Annual Review of Economics - Volume 10, 2018

This review surveys the literature on sorting in the labor market. There are inherent differences in worker ability and across-firm productivity. Two fundamental questions are whether the exact composition of skills of workers and productivity of firms affects output and how this composition determines the equilibrium allocation of workers within a firm and between firms. There has been a surge of research investigating the causes and consequences of the process of allocation of heterogeneous workers to firms. The focus in this review is on theory that sheds light on open questions in macroeconomics, labor, and industrial organization, with a particular emphasis on the role of firm size. Those models allow us to infer from the observed sorting patterns (who matches with whom) what the underlying technological determinants are and how they have evolved in recent decades. Furthermore, they help us understand the technological origins of important labor market trends, such as the increase in wage inequality and the change in labor market and firm dynamics.

We review recent developments in the econometrics of shape restrictions and their role in applied work. Our objectives are threefold. First, we aim to emphasize the diversity of applications in which shape restrictions have played a fruitful role. Second, we intend to provide practitioners with an intuitive understanding of how shape restrictions impact the distribution of estimators and test statistics. Third, we aim to provide an overview of new advances in the theory of estimation and inference under shape restrictions. Throughout the review, we outline open questions and interesting directions for future research.

Trade occurs between firms both across borders and within countries, and most trade transactions include at least one large firm with many trading partners. This article reviews the literature on firm-to-firm connections in trade. A growing body of evidence coming from domestic and international transaction data has established empirical regularities that have inspired the development of new theories emphasizing firm heterogeneity among both buyers and suppliers in production networks. Theoretical work has considered both static and dynamic matching environments in a framework of many-to-many matching. The literature on trade and production networks is at an early stage, and there are many unanswered empirical and theoretical questions.

Violence within families and child neglect are strikingly common: 700,000 children are found to be victims of abuse or neglect in the United States each year; over the course of childhood, 6% of children are placed in foster care, and 18% witness intimate partner violence. These children are at much higher risks of homelessness, criminal justice involvement, unemployment, and chronic health conditions compared to their neighbors. This article reviews the state of the economics literature on the causes and consequences of child maltreatment and intimate partner violence and calls for greater research into interventions aimed at improving child well-being.

This article reviews recent advances in fixed effects estimation of panel data models for long panels, where the number of time periods is relatively large. We focus on semiparametric models with unobserved individual and time effects, where the distribution of the outcome variable, conditional on covariates and unobserved effects, is specified parametrically while the distribution of the unobserved effects is left unrestricted. In contrast to existing reviews on long panels, we discuss models with both individual and time effects, split-panel jackknife bias corrections, unbalanced panels, distribution and quantile effects, and other extensions. Understanding and correcting the incidental parameter bias caused by the estimation of many fixed effects are our main focuses, and the unifying theme is that the order of this bias is given by the simple formula p/n for all models discussed, with p being the number of estimated parameters and n the total sample size.

Classic arguments for decentralization, augmented by ideas about how participation empowers the poor, motivate the widely used approach in foreign aid called community-driven development (CDD). CDD devolves control over the selection, implementation, and financial management of public goods to communities. Until recently, policy enthusiasm has outstripped the evidence. I synthesize findings from randomized controlled trials and find that CDD effectively delivers public goods and modest economic returns at low cost in difficult environments. There is little evidence, however, that CDD transforms local decision making or empowers the poor in any enduring way. Part of this failure may be because some constraints believed to be important—like insufficient social capital—appear not to bind. Others, like exclusive local institutions, are a problem, although not one that CDD remedies. These results present a conundrum: How much participation is enough to safeguard the gains of such extreme decentralization while minimizing the opportunity costs imposed on poor people's time?

Many theories of labor market turnover generate a job ladder. Due to search frictions, workers earn rents from employment. All workers agree on which jobs are, in this sense, more desirable and slowly climb the job ladder through job-to-job quits. Occasionally, negative shocks throw them off the ladder and back into unemployment. We review a recent body of theory and empirical evidence on labor market turnover through the lens of the job ladder. We focus on the critical role that the job ladder plays in transmitting aggregate shocks, through the pace and direction of employment reallocation, to economic activity and wages and in shaping business cycles more generally. The main evidence concerns worker transitions, both through nonemployment and from job to job, between firms of different sizes, ages, productivity levels, and wage premiums, as well as the resulting earnings growth. Poaching by firms up the ladder is the main engine of reallocation, which shuts down in recessions.

We construct an integrated assessment model with multiple energy sources—two fossil fuels and green energy—and use it to evaluate ranges of plausible estimates for the climate sensitivity, as well as for the sensitivity of the economy to climate change. Rather than focusing explicitly on uncertainty, we look at extreme scenarios defined by the upper and lower limits given in available studies in the literature. We compare optimal policy with laissez faire, and we point out the possible policy errors that could arise. By far the largest policy error arises when the climate policy is overly passive; overly zealous climate policy (i.e., a high carbon tax applied when climate change and its negative impacts on the economy are very limited) does not hurt the economy much as there is considerable substitutability between fossil and nonfossil energy sources.

Recent decades have seen the emergence of global value chains (GVCs), in which production stages for individual goods are broken apart and scattered across countries. Stimulated by these developments, there has been rapid progress in data and methods for measuring GVC linkages. The macro approach to measuring GVCs connects national input–output tables across borders by using bilateral trade data to construct global input–output tables. These tables have been applied to measure trade in value added, the length of and location of producers in GVCs, and price linkages across countries. The micro approach uses firm-level data to document firms’ input sourcing decisions, how import and export participation are linked, and how multinational firms organize their production networks. In this review, I evaluate progress in these two approaches, highlighting points of contact between them and areas that demand further work. I argue that further convergence between these approaches can strengthen both, yielding a more complete empirical portrait of GVCs.

