ASSA Round-up: Day 3
Today was the final day of the three-day annual meeting of the Allied Social Science Associations, which is organized by the American Economic Association. The conference, held virtually this year, featured hundreds of sessions covering a wide variety of economics and other social science research. We’ve already posted the abstracts of some of the papers that caught the attention of Equitable Growth Staff during Day One and Day Two, as well as links to the sessions at which they were presented. Following are additional papers from the first two days as well as some from today’s final slate of sessions.
Nickolas Gagnon, Vienna University of Economics and Business, Kristof Bosmans, Maastricht University, and Arno Riedl, Maastricht University
Abstract: Labor market opportunities and wages may be unfair for various reasons, and how workers respond to different types of unfairness can have major economic consequences. Using an online labor platform, where workers engage in an individual task for a piece-rate wage, we investigate the causal effect of neutral and gender-discriminatory unfair chances on labor supply. We randomize workers into treatments where we control relative pay and chances to receive a low or a high wage. Chances can be fair, unfair based on an unspecified source, or unfair based on gender discrimination. Unequal pay reduces labor supply of low-wage workers, irrespective of whether the low wage is the result of fair or unfair chances. Importantly, the source of unfair chances matters. When a low wage is the result of gender-discriminatory chances, workers matched with a high-wage worker substantially reduce their labor supply compared to the case of equal low wages (-22%). This decrease is twice as large as those induced by low wages due to fair chances or unfair chances coming from an unspecified source. In addition, exploratory analysis suggests that in response to unequal pay, low-wage male workers reduce labor supply irrespective of the source of inequality, whereas low-wage female workers reduce labor supply only if unequal pay is due to gender-discriminatory chances. Our results concerning gender discrimination indicate a new reason for the lower labor supply of women, which is a prominent explanation for the gender gap in earnings.
Nina Roussille, University of California, Berkeley
Abstract: The gender ask gap measures the extent to which women ask for lower salaries than comparable men. This paper studies the role of the ask gap in generating wage inequality using novel data from Hired.com, a leading online recruitment platform for full time engineering jobs in the United States. To use the platform, job candidates must post an ask salary, stating how much they want to make in their next job. Firms then apply to candidates by offering a bid salary they are willing to pay the candidate. If the candidate is hired, a final salary is recorded. After adjusting for resume characteristics, the ask gap is 3.3%, the bid gap is 2.4% and the gap in final offers is 1.8%. Remarkably, further controlling for the ask salary explains all of the gender gaps in bid and final salary on the platform. To estimate the market-level effects of an increase in women’s ask salary, I exploit a sudden change in how candidates were prompted to provide their ask salary. For a subset of candidates, in mid-2018, the answer box used to solicit the ask salary went from an empty field to a pre-filled entry with the median salary on the platform for a similar candidate. Comparing candidates creating a profile before and after the feature change, I find that this change drove the ask gap and the bid gap to zero. In addition, women received the same number of bids before and after the change, suggesting they face little penalty for demanding wages comparable to men.
Francesca Truffa, Northwestern University, Menaka Hampole, Northwestern University, Ashley Wong, Northwestern University
Abstract: In this paper, we investigate how female peers influence the likelihood of attaining senior corporate leadership positions for female MBA graduates. Using a combination of administrative data from a top 10 U.S. business school and hand-collected resumes from a large professional social media platform, we first document new facts on the evolution of the gender gap in the corporate management pipeline. Specifically, while there is no gender gap in the likelihood of becoming a manager, there is a gender gap in the probability of attaining senior-level managerial positions. We find that this difference is driven by a 10 percentage point gender gap in the probability of becoming a senior manager immediately after the MBA and by a 20% gap in the promotion rate from low-level manager to Director or VP. In the second half of the paper, we exploit the variation in gender composition of peers groups through the random assignment of MBA students to sections. We find that a 1 standard deviation increase in the proportion of female MBA peers leads to a 5% increase in the likelihood of holding a senior-level management position for women with no effect for men. The increase is not driven by more women entering any management positions, but rather, an increase in the probability of women attaining a senior-level position earlier in their careers as well as an increase in promotion rate along the pipeline.
