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Showing papers by "National Bureau of Economic Research published in 2019"


Journal ArticleDOI
TL;DR: The authors conducted a version of the Contingent Worker Survey as part of the RAND American Life Panel in late 2015, and found that the survey results pointed to a r... and a r...
Abstract: To monitor trends in alternative work arrangements, the authors conducted a version of the Contingent Worker Survey as part of the RAND American Life Panel in late 2015. Their findings point to a r...

533 citations


Journal ArticleDOI
TL;DR: In this paper, the authors estimate the effect of minimum wages on low-wage jobs using 138 prominent state-level minimum wage changes between 1979 and 2016 in the U.S using a dierence-in-dierences approach.
Abstract: We estimate the eect of minimum wages on low-wage jobs using 138 prominent state-level minimum wage changes between 1979 and 2016 in the U.S using a dierence-in-dierences approach. We first estimate the eect of the minimum wage increase on employment changes by wage bins throughout the hourly wage distribution. We then focus on the bottom part of the wage distribution and compare the number of excess jobs paying at or slightly above the new minimum wage to the missing jobs paying below it to infer the employment eect. We find that the overall number of low-wage jobs remained essentially unchanged over the five years following the increase. At the same time, the direct eect of the minimum wage on average earnings was amplified by modest wage spillovers at the bottom of the wage distribution. Our estimates by detailed demographic groups show that the lack of job loss is not explained by labor-labor substitution at the bottom of the wage distribution. We also find no evidence of disemployment when we consider higher levels of minimum wages. However, we do find some evidence of reduced employment in tradable sectors. We also show how decomposing the overall employment eect by wage bins allows a transparent way of assessing the plausibility of estimates.

449 citations


Journal ArticleDOI
Richard Karlsson Linnér1, Richard Karlsson Linnér2, Pietro Biroli3, Edward Kong4, S. Fleur W. Meddens2, S. Fleur W. Meddens1, Robbee Wedow, Mark Alan Fontana5, Mark Alan Fontana6, Maël Lebreton7, Stephen P. Tino8, Abdel Abdellaoui2, Anke R. Hammerschlag2, Michel G. Nivard2, Aysu Okbay2, Cornelius A. Rietveld1, Pascal Timshel9, Pascal Timshel10, Maciej Trzaskowski11, Ronald de Vlaming1, Ronald de Vlaming2, Christian L. Zund3, Yanchun Bao12, Laura Buzdugan13, Laura Buzdugan3, Ann H. Caplin, Chia-Yen Chen14, Chia-Yen Chen4, Peter Eibich15, Peter Eibich16, Peter Eibich17, Pierre Fontanillas, Juan R. González18, Peter K. Joshi19, Ville Karhunen20, Aaron Kleinman, Remy Z. Levin21, Christina M. Lill22, Gerardus A. Meddens, Gerard Muntané18, Gerard Muntané23, Sandra Sanchez-Roige21, Frank J. A. van Rooij1, Erdogan Taskesen2, Yang Wu11, Futao Zhang11, Adam Auton, Jason D. Boardman24, David W. Clark19, Andrew Conlin20, Conor C. Dolan2, Urs Fischbacher25, Patrick J. F. Groenen1, Kathleen Mullan Harris26, Gregor Hasler27, Albert Hofman4, Albert Hofman1, Mohammad Arfan Ikram1, Sonia Jain21, Robert Karlsson28, Ronald C. Kessler4, Maarten Kooyman, James MacKillop29, James MacKillop30, Minna Männikkö20, Carlos Morcillo-Suarez18, Matthew B. McQueen24, Klaus M. Schmidt31, Melissa C. Smart12, Matthias Sutter32, Matthias Sutter17, Matthias Sutter33, Roy Thurik1, André G. Uitterlinden1, Jon White34, Harriet de Wit35, Jian Yang11, Lars Bertram22, Lars Bertram36, Dorret I. Boomsma2, Tõnu Esko37, Ernst Fehr3, David A. Hinds, Magnus Johannesson38, Meena Kumari12, David Laibson4, Patrik K. E. Magnusson28, Michelle N. Meyer39, Arcadi Navarro18, Arcadi Navarro40, Abraham A. Palmer21, Tune H. Pers10, Tune H. Pers9, Danielle Posthuma2, Daniel Schunk41, Murray B. Stein21, Rauli Svento20, Henning Tiemeier1, Paul R. H. J. Timmers19, Patrick Turley14, Patrick Turley42, Patrick Turley4, Robert J. Ursano43, Gert G. Wagner16, Gert G. Wagner17, James F. Wilson44, James F. Wilson19, Jacob Gratten45, Jacob Gratten11, James J. Lee46, David Cesarini47, Daniel J. Benjamin48, Daniel J. Benjamin42, Philipp Koellinger2, Philipp Koellinger16, Jonathan P. Beauchamp8 
TL;DR: This paper found evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of their other GWAS, and general risk-tolerance is genetically correlated with a range of risky behaviors.
Abstract: Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