High-frequency trading (HFT) has grown substantially in recent years due to fast-paced technological developments and their rapid uptake, particularly in equity markets. This review investigates how HFT could evolve and, by developing a robust understanding of its effects, identifies potential risks and opportunities that HFT could present in terms of financial stability and other market outcomes such as volatility, liquidity, price efficiency, and price discovery. Despite commonly held negative perceptions, the available evidence indicates that HFT and algorithmic trading may have several beneficial effects on markets. However, these types of trading may cause instabilities in financial markets in specific circumstances. Carefully chosen regulatory measures are needed to address concerns in the shorter term. However, further work is needed to inform policies in the longer term, particularly in view of likely uncertainties and lack of data. This work will be vital in supporting evidence-based regulation in this controversial and rapidly evolving field.

Health insurance confers benefits to the previously uninsured, including improvements in health, reductions in out-of-pocket spending, and reduced medical debt. However, because the nominally uninsured pay only a small share of their medical expenses, health insurance also provides substantial transfers to nonrecipient parties who would otherwise bear the costs of providing uncompensated care to the uninsured. The prevalence of uncompensated care helps explain the limited take-up of heavily subsidized public health insurance and the evidence that many recipients value formal health insurance at substantially less than the cost to insurers of providing that coverage. The distributional implications of public subsidies for health insurance depend critically on the ultimate economic incidence of the transfers that they deliver to providers of uncompensated care.

Sub-Saharan Africa has experienced high urban population growth over the past half century, dramatically reshaping the economic and spatial profile of the region. Simultaneously, this process has challenged the conventional view that countries urbanize alongside structural transformation, as urbanization in Africa has occurred despite low productivity gains in agriculture and very limited industrialization. While there are large household income gaps between urban and rural areas that induce migration, most cities have very high agricultural employment, blurring the connection between structural transformation and urbanization. Urban income premiums apply equally to farm and nonfarm families. Looking across the urban hierarchy, we discuss how high urban primacy presents problems for economic growth in Africa, how secondary cities are faltering with a lack of industrialization, and how growth of employment in tradable services may signal a different path to structural transformation.

We review new theories of learning that posit specific, distinct roles for the learner or innovator and their intellectual environment. We consider applications to the dynamics of individual earnings over the life cycle, the diffusion of knowledge within an organization and firm dynamics, and the role of trade in the diffusion of ideas.

This article reviews the basic theoretical models that are appropriate for analyzing different types of welfare reforms, as well as the related empirical literature. We first present the canonical labor supply model of a classical welfare program and then extend this basic framework to include in-kind transfers, incomplete take-up, human capital, preference persistence, and borrowing and saving. The empirical literature on these models is presented. The negative income tax, earnings subsidies, US welfare reforms with features that differ from those in other countries, and childcare reforms are then surveyed in terms of both the theoretical models and the empirical literature surrounding each.

Over the past two decades, the literature on comparative development has moved from country-level to within-country analyses. The questions asked have expanded in scope as economists have used satellite images of light density at night and other big spatial data to proxy for development at the desired level. The focus has also shifted from uncovering correlations to identifying causal relations, using elaborate econometric techniques including spatial regression discontinuity designs. In this review, we show how the combination of geographic information systems with insights from disciplines ranging from the earth sciences to linguistics and history has transformed the research landscape on the roots of the spatial patterns of development. We discuss the limitations of the luminosity data and associated econometric techniques and conclude by offering some thoughts on future research.

This review explores the role of incentives in providing goods and services that have significant social returns not captured in private returns, and where outcomes and performances are not easy to measure. We discuss how the presence of prosocial motivation among agents involved in the provision of these goods and services changes the design of incentives. The review also emphasises how heterogeneous prosocial motivation puts a premium on selection of agents in this context. We also discuss alternative theories of prosocial motivation.

We review the evidence on social incentives, namely on how social interactions with colleagues, subordinates, bosses, customers, and others shape agents’ effort choices in organizations. We propose a two-way taxonomy based on (a) whether the social group is horizontal (peers at the same level of the hierarchy) or vertical (individuals at different levels within or outside of the organization) and (b) whether the agent's effort creates externalities for the other members of their social group. We show settings in which social incentives improve productivity and settings in which they reduce it. In most cases, the size of the effect is approximately 10%, which is half of the typical effect of performance pay. We also show that social incentives can interfere with financial incentives, making them ineffective or even detrimental. We conclude that social incentives are a powerful motivator that must be taken into account in the design of organizational policies and that more research is needed to understand how policies can shape the preferences that underpin these incentives.

Program evaluation methods are widely applied in economics to assess the effects of policy interventions and other treatments of interest. In this article, we describe the main methodological frameworks of the econometrics of program evaluation. In the process, we delineate some of the directions along which this literature is expanding, discuss recent developments, and highlight specific areas where new research may be particularly fruitful.

This review provides a guide to macroeconomic applications of the theory of rational bubbles. It shows that rational bubbles can be easily incorporated into standard macroeconomic models and illustrates how they can be used to account for important macroeconomic phenomena. It also discusses the welfare implications of rational bubbles and the role of policy in managing them. Finally, it provides a detailed review of the literature.

We provide a model of self-selection by candidates in a probabilistic voting environment to shed light on the forces shaping the quality of politicians from both the supply and demand sides of politics. The model highlights the idea that the patterns of selection and the comparative statics of politician quality depend critically on how the costs of running for office vary for candidates with different qualities. The model offers predictions on how the quality of the political class will vary with key parameters pertaining to both the supply and demand for candidates. We use the model to frame a review of the empirical literature on political selection that has emerged over the past two decades. We contrast areas where significant progress has been made with others where important theoretical predictions remain untested or existing evidence does not allow a consensus, highlighting areas for future research.