Jose Joaquin Lopez, University of Memphis, Jamein P. Cunningham, University of Memphis
Abstract: We present new evidence on differences in litigation, judge dismissal, and plaintiff win rates across United States district courts from 1979 to 2016. Across courts, litigation rates are negatively (positively) correlated with judge dismissal (plaintiff win) rates. Further, Republican judges tend to dismiss cases at a higher rate than Democrats, regardless of judge gender and race. Finally, states with higher litigation rates also exhibit higher racial wage gaps, whereas states where judge dismissal (plaintiff win) rates are higher experience higher (lower) racial wage gaps. Our results highlight the importance of legal institutions on the persistence of racial inequality.
Jhacova Williams, Economic Policy Institute
Abstract: Using a unique dataset, this paper examines the extent to which streets named after prominent Confederate generals reflect an area’s racial animus toward blacks and are related to black-white labor market differentials. The analysis shows that Confederate streets are positively associated with a proxy for historical racial animus. Specifically, I show that areas that experienced more historical lynchings have more streets named after prominent Confederate generals today. Examining individual-level data show that blacks who reside in areas that have a relatively higher number of Confederate streets are less likely to be employed, more likely to be employed in low-status occupations, and have lower wages compared to whites. I find no evidence that geographic sorting explains these results. Investigating whether these results extend to other groups shows that Confederate streets are associated with employment, occupational status, and wage differentials between other minorities and whites.
Maggie E.C. Jones, University of Victoria, Lisa D. Cook, Michigan State University, Trevon D. Logan, Ohio State University, and David Rosé, Wilfrid Laurier University
Abstract: Models of taste-based discrimination suggest that competition will drive down the market share of discriminatory firms even in the absence of government intervention. We present a stylized model that captures the nature of the relationship between the ratio of non-discriminatory to discriminatory firms and the ratio of non-discriminatory to discriminatory consumers. We then consider the case of discrimination against black consumers during the Jim Crow era. Combining exogenous variation in the racial composition of local markets induced by white casualties during WWII with a novel dataset of discriminatory and non-discriminatory firms, we find that white casualties are associated with large increases in both the number of non-discriminatory public accommodations as well as the ratio of non-discriminatory to discriminatory public accommodations throughout the United States. While our analysis is most consistent with the market conditions hypothesis, we show that activism among blacks likely played a role in the expansion of access to public accommodations.
Rob Gillezeau, University of Victoria, Jamein P. Cunningham, University of Memphis, Donna Feir, Federal Reserve Bank of Minneapolis and University of Victoria
Abstract: For decades, the rate of civilians killed by law enforcement in the United States has been unprecedented relative to its comparator countries. In this paper, we explore a potential causal factor: the provision of collective bargaining rights to law enforcement beginning in the 1950s and continuing through the 1980s. Using an event study approach that takes advantage of variation in the location and timing of when officers are granted bargaining rights, we find that over 60% of the increase in non-white civilian deaths can be explained by exposure to collective bargaining. In contrast, there is little to no impact for the white civilian population. Further, access to collective bargaining has no impact on total crime, violent crime, or officer deaths and causes a modest increase in compensation and decline in officer employment. These results are robust to an empirical strategy that relies strictly on border counties, which ensures a more effective control group. It appears that the collective bargaining process is, on average, being used to protect the ability of officers to discriminate in the disproportionate use of force against the non-white population. The results indicate that the employer, in this case local and regional governments, have a responsibility to bargain in a manner that protects all members of the public.