395 citations


Journal ArticleDOI
TL;DR: There is a substantial gap between the promise and reality of artificial intelligence in human resource (HR) management, and four challenges in using data science techniques for HR management are identified.
Abstract: There is a substantial gap between the promise and reality of artificial intelligence in human resource (HR) management. This article identifies four challenges in using data science techniques for...

385 citations


Journal ArticleDOI
TL;DR: In this article, the authors constructed a matched employer-employee data set for the United States using administrative records and found that virtually all of the rise in inequality between workers is accounted for by increasing dispersion in average wages paid by the employers of these individuals.
Abstract: Earnings inequality in the United States has increased rapidly over the last three decades, but little is known about the role of firms in this trend. For example, how much of the rise in earnings inequality can be attributed to rising dispersion between firms in the average wages they pay, and how much is due to rising wage dispersion among workers within firms? Similarly, how did rising inequality affect the wage earnings of different types of workers working for the same employer—men vs. women, young vs. old, new hires vs. senior employees, and so on? To address questions like these, we begin by constructing a matched employer-employee data set for the United States using administrative records. Covering all U.S. firms between 1978 to 2012, we show that virtually all of the rise in earnings dispersion between workers is accounted for by increasing dispersion in average wages paid by the employers of these individuals. In contrast, pay differences within employers have remained virtually unchanged, a finding that is robust across industries, geographical regions, and firm size groups. Furthermore, the wage gap between the most highly paid employees within these firms (CEOs and high level executives) and the average employee has increased only by a small amount, refuting oft-made claims that such widening gaps account for a large fraction of rising inequality in the population.

318 citations


Journal ArticleDOI
TL;DR: In this paper, the authors identify two key costs that are affected by distributed ledger technology: 1) the cost of verification; and 2) the costs of networking, and discuss how blockchain technology and cryptocurrencies will influence the rate and direction of innovation.
Abstract: We rely on economic theory to discuss how blockchain technology and cryptocurrencies will influence the rate and direction of innovation. We identify two key costs that are affected by distributed ledger technology: 1) the cost of verification; and 2) the cost of networking. Markets facilitate the voluntary exchange of goods and services between buyers and sellers. For an exchange to be executed, key attributes of a transaction need to be verified by the parties involved at multiple points in time. Blockchain technology, by allowing market participants to perform costless verification, lowers the costs of auditing transaction information, and allows new marketplaces to emerge. Furthermore, when a distributed ledger is combined with a native cryptographic token (as in Bitcoin), marketplaces can be bootstrapped without the need of traditional trusted intermediaries, lowering the cost of networking. This challenges existing revenue models and incumbents's market power, and opens opportunities for novel approaches to regulation, auctions and the provision of public goods, software, identity and reputation systems.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

