1.	Synthetic Difference In Differences Dmitry Arkhangelsky, Susan Athey, David A. Hirshberg, Guido W. Imbens, and Stefan Wager #25532 Abstract: We present a new perspective on the Synthetic Control (SC) method as a weighted least squares regression estimator with time fixed effects and unit weights. This perspective suggests a generalization with two way (both unit and time) fixed effects, and both unit and time weights, which can be interpreted as a unit and time weighted version of the standard Difference In Differences (DID) estimator. We find that this new Synthetic Difference In Differences (SDID) estimator has attractive properties compared to the SC and DID estimators. Formally we show that our approach has double robustness properties: the SDID estimator is consistent under a wide variety of weighting schemes given a well-specified fixed effects model, and SDID is consistent with appropriately penalized SC weights when the basic fixed effects model is misspecified and instead the true data generating process involves a more general low-rank structure (e.g., a latent factor model). We also present results that justify standard inference based on weighted DID regression. Further generalizations include unit and time weighted factor models.
2.	A Panel-based Proxy for Gun Prevalence in the US Daniel Cerqueira, Danilo Santa Cruz Coelho, John J. Donohue, Marcelo Fernandes, and Jony Arrais Pinto Jr. #25530 Abstract: There is a consensus that the proportion of suicides committed with a firearm is the best proxy for gun ownership prevalence. Cerqueira et al. (2108) exploit the socioeconomic characteristics of suicide victims in order to develop a new and more refined proxy. It is based on the fixed effects of the victim's place of residence estimated from a discrete choice model for the likelihood of committing suicide with gun. We empirically assess this new indicator using gun ownership data from the Behavioral Risk Factor Surveillance System (BRFSS) and suicide registers of the US National Center for Health Statistics (NCHS) from 1995 through 2004. We demonstrate that this new gun proxy provides significant gains in correlation with the percentage of households with firearms.
3.	Estimating the Economic Impacts of Climate Change Using Weather Observations Charles D. Kolstad and Frances C. Moore #25537 Abstract: This paper reviews methods that have been used to statistically measure the effect of climate on economic value, using historic data on weather, climate, economic activity and other variables. This has been an active area of research for several decades, with many recent developments and discussion of the best way of measuring climate damages. The paper begins with a conceptual framework covering issues relevant to estimating the costs of climate change impacts. It then considers several approaches to econometrically estimate impacts that have been proposed in the literature: cross-sections, linear and non-linear panel methods, long-differences, and partitioning variation. For each method we describe the kind of impacts (short-run vs long-run) estimated, the type of weather or climate variation used, and the pros and cons of the approach.
4.	Narratives about Technology-Induced Job Degradations Then and Now Robert J. Shiller #25536 Abstract: Concerns that technological progress degrades job opportunities have been expressed over much of the last two centuries by both professional economists and the general public. These concerns can be seen in narratives both in scholarly publications and in the news media. Part of the expressed concern about jobs has been about the potential for increased economic inequality. But another part of the concern has been about a perceived decline in job quality in terms of its effects on monotony vs creativity of work, individual sense of identity, power to act independently, and meaning of life. Public policy should take account of both of these concerns, inequality and job quality.
5.	Tax Policy and Local Labor Market Behavior Daniel G. Garrett, Eric C. Ohrn, and Juan Carlos Suárez Serrato #25546 Abstract: Since 2002, the US government has encouraged business investment using accelerated depreciation policies that significantly reduce investment costs. We provide the first in-depth analysis of this stimulus on employment and earnings. Our local labor markets approach exploits cross-industry differences in policy generosity interacted with county-level variation in industry concentration. Places that experience larger decreases in investment costs see a level increase in employment that implies a $53,000 cost-per-job. We find no positive effects on average earnings. In contrast, we document a persistent growth in capital. These results imply a capital-labor substitution elasticity that grows over time and can exceed unity.
6.	Ten Years after the Financial Crisis: What Have We Learned from the Renaissance in Fiscal Research? Valerie A. Ramey #25531 Abstract: This paper takes stock of what we have learned from the “Renaissance” in fiscal research in the ten years since the financial crisis. I first summarize the new innovations in methodology and discuss the various strengths and weaknesses of the main approaches. Reviewing the estimates, I come to the surprising conclusion that the bulk of the estimates for average spending and tax change multipliers lie in a fairly narrow range, 0.6 to 1 for spending multipliers and -2 to -3 for tax change multipliers. However, I identify economic circumstances in which multipliers lie outside those ranges. I conclude by reviewing the debate on whether multipliers were higher on the stimulus spending in the U.S. and the fiscal consolidations in Europe.
7.	Judging Judge Fixed Effects Brigham R. Frandsen, Lars J. Lefgren, and Emily C. Leslie #25528 Abstract: We propose a test for the identifying assumptions invoked in designs based on random assignment to one of many "judges.'' We show that standard identifying assumptions imply that the conditional expectation of the outcome given judge assignment is a continuous function with bounded slope of the judge propensity to treat. The implication leads to a two-part test that generalizes the Sargan-Hansen overidentification test and assesses whether implied treatment effects across the range of judge propensities are possible given the domain of the outcome. We show the asymptotic validity of the testing procedure, demonstrate its finite-sample performance in simulations, and apply the test in an empirical setting examining the effects of pre-trial release on defendant outcomes in Miami. When the assumptions are not satisfied, we propose a weaker average monotonicity assumption under which IV still converges to a proper weighted average of treatment effects.
8.	Universal Basic Income in the US and Advanced Countries Hilary W. Hoynes and Jesse Rothstein #25538 Abstract: We discuss the potential role of Universal Basic Incomes (UBIs) in advanced countries. A feature of advanced economies that distinguishes them from developing countries is the existence of well developed, if often incomplete, safety nets. We develop a framework for describing transfer programs, flexible enough to encompass most existing programs as well as UBIs, and use this framework to compare various UBIs to the existing constellation of programs in the United States. A UBI would direct much larger shares of transfers to childless, non-elderly, non-disabled households than existing programs, and much more to middle-income rather than poor households. A UBI large enough to increase transfers to low-income families would be enormously expensive. We review the labor supply literature for evidence on the likely impacts of a UBI. We argue that the ongoing UBI pilot studies will do little to resolve the major outstanding questions.
9.	We are all Behavioral, More or Less: Measuring and Using Consumer-level Behavioral Sufficient Statistics Victor Stango and Jonathan Zinman #25540 Abstract: Can a behavioral sufficient statistic empirically capture cross-consumer variation in behavioral tendencies and help identify whether behavioral biases, taken together, are linked to material consumer welfare losses? Our answer is yes. We construct simple consumer-level behavioral sufficient statistics—“B-counts”—by eliciting seventeen potential sources of behavioral biases per person, in a nationally representative panel, in two separate rounds nearly three years apart. B-counts aggregate information on behavioral biases within-person. Nearly all consumers exhibit multiple biases, in patterns assumed by behavioral sufficient statistic models (a la Chetty), and with substantial variation across people. B-counts are stable within-consumer over time, and that stability helps to address measurement error when using B-counts to model the relationship between biases, decision utility, and experienced utility. Conditional on classical inputs—risk aversion and patience, life-cycle factors and other demographics, cognitive and non-cognitive skills, and financial resources—B-counts strongly negatively correlate with both objective and subjective aspects of experienced utility. The results hold in much lower-dimensional models employing “Sparsity B-counts” based on bias subsets (a la Gabaix) and/or fewer covariates, illuminating lower-cost ways to use behavioral sufficient statistics to help capture the combined influence of multiple behavioral biases for a wide range of research questions and applications.