Evan K. Rose, University of California, Berkeley
Abstract: Most convicted criminals are sentenced to probation and allowed to return home. On probation, however, a technical rule violation such as not paying fees can result in incarceration. Rule violations account for more than 30% of all prison spells in many states and are significantly more common among black offenders. I test whether technical rules are effective tools for identifying likely reoffenders and deterring crime and examine their disparate racial impacts using administrative data from North Carolina. Analysis of a 2011 reform eliminating prison punishments for technical violations reveals that 40% of rule breakers would go on to commit crimes if their violations were ignored. The same reform also closed a 33% black-white gap in incarceration rates without substantially increasing the black-white reoffending gap. These effects combined imply that technical rules target riskier probationers overall, but disproportionately affect low-risk black offenders. To justify black probationers’ higher violation rate on efficiency grounds, their crimes must be roughly twice as socially costly as white probationers’. Exploiting the repeat-spell nature of the North Carolina data, I estimate a semi-parametric competing risks model that allows me to distinguish the effects of particular types of technical rules from unobserved probationer heterogeneity. The estimates reveal that the deterrent effects of harsh punishments for rule breaking are negligible. Rules related to the payment of fees and fines, which are common in many states, are ineffective in tagging likely reoffenders and drive differential impacts by race. These findings illustrate the potentially large influence of facially race-neutral policies on racial disparities in criminal justice outcomes.
Monica I. Garcia-Perez, St. Cloud State University
Abstract: Using the Health Retirement Survey (2006-2017) -(HRS- RAND HRS Longitudinal File- Bugliari, 2009), I plan to analyze the connection between wealth depletion and health shocks among elderly Hispanic. I plan to identify the effect of nearly diagnosed conditions, separated by their level of severity (Mild, Intermediate, and Severe), on the average wealth depletion compared to White individuals. The key health conditions that are evaluated include diabetes and liver disease. Both are conditions that make this population more vulnerable to the current virus COVID-19.
Jose Fernandez, University of Louisville
Abstract: Due to the financial crisis facing Puerto Rico, many medical professionals on the island have left. Former Governor Rossello passed Act 14 in April of 2017 hoping to stave off the exodus of physicians. Act 14 reduces the income tax charge on medical services from 30 percent to 4 percent for 15 years. During the same year Puerto Rico experience a devastating category 4 hurricane, which left the island without power or water for several months. We will use a difference in difference estimation to estimate the effects of this change in the marginal tax rate to both keep physicians on the island as well as attract new physicians to the island from the mainland US. We use data from the Quarterly Census of Employment and Wages, the May Occupational Employment Statistics counts, and the AAMC Report on Residents. We find the number of healthcare providers decreased by 6.5 percent. The number of family physicians and pediatricians fell by 17.5 percent and 62 percent respectively. However, the number of registered nurses increased by 2.7 percent. Although the levels of healthcare providers decrease, the rate of healthcare provides per capita actually increased during this time period since the population decreases more rapidly than the fall in the level of healthcare providers.
Chang Hyung (Max) Lee, San Francisco State University
Abstract: This paper models the education and coming out choices of sexual minorities and empirically tests the model predictions using the American Community Survey and the National Longitudinal Study of Adolescent to Adult Health. The model predicts higher educational attainment for minorities if education reduces potential discrimination. The gap is driven by two mechanisms I call counterbalance and selection. Minorities choose to obtain more education in anticipation of future discrimination (counterbalance), and educated minorities become more likely to come out as they experience less discrimination relative to their less-educated counterparts (selection). The empirical analyses suggest that sexual minority men obtain more education than heterosexual counterparts, the education gap disappears in LGBTQ-friendly places, and the ability threshold for college enrollment is lower for minority men relative to their heterosexual counterparts. With women, the ability threshold is surprisingly higher for sexual minorities. I explore the possibility that sexual minority women may reduce their education to avoid discrimination.
Jonathan Dingel, University of Chicago, and Brent Neiman, University of Chicago
Abstract: Evaluating the economic impact of “social distancing” measures taken to arrest the spread of COVID-19 raises a fundamental question about the modern economy: how many jobs can be performed at home? We classify the feasibility of working at home for all occupations and merge this classification with occupational employment counts. We find that 37 percent of jobs in the United States can be performed entirely at home, with significant variation across cities and industries. Applying our occupational classifications to 85 other countries reveals that lower-income economies have a lower share of jobs that can be done at home.