294 citations


Journal ArticleDOI
TL;DR: The authors developed a dynamic trade model with spatially distinct labor markets facing varying exposure to international trade and found that the China trade shock resulted in a loss of 0.8 million U.S. manufacturing jobs, about 25% of the observed decline in manufacturing employment.
Abstract: We develop a dynamic trade model with spatially distinct labor markets facing varying exposure to international trade. The model captures the role of labor mobility frictions, goods mobility frictions, geographic factors, and input-output linkages in determining equilibrium allocations. We show how to solve the equilibrium of the model and take the model to the data without assuming that the economy is at a steady state and without estimating productivities, migration frictions, or trade costs, which can be difficult to identify. We calibrate the model to 22 sectors, 38 countries, and 50 U.S. states. We study how the rise in China’s trade for the period 2000 to 2007 impacted U.S. households across more than a thousand U.S. labor markets distinguished by sector and state. We find that the China trade shock resulted in a loss of 0.8 million U.S. manufacturing jobs, about 25% of the observed decline in manufacturing employment from 2000 to 2007. The U.S. gains in the aggregate but, due to trade and migration frictions, the welfare and employment effects vary across U.S. labor markets. Estimated transition costs to the new long-run equilibrium are also heterogeneous and reflect the importance of accounting for labor dynamics.

294 citations


Journal ArticleDOI
TL;DR: The authors discuss the relevance of the recent machine learning literature for economics and econometrics, and discuss the differences in goals, methods, and settings between the ML literature and economics.
Abstract: We discuss the relevance of the recent machine learning (ML) literature for economics and econometrics. First we discuss the differences in goals, methods, and settings between the ML literature an...

273 citations


Journal ArticleDOI
12 Jun 2019-Nature
TL;DR: Assessment of the current understanding of the relationship between climate and conflict, based on the structured judgments of experts from diverse disciplines concludes that climate has affected organized armed conflict within countries, and intensifying climate change is estimated to increase future risks of conflict.
Abstract: Research findings on the relationship between climate and conflict are diverse and contested. Here we assess the current understanding of the relationship between climate and conflict, based on the structured judgments of experts from diverse disciplines. These experts agree that climate has affected organized armed conflict within countries. However, other drivers, such as low socioeconomic development and low capabilities of the state, are judged to be substantially more influential, and the mechanisms of climate–conflict linkages remain a key uncertainty. Intensifying climate change is estimated to increase future risks of conflict. Climate has affected organized armed conflict within countries, and intensifying climate change is estimated to increase future risks of conflict, although other drivers are substantially more influential and the mechanisms of climate–conflict linkages remain uncertain.

257 citations


Journal ArticleDOI
TL;DR: The barriers that inhibit scientists from measuring the effects of AI and automation on the future of work are discussed and a decision framework that focuses on resilience to unexpected scenarios in addition to general equilibrium behavior is recommended.
Abstract: Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. Rising automation is happening in a period of growing economic inequality, raising fears of mass technological unemployment and a renewed call for policy efforts to address the consequences of technological change. In this paper we discuss the barriers that inhibit scientists from measuring the effects of AI and automation on the future of work. These barriers include the lack of high-quality data about the nature of work (e.g., the dynamic requirements of occupations), lack of empirically informed models of key microlevel processes (e.g., skill substitution and human–machine complementarity), and insufficient understanding of how cognitive technologies interact with broader economic dynamics and institutional mechanisms (e.g., urban migration and international trade policy). Overcoming these barriers requires improvements in the longitudinal and spatial resolution of data, as well as refinements to data on workplace skills. These improvements will enable multidisciplinary research to quantitatively monitor and predict the complex evolution of work in tandem with technological progress. Finally, given the fundamental uncertainty in predicting technological change, we recommend developing a decision framework that focuses on resilience to unexpected scenarios in addition to general equilibrium behavior.

256 citations


ReportDOI
TL;DR: In this article, the authors measure the macroeconomic consequences of the convergence of occupational distribution between white men, women, and blacks over the last 50 years and show that the changing frictions implied by the observed occupational convergence account for 15 to 20 percent of growth in aggregate output per worker since 1960.
Abstract: Over the last 50 years, there has been a remarkable convergence in the occupational distribution between white men, women, and blacks. We measure the macroeconomicconsequencesofthisconvergencethroughtheprismofaRoymodel of occupational choice in which women and blacks face frictions in the labor market and in the accumulation of human capital. The changing frictions implied by the observed occupational convergence account for 15 to 20 percent of growth in aggregate output per worker since 1960.

