Pre-Analysis Plans (PAPs) for randomized evaluations are becoming increasingly common in Economics, but their definition remains unclear and their practical applications therefore vary widely. Based on our collective experiences as researchers and editors, we articulate a set of principles for the ex-ante scope and ex-post use of PAPs. We argue that the key benefits of a PAP can usually be realized by completing the registration fields in the AEA RCT Registry. Specific cases where more detail may be warranted include when subgroup analysis is expected to be particularly important, or a party to the study has a vested interest. However, a strong norm for more detailed pre-specification can be detrimental to knowledge creation when implementing

field experiments in the real world. An ex-post requirement of strict adherence to pre-specified plans, or the discounting of non-pre-specified work, may mean that some experiments do not take place, or that interesting observations and new theories are not explored and reported. Rather, we recommend that the final research paper be written and judged as a distinct object from the “results of the PAP”; to emphasize this distinction, researchers could consider producing a short, publicly available report (the “populated PAP”) that populates the PAP to the extent possible and briefly discusses any barriers to doing so.

Low-income families in the United States tend to live in neighborhoods that offer limited opportunities for upward income mobility. One potential explanation for this pattern is that families prefer such neighborhoods for other reasons, such as affordability or proximity to family and jobs. An alternative explanation is that they do not move to high-opportunity areas because of barriers that prevent them from making such moves. We test between these two explanations using a randomized controlled trial with housing voucher recipients in Seattle and King County. We provided services to reduce barriers to moving to high-upward-mobility neighbor- hoods: customized search assistance, landlord engagement, and short-term financial assistance. Unlike many previous housing mobility programs, families using vouchers were not required to move to a high-opportunity neighborhood to receive a voucher. The intervention increased the fraction of families who moved to high-upward-mobility areas from 15% in the control group to 53% in the treatment group. Families induced to move to higher opportunity areas by the treatment do not make sacrifices on other aspects of neighborhood quality, tend to stay in their new neighborhoods when their leases come up for renewal, and report higher levels of neighborhood satisfaction after moving. These findings imply that most low-income families do not have a strong preference to stay in low-opportunity areas; instead, barriers in the housing search process are a central driver of residential segregation by income. Interviews with families reveal that the capacity to address each family’s needs in a specific manner – from emotional support to brokering with landlords to customized financial assistance – was critical to the pro- gram’s success. Using quasi-experimental analyses and comparisons to other studies, we show that more standardized policies – increasing voucher payment standards in high-opportunity areas or informational interventions – have much smaller impacts. We conclude that redesigning affordable housing policies to provide customized assistance in housing search could reduce residential segregation and increase upward mobility substantially.

This paper examines the evidence from randomized evaluations of sector-focused training programs that target low-wage workers and combine upfront screening, occupational and soft skills training, and wraparound services. The programs generate substantial and persistent earnings gains (12 to 34 percent) following training. Theoretical mechanisms for program impacts are explored for the WorkAdvance demonstration. Earnings gains are generated by getting participants into higher-wage jobs in higher-earning industries and occupations not just by raising employment. Training in transferable and certifiable skills (likely under-provided from poaching concerns) and reductions of employment barriers to high-wage sectors for non-traditional workers appear to play key roles.

How does one’s place of residence affect individual behavior and long-run outcomes? Understanding neighborhood and place effects has been a leading question for social scientists during the past half-century. Recent empirical studies using experimental and quasi-experimental research designs have generated new insights on the importance of residential neighborhoods in childhood and adulthood. This paper summarizes the recent neighborhood effects literature and interprets the findings. Childhood neighborhoods affect long-run economic and educational outcomes in a manner consistent with exposure models of neighborhood effects. For adults, neighborhood environments matter for their health and well-being but have more ambiguous impacts on labor market outcomes. We discuss the evidence on the mechanisms behind the observed patterns and conclude by highlighting directions for future research.

Although non-experimental studies find robust neighborhood effects on adults, such findings have been challenged by results from the Moving to Opportunity (MTO) residential mobility experiment. Using a within-study comparison design, this paper compares experimental and nonexperimental estimates from MTO and a parallel analysis of the Panel Study of Income Dynamics (PSID). Striking similarities were found between non-experimental estimates based on MTO and PSID. No clear evidence was found that different estimates are related to duration of adult exposure to disadvantaged neighborhoods, non-linear effects of neighborhood conditions, magnitude of the change in neighborhood context, frequency of moves, treatment effect heterogeneity, or measurement, although uncertainty bands around our estimates were sometimes large. One other possibility is that MTO-induced moves might have been unusually disruptive, but results are inconsistent for that hypothesis. Taken together, the findings suggest that selection bias might account for evidence of neighborhood effects on adult economic outcomes in nonexperimental studies.

The race between education and technology provides a canonical framework that does an excellent job of explaining US wage structure changes across the twentieth century. The framework involves secular increases in the demand for more-educated workers from skill-biased technological change, combined with variations in the supply of skills from changes in educational access. We expand the analysis backwards and forwards. The framework helps explain rising skill differentials in the nineteenth and twenty-first centuries, but needs to be augmented to illuminate the recent convexification of education returns and implied slowdown in the growth of the relative demand for college workers. Increased educational wage differentials explain 75 percent of the rise of U.S. wage inequality from 1980 to 2000 as compared to 38 percent for 2000 to 2017.

The fall of labor's share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments typically rely on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms." If globalization or technological changes push sales towards the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms. Since these firms have high markups and a low labor share of value-added and sales, a reallocation of output toward superstar firms depresses the aggregate labor share. We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all firms; (iv) the between firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity; (vi) the aggregate markup will rise more than the typical firm's markup; and (vii) these patterns should be observed not only in U.S. firms, but also internationally. We find support for all of these predictions.

To monitor trends in alternative work arrangements, we conducted a version of the Contingent Worker Survey as part of the RAND American Life Panel in late 2015. The findings point to a rise in the incidence of alternative work arrangements in the U.S. economy from 1995 to 2015. The percentage of workers engaged in alternative work arrangements – defined as temporary help agency workers, on-call workers, contract workers, and independent contractors or freelancers – rose from 10.7 percent in February 2005 to possibly as high as 15.8 percent in late 2015. Workers who provide services through online intermediaries, such as Uber or Task Rabbit, accounted for 0.5 percent of all workers in 2015. About twice as many workers selling goods or services directly to customers reported finding customers through offline intermediaries than through online intermediaries.

American women are working more, through their sixties and even into their seventies. Their increased participation at older ages started in the late 1980s before the turnaround in older men’s labor force participation and the economic downturns of the 2000s. The higher labor force participation of older women consists disproportionately of those working at full-time jobs. Increased labor force participation of women in their older ages is part of the general increase in cohort labor force participation. Cohort effects, in turn, are mainly a function of educational advances and greater prior work experience. But labor force participation rates of the most recent cohorts in their forties are less than those for previous cohorts. It would appear that employment at older ages could stagnate or even decrease. But several other factors will be operating in an opposing direction leading us to conclude that women are likely to continue to work even longer.