Anne A. Brenøe, University of Zurich, Serena P. Canaan, American University of Beirut, Nikolaj A. Harmon, University of Copenhagen, and Heather N. Royer, University of California, Santa Barbara
Abstract: Most of the existing evidence on the effectiveness of family leave policies comes from studies focusing on their impacts on affected families – that is, mothers, fathers, and their children – without a clear understanding of the costs and effects on firms and coworkers. We use data from Denmark to evaluate the effect on firms and coworkers when a worker gives birth and goes on leave. Using a dynamic difference-in-differences design, we compare small firms in which a female employee is about to give birth to an observationally equivalent sample of small firms with female employees who are not close to giving birth. Identification rests on a parallel trends assumption, which we substantiate through a set of natural validity checks. When an employee gives birth, she goes on leave from her firm for 9.5 months on average. Firms respond by increasing their labor inputs along several margins such that the net effect on total work hours is close to zero. Firms’ total wage bill increases in response to leave take up, but this is driven entirely by wages paid to workers on leave for which firms receive reimbursement. There are no measurable effects on firm output, profitability or survival. Finally, coworkers of the woman going on leave see temporary increases in their hours, earnings, and likelihood of being employed but experience no significant changes in well-being at work as proxied by sick days. Overall, our results suggest that employees going on parental leave impose negligible costs on their firm and coworkers.
Raj Chetty, Harvard University, John Van Reenen, Massachusetts Institute of Technology, Owen Zidar, Princeton University, and Eric Zwick, University of Chicago
Abstract: We use de-identified tax returns to characterize entrepreneurship across the American population since the late 1990s. Our longitudinal data permit an analysis of which new firms end up being highly successful, allowing us to distinguish startups that are destined to remain as small businesses from “job creators.” We document new facts on lifecycle of “job creating” entrepreneurs – from their family backgrounds, to the areas they grew up in, to their labor market trajectories. Entrepreneurs tend to be white, male and drawn from high-income families. Part of the relationship between parental income and entrepreneurship appears to be due to the causal effect of liquidity, based on an analysis of liquidity shocks around IPOs. Another part appears to be due to exposure: children exposed to more entrepreneurs while they are growing up are more likely to start businesses themselves. Entrepreneurs are often seen as vital to economic dynamism, so we contrast them with another engine of growth – inventors. We find that the geographic origins of entrepreneurs are more dispersed than those of inventors, although the origins of “star” (high job creators) and high-tech entrepreneurs is more similar and concentrated in a few hubs. Children exposed to more entrepreneurship growing up tend to be more likely to become entrepreneurs themselves. Using a matched event study design, we find that (consistent with existing evidence), the variance of expected income increases after starting a business. However, contrary to received wisdom, becoming an entrepreneur has a positive effect on individual income even at the median. We conclude that increasing the number of “star” entrepreneurs may call for efforts to expand the supply of entrepreneurs, potentially through the provision of liquidity and exposure to entrepreneurship at early stages.
Yuci Chen, University of Illinois at Urbana-Champaign
Abstract: I investigate how establishments adjust their production plans on various margins when wage rates increase. Exploiting state-by-year variation in minimum wage, I analyze U.S. manufacturing plants’ responses over a 23-year period. Using instrumental variable method and Census Microdata, I find that when the hourly wage of production workers increases by one percent, manufacturing plants reduce the total hours worked by production workers by 0.7 percent and increase capital expenditures on machinery and equipment by 2.7 percent. The reduction in total hours worked by production workers is driven by intensive-margin changes. The estimated elasticity of substitution between capital and labor is 0.85. Following the wage increases, no statistically significant changes emerge in revenue, materials or total factor productivity. Additionally, I find that when wage rates increase, establishments are more likely to exit the market. Finally, I provide evidence that when the minimum wage increases the wages of some of the establishments in a firm, the firm also increases the wages for its other establishments.