Journal ArticleDOI
16 Apr 2019-JAMA
TL;DR: Among employees of a large US warehouse retail company, a workplace wellness program resulted in significantly greater rates of some positive self-reported health behaviors among those exposed compared with employees who were not exposed, but there were no significant differences in clinical measures of health, health care spending and utilization, and employment outcomes after 18 months.
Abstract: Importance Employers have increasingly invested in workplace wellness programs to improve employee health and decrease health care costs. However, there is little experimental evidence on the effects of these programs. Objective To evaluate a multicomponent workplace wellness program resembling programs offered by US employers. Design, Setting, and Participants This clustered randomized trial was implemented at 160 worksites from January 2015 through June 2016. Administrative claims and employment data were gathered continuously through June 30, 2016; data from surveys and biometrics were collected from July 1, 2016, through August 31, 2016. Interventions There were 20 randomly selected treatment worksites (4037 employees) and 140 randomly selected control worksites (28 937 employees, including 20 primary control worksites [4106 employees]). Control worksites received no wellness programming. The program comprised 8 modules focused on nutrition, physical activity, stress reduction, and related topics implemented by registered dietitians at the treatment worksites. Main Outcomes and Measures Four outcome domains were assessed. Self-reported health and behaviors via surveys (29 outcomes) and clinical measures of health via screenings (10 outcomes) were compared among 20 intervention and 20 primary control sites; health care spending and utilization (38 outcomes) and employment outcomes (3 outcomes) from administrative data were compared among 20 intervention and 140 control sites. Results Among 32 974 employees (mean [SD] age, 38.6 [15.2] years; 15 272 [45.9%] women), the mean participation rate in surveys and screenings at intervention sites was 36.2% to 44.6% (n = 4037 employees) and at primary control sites was 34.4% to 43.0% (n = 4106 employees) (mean of 1.3 program modules completed). After 18 months, the rates for 2 self-reported outcomes were higher in the intervention group than in the control group: for engaging in regular exercise (69.8% vs 61.9%; adjusted difference, 8.3 percentage points [95% CI, 3.9-12.8]; adjustedP = .03) and for actively managing weight (69.2% vs 54.7%; adjusted difference, 13.6 percentage points [95% CI, 7.1-20.2]; adjustedP = .02). The program had no significant effects on other prespecified outcomes: 27 self-reported health outcomes and behaviors (including self-reported health, sleep quality, and food choices), 10 clinical markers of health (including cholesterol, blood pressure, and body mass index), 38 medical and pharmaceutical spending and utilization measures, and 3 employment outcomes (absenteeism, job tenure, and job performance). Conclusions and Relevance Among employees of a large US warehouse retail company, a workplace wellness program resulted in significantly greater rates of some positive self-reported health behaviors among those exposed compared with employees who were not exposed, but there were no significant differences in clinical measures of health, health care spending and utilization, and employment outcomes after 18 months. Although limited by incomplete data on some outcomes, these findings may temper expectations about the financial return on investment that wellness programs can deliver in the short term. Trial Registration ClinicalTrials.gov Identifier:NCT03167658

Journal ArticleDOI
TL;DR: The authors examined which issuer and ICO characteristics predict successful real outcomes (increasing issuer employment and avoiding enterprise failure). Success is associated with disclosure, credible commitment to the project, and quality signals.
Abstract: Initial coin offerings (ICOs) have emerged as a new mechanism for entrepreneurial finance, with parallels to initial public offerings, venture capital, and pre-sale crowdfunding. In a sample of more than 1,500 ICOs that collectively raise $12.9 billion, we examine which issuer and ICO characteristics predict successful real outcomes (increasing issuer employment and avoiding enterprise failure). Success is associated with disclosure, credible commitment to the project, and quality signals. An instrumental variables analysis finds that ICO token exchange listing causes higher future employment, indicating that access to token liquidity has important real consequences for the enterprise.


