been slow. The review concludes by discussing what the future of mobile money in developing economies may look like and, thus, where the most exciting opportunities for research may be.

Exact consumer's surplus and deadweight loss are the most widely used welfare and economic efficiency measures. These measures can be computed from demand functions in straightforward ways. Nonparametric estimation can be used to estimate the welfare measures. In doing so, it seems important to account correctly for unobserved heterogeneity, given the high degree of unexplained demand variation often found in applications. This review surveys work on nonparametric welfare analysis, focusing on work that allows for general heterogeneity in demand, such as that of Hausman & Newey (2016).