Eliza Forsythe, University of Illinois at Urbana-Champaign
Abstract: Minimum wage increases often result in spillovers above the strict minimum wage cutoff, however the mechanism behind these spillovers is not well understood. Using establishment-level panel data from the Occupational Employment Statistics program, I estimate the effect of minimum wage increases implemented by 10 states in 2014and 2015 on establishment wage and occupational structures. I show that minimum wage increases lead to wage spillovers within establishments. I find no evidence that minimum wage increases induce establishments to reorganize their occupational structure across major occupational groups, however I find it does lead to a 1% increase in reallocation within 2-digit occupations. In addition, I do not find any major effect of minimum wage increases on the type of establishment that closes or the occupation or wage structure of newly opened establishments. Finally, I find that minimum wage increases propagate up the management hierarchy, leading to increased wages for supervisors. Nonetheless, I find overall wage inequality decreases within establishments after minimum wage increases.
Daron Acemoglu, Massachusetts Institute of Technology, and Pascual Restrepo, Boston University
Abstract: This paper develops a framework that links automation to inequality. At the center of the framework is the substitution of machines for tasks brought about by the automation process. Critically, workers have different competitive advantages and specialize in different industries and occupations. The pattern of automation then creates downward pressure on the wages of different groups of workers and shapes the structure of wages. The theoretical framework characterizes the direct and the general equilibrium (indirect) effects of automation. The general equilibrium effects involve, for example, the fact that once the tasks performed by some workers are automated, these workers compete for jobs previously performed by other workers. We then derive a flexible framework based on this theoretical model for estimating the extent of inequality created by automation. Our empirical framework flexibly includes the standard forces emphasized in the literature, including skill-biased technological change, gender-biased technological change, and changes in experience premia as well as inter-industry wage premia that may be time-varying. We estimate this model on data on the evolution of wages by detailed demographic groups. Our estimates indicate that the majority of the changes in the US wage structure are due to automation. For example, more than 80% of the changes in the college-high school wage premia are explained by automation patterns, and very little is accounted for by standard skill-biased technological change channel.
Daron Acemoglu, Massachusetts Institute of Technology, Gary Andersen, National Center for Science and Engineering Statistics, David Beede, U.S. Census Bureau, Catherine Buffington, U.S. Census Bureau, Emin Dinlersoz, U.S. Census Bureau, Lucia Foster, U.S. Census Bureau, Nathan Goldschlag, U.S. Census Bureau, John C. Haltiwanger, University of Maryland, Zachary Kroff, U.S. Census Bureau, Pascual Restrepo, Boston University, and Nikolas Zolas, U.S. Census Bureau
Abstract: This paper provides initial evidence on the connection between advanced technology presence and the size and composition of the workforce of U.S. firms and industries. Recent research using task-based models of production has demonstrated that advanced technology use by firms can alter both the number and types of workers through the creation of new tasks and the substitution of capital for labor in existing tasks. These effects can induce reallocation of labor and other inputs. Detailed evidence on the extent of these effects has been lacking for the population of U.S. firms, mainly due to the absence of reliable and comprehensive measures of technology use at the firm level. This analysis leverages a new technology module included in Census Bureau’s 2019 Annual Business Survey that collected data from over 300,000 firms on the adoption and use of five advanced technologies (Robotics, AI, Cloud Computing, Specialized Software, and Specialized Equipment), combined with firms’ subjective assessments of how each technology alters their workforce. The survey data is matched at the firm-level with administrative data on employment, revenues, and wages from the Census Bureau’s Longitudinal Business Database. The data is used to document across firms and industries the heterogeneity in technology adoption rates, the intensity of technology use, motivations for technology adoption, and barriers to adoption. The analysis also explores how firm-level technology adoption and use is related to firm and industry-level employment growth, how the adoption of new technologies creates (or destroys) roles for labor, and which type of technologies complement (or substitute) labor and skill.