Journal ArticleDOI
TL;DR: A dynamic asset-pricing model of (crypto-)tokens on (blockchain-based) platforms, and their roles on endogenous user adoption is provided, which produces explosive growth of user base after an initial period of dormant adoption, accompanied by a run-up of token price volatility.
Abstract: We develop a dynamic asset-pricing model of cryptocurrencies/tokens that allow users to conduct peer-to-peer transactions on digital platforms. The equilibrium value of tokens is determined by aggregating heterogeneous users' transactional demand rather than discounting cashflows as in standard valuation models. Endogenous platform adoption builds upon user network externality and exhibits an S-curve — it starts slow, becomes volatile, and eventually tapers off. Introducing tokens lowers users' transaction costs on the platform by allowing users to capitalize on platform growth. The resulting intertemporal feedback between user adoption and token price accelerates adoption and dampens user-base volatility. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Journal ArticleDOI
TL;DR: This work uses insurance claims data covering 28% of individuals with employer-sponsored health insurance in the United States to study the variation in health spending on the privately insured, examine the structure of insurer-hospital contracts, and analyze the variations in hospital prices across the nation.
Abstract: We use insurance claims data for 27.6 percent of individuals with private employer-sponsored insurance in the US between 2007 and 2011 to examine the variation in health spending and in hospitals’ transaction prices. We document the variation in hospital prices within and across geographic areas, examine how hospital prices influence the variation in health spending on the privately insured, and analyze the factors associated with hospital price variation. Four key findings emerge. First, health care spending per privately insured beneficiary varies by a factor of three across the 306 Hospital Referral Regions (HRRs) in the US. Moreover, the correlation between total spending per privately insured beneficiary and total spending per Medicare beneficiary across HRRs is only 0.14. Second, variation in providers’ transaction prices across HRRs is the primary driver of spending variation for the privately insured, whereas variation in the quantity of care provided across HRRs is the primary driver of Medicare spending variation. Consequently, extrapolating lessons on health spending from Medicare to the privately insured must be done with caution. Third, we document large dispersion in overall inpatient hospital prices and in prices for seven relatively homogenous procedures. For example, hospital prices for lower-limb MRIs vary by a factor of twelve across the nation and, on average, two-fold within HRRs. Finally, hospital prices are positively associated with indicators of hospital market power. Even after conditioning on many demand and cost factors, hospital prices in monopoly markets are 15.3 percent higher than those in markets with four or more hospitals.

Journal ArticleDOI
TL;DR: This paper developed statistical techniques for handling experimental measurement error and applied them to data from the Caltech Cohort Study, which conducts repeated incentivized surveys of the student body, demonstrating that results change substantially when measurement error is accounted for.
Abstract: Measurement error is ubiquitous in experimental work. It leads to imperfect statistical controls, attenuated estimated effects of elicited behaviors, and biased correlations between characteristics. We develop statistical techniques for handling experimental measurement error. These techniques are applied to data from the Caltech Cohort Study, which conducts repeated incentivized surveys of the Caltech student body. We replicate three classic experiments, demonstrating that results change substantially when measurement error is accounted for. Collectively, these results show that failing to properly account for measurement error may cause a field-wide bias leading scholars to identify “new” phenomena.

ReportDOI
TL;DR: The authors study how different forms of communication influence the inflation expectations of individuals in a randomized controlled trial and find that reading the actual Federal Open Market Committee (FOMC) statement has about the same average effect on expectations as simply being told about the Federal Reserve's inflation target.
Abstract: We study how different forms of communication influence the inflation expectations of individuals in a randomized controlled trial. We first solicit individuals’ inflation expectations in the Nielsen Homescan panel and then provide eight different forms of information regarding inflation. Reading the actual Federal Open Market Committee (FOMC) statement has about the same average effect on expectations as simply being told about the Federal Reserve’s inflation target. Reading a news article about the most recent FOMC meetings results in a forecast revision which is smaller by half. Our results have implications for how central banks should communicate to the broader public.

Journal ArticleDOI
TL;DR: In this paper, the authors explore how entrepreneurs can use initial coin offerings to fund venture start-up costs and find that venture returns are independent of any committed growth in the supply of tokens over time, but that initial funds raised are maximized by setting that growth to zero to encourage saving by early participants.
Abstract: This paper explores how entrepreneurs can use initial coin offerings - whereby they issue crypto tokens and commit to only accept those tokens as payment for their products - to fund venture start-up costs. We show that the ICO mechanism allows entrepreneurs to generate buyer competition for the token, giving it value. We also find that venture returns are independent of any committed growth in the supply of tokens over time, but that initial funds raised are maximized by setting that growth to zero to encourage saving by early participants. Nonetheless, since the value of the tokens depends on a single period of demand, the ability to raise funds is more limited than in traditional equity finance. Furthermore, a lack of commitment in monetary policy undermines saving behavior, hence the cost of using tokens to fund start-up costs is inflexibility in future capital raises. Crypto tokens can also facilitate coordination among stakeholders within digital ecosystems when network effects are present.

Journal ArticleDOI
TL;DR: Ramey et al. as mentioned in this paper take stock of what we have learned from the Renaissance in fiscal research in the ten years since the financial crisis, and come to the surprising conclusion that the bulk of the estimates for average spending and tax change multipliers lie in a fairly narrow range.
Abstract: Author(s): Ramey, Valerie A | 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 discuss the new innovations in methodology and various strengths and weaknesses of the main approaches to estimating fiscal multipliers. 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. Finally, I review the debate on whether multipliers were higher for the 2009 Obama stimulus spending in the United States or for fiscal consolidations in Europe.

Journal ArticleDOI
TL;DR: This paper studied the causes of nutritional inequality in the United States, and found that the wealthy eat more healthfully than the poor in the US, while the remaining 90% is driven by differences in demand.
Abstract: We study the causes of “nutritional inequality”: why the wealthy eat more healthfully than the poor in the United States. Exploiting supermarket entry and household moves to healthier neighborhoods, we reject that neighborhood environments contribute meaningfully to nutritional inequality. We then estimate a structural model of grocery demand, using a new instrument exploiting the combination of grocery retail chains’ differing presence across geographic markets with their differing comparative advantages across product groups. Counterfactual simulations show that exposing low-income households to the same products and prices available to high-income households reduces nutritional inequality by only about 10%, while the remaining 90% is driven by differences in demand. These findings counter the argument that policies to increase the supply of healthy groceries could play an important role in reducing nutritional inequality.

Posted Content
TL;DR: This paper analyzed the impacts of the 2018 trade war on the U.S. economy and found that tradeable-sector workers in heavily Republican counties were the most negatively affected by the trade war.
Abstract: We analyze the impacts of the 2018 trade war on the U.S. economy. We estimate import demand and export supply elasticities using changes in U.S. and retaliatory tariffs over time. Imports from targeted countries declined 31.5% within products, while targeted U.S. exports fell 11.0%. We find complete pass-through of U.S. tariffs to variety-level import prices. Using a general equilibrium framework that matches these elasticities, we compute the aggregate and regional impacts. Annual consumer and producer losses from higher costs of imports were $68.8 billion (0.37% of GDP). After accounting for higher tariff revenue and gains to domestic producers from higher prices, the aggregate welfare loss was $7.8 billion (0.04% of GDP). U.S. tariffs favored sectors located in politically competitive counties, but retaliatory tariffs offset the benefits to these counties. We find that tradeable-sector workers in heavily Republican counties were the most negatively affected by the trade war.

Journal ArticleDOI
TL;DR: Algorithms are not only a threat to be regulated; with the right safeguards in place, they have the potential to be a positive force for equity.
Abstract: The law forbids discrimination. But the ambiguity of human decision-making often makes it extraordinarily hard for the legal system to know whether anyone has actually discriminated. To understand how algorithms affect discrimination, we must therefore also understand how they affect the problem of detecting discrimination. By one measure, algorithms are fundamentally opaque, not just cognitively but even mathematically. Yet for the task of proving discrimination, processes involving algorithms can provide crucial forms of transparency that are otherwise unavailable. These benefits do not happen automatically. But with appropriate requirements in place, the use of algorithms will make it possible to more easily examine and interrogate the entire decision process, thereby making it far easier to know whether discrimination has occurred. By forcing a new level of specificity, the use of algorithms also highlights, and makes transparent, central tradeoffs among competing values. Algorithms are not only a threat to be regulated; with the right safeguards in place, they have the potential to be a positive force for equity.

Journal ArticleDOI
TL;DR: In this evaluation of the dispensing of naloxone across the United States, NALs granting direct authority to pharmacists were associated with significant reductions in fatal overdoses, but they may also increase nonfatal overdoses seen in emergency department visits.
Abstract: Importance Given high rates of opioid-related fatal overdoses, improving naloxone access has become a priority. States have implemented different types of naloxone access laws (NALs) and there is controversy over which of these policies, if any, can curb overdose deaths. We hypothesize that NALs granting direct authority to pharmacists to provide naloxone will have the greatest potential for reducing fatal overdoses. Objectives To identify which types of NALs, if any, are associated with reductions in fatal overdoses involving opioids and examine possible implications for nonfatal overdoses. Design, Setting, and Participants State-level changes in both fatal and nonfatal overdoses from 2005 to 2016 were examined across the 50 states and the District of Columbia after adoption of NALs using a difference-in-differences approach while estimating the magnitude of the association for each year relative to time of adoption. Policy environments across full state populations were represented in the primary data set. The association for 3 types of NALs was associated: NALs providing direct authority to pharmacists to prescribe, NALs providing indirect authority to prescribe, and other NALs. The study was conducted from January 2017 to January 2019. Exposures Fatal and nonfatal overdoses in states that adopted NAL laws were compared with those in states that did not adopt NAL laws. Further consideration was given to the type of NAL passed in terms of its association with these outcomes. We hypothesize that NALs granting direct authority to pharmacists to provide naloxone will have the greatest potential for reducing fatal overdoses. Main Outcomes and Measures Fatal overdoses involving opioids were the primary outcome. Secondary outcomes were nonfatal overdoses resulting in emergency department visits and Medicaid naloxone prescriptions. Results In this evaluation of the dispensing of naloxone across the United States, NALs granting direct authority to pharmacists were associated with significant reductions in fatal overdoses, but they may also increase nonfatal overdoses seen in emergency department visits. The effect sizes for fatal overdoses grew over time relative to adoption of the NALs. These policies were estimated to reduce opioid-rated fatal overdoses by 0.387 (95% CI, 0.119-0.656;P = .007) per 100 000 people in 3 or more years after adoption. There was little evidence of an association for indirect authority to dispense (increase by 0.121; 95% CI, −0.014 to 0.257;P = .09) and other NALs (increase by 0.094; 95% CI, −0.040 to 0.227;P = .17). Conclusions and Relevance Although many states have passed some type of law affecting naloxone availability, only laws allowing direct dispensing by pharmacists appear to be useful. Communities in which access to naloxone is improved should prepare for increases in nonfatal overdoses and link these individuals to effective treatment.

ReportDOI
TL;DR: In this paper, the authors characterize the factors that determine who becomes an inventor in America by using de-identified data on 1.2 million inventors from patent records linked to tax records.
Abstract: We characterize the factors that determine who becomes an inventor in America by using de-identified data on 1.2 million inventors from patent records linked to tax records. We establish three sets of results. First, children from high-income (top 1%) families are ten times as likely to become inventors as those from below-median income families. There are similarly large gaps by race and gender. Differences in innate ability, as measured by test scores in early childhood, explain relatively little of these gaps. Second, exposure to innovation during childhood has significant causal effects on children's propensities to become inventors. Growing up in a neighborhood or family with a high innovation rate in a specific technology class leads to a higher probability of patenting in exactly the same technology class. These exposure effects are gender-specific: girls are more likely to become inventors in a particular technology class if they grow up in an area with more female inventors in that technology class. Third, the financial returns to inventions are extremely skewed and highly correlated with their scientific impact, as measured by citations. Consistent with the importance of exposure effects and contrary to standard models of career selection, women and disadvantaged youth are as under-represented among highimpact inventors as they are among inventors as a whole. We develop a simple model of inventors' careers that matches these empirical results. The model implies that increasing exposure to innovation in childhood may have larger impacts on innovation than increasing the financial incentives to innovate, for instance by cutting tax rates. In particular, there are many “lost Einsteins” - individuals who would have had highly impactful inventions had they been exposed to innovation

ReportDOI
TL;DR: In this article, a randomized controlled trial with housing voucher recipients in Seattle and King County was conducted, where the authors provided services to reduce barriers to moving to high-upward mobility neighborhoods: customized search assistance, landlord engagement, and short-term financial assistance.
Abstract: 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 neighborhoods: 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 program'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.

ReportDOI
TL;DR: This paper developed a framework for evaluating the welfare impact of various interventions designed to increase take-up of social safety net programs in the presence of potential behavioral biases, and calibrate the key parameters using a randomized field experiment in which 30,000 elderly individuals not enrolled in but likely eligible for the Supplemental Nutrition Assistance Program (SNAP) are either provided with information that they are likely eligible, provided with this information and also offered assistance in applying, or are in a "status quo" control group.
Abstract: This paper develops a framework for evaluating the welfare impact of various interventions designed to increase take-up of social safety net programs in the presence of potential behavioral biases. We calibrate the key parameters using a randomized field experiment in which 30,000 elderly individuals not enrolled in – but likely eligible for – the Supplemental Nutrition Assistance Program (SNAP) are either provided with information that they are likely eligible, provided with this information and also offered assistance in applying, or are in a "status quo" control group. Only 6 percent of the control group enrolls in SNAP over the next 9 months, compared to 11 percent of the Information Only group and 18 percent of the Information Plus Assistance group. The individuals who apply or enroll in response to either intervention receive lower benefits and are less sick than the average enrollee in the control group. The results are consistent with the existence of optimization frictions that are greater for needier individuals, suggesting that the poor targeting properties of the interventions reduce their welfare gains.

Journal ArticleDOI
TL;DR: A model-selection method to systematically evaluate the contribution to asset pricing of any new factor, above and beyond what a high-dimensional set of existing factors explains, is proposed.
Abstract: We propose a model-selection method to systematically evaluate the contribution to asset pricing of any new factor, above and beyond what a high-dimensional set of existing factors explains. Our methodology explicitly accounts for potential model-selection mistakes that produce a bias due to the omitted variables, unlike the standard approaches that assume perfect variable selection, which rarely occurs in practice. We apply our procedure to a set of factors recently discovered in the literature. While most of these new factors are found to be redundant relative to the existing factors, a few — such as profitability — have statistically significant explanatory power beyond the hundreds of factors proposed in the past. In addition, we show that our estimates and their significance are stable, whereas the model selected by simple LASSO is not. Finally, we provide additional applications of our procedure that illustrate how it could help control the proliferation of factors in the zoo.

Journal ArticleDOI
TL;DR: A number of recent papers have argued that US firms exert increasing market power, as measured by their markups of price over marginal cost as mentioned in this paper, which is based on the hypothesis of firm cost minimization Yet different assumptions and methods of implementation lead to quite different conclusions regarding the levels and trends of markups.
Abstract: A number of recent papers have argued that US firms exert increasing market power, as measured by their markups of price over marginal cost I review three of the main approaches to estimating economy-wide markups and show that all are based on the hypothesis of firm cost minimization Yet different assumptions and methods of implementation lead to quite different conclusions regarding the levels and trends of markups I survey the literature critically and argue that some of the startling findings of steeply rising markups are difficult to reconcile with other evidence and with aggregate data Existing methods cannot determine whether markups have been stable or whether they have risen modestly over the past several decades Even relatively small increases in markups are consistent with significant changes in aggregate outcomes, such as the observed decline in labor's share of national income

Journal ArticleDOI
TL;DR: In this article, the authors show that contradictory findings on the labor market effects of exogenous refugee waves such as the Mariel Boatlift in Miami have been found in the literature.
Abstract: Studies have reached conflicting conclusions regarding the labor market effects of exogenous refugee waves such as the Mariel Boatlift in Miami The authors show that contradictory findings on the