The Declining Labor Market Prospects of Less-Educated Men

What drives innovation? Lessons from COVID-19 R&D

This paper studies the global R&D effort to fight the deadliest diseases. We find: (1) the elasticity of R&D effort with respect to market size is about 1/2 in the cross-section of diseases; (2) given this elasticity, the R&D response to COVID-19 has been 4 to 26 times greater than that implied by its market size; (3) the aggregate short-term elasticity of science and innovation can be very large, as demonstrated by the aggregate flow of clinical trials increasing by 38% in 2020, with limited crowding out of trials for non-COVID diseases; and (4) public institutions and government-led incentives were a key driver of the COVID-19 R&D effort-with public research institutions accounting for 70 percent of all COVID-19 clinical trials globally. Overall, our work suggests that leveraging early-stage incentives, non-monetary incentives, and public institutions may be important for scaling up global innovation.

People Judge Discrimination Against Women More Harshly Than Discrimination Against Men - Does Statistical Fairness Discrimination Explain Why?

Previous research has shown that people care less about men than about women who are left behind. We show that this finding extends to the domain of labor market discrimination: In identical scenarios, people judge discrimination against women more morally bad than discrimination against men. This result holds in a representative sample of the US population and in a larger but not representative sample of Amazon Mechanical Turk (Mturk) respondents. We test if this gender gap is driven by statistical fairness discrimination, a process in which people use the gender of the victim to draw inferences about other characteristics which matter for their fairness judgments. We test this explanation with a survey experiment in which we explicitly hold information about the victim of discrimination constant. Our results provide only mixed support for the statistical fairness discrimination explanation. In our representative sample, we see no meaningful or significant effect of the information treatments. By contrast, in our Mturk sample, we see that providing additional information partly reduces the effect of the victim’s gender on judgment of the discriminator. While people may engage in statistical fairness discrimination, this process is unlikely to be an exhaustive explanation for why discrimination against women is judged as worse.

The geography of desperation in America: Labor force participation, mobility, place, and well-being

There are deep divisions between Americans with opportunities and hope for the future and those left behind. We explored this earlier using metrics of reported well-being and found deep desperation - and an association with premature death - among less than college educated whites. This contrasts with more hope for the future among Black and Hispanics, despite worse objective conditions. Here we extend these findings and focus on workers out of the labor force (OLF), their low well-being, and their lack of geographic mobility. The well-being of this group varies substantially across age, gender, and race. We find that those in prime age fare worse than other age groups; within prime age respondents, women report higher well-being than men, and among prime age males, whites report significantly lower well-being, worse health, and higher pain than minorities. Prime age OLF respondents - especially white males - report worse health than those in other labor market categories, suggesting that their dropout is partly due to bad health. Individuals in counties with a higher percentage of respondents still in their childhood census tracts have poorer health and little hope. Those in counties with higher percentages of adults in their parents' homes have even worse well-being and health. The state of these cohorts - and their tendency to stay in the places they grew up rather than move - is one potential explanation for the declining levels of geographic mobility in the U.S.

The rise of US earnings inequality: Does the cycle drive the trend?

We document that declining hours worked are the primary driver of widening inequality in the bottom half of the male labor earnings distribution in the United States over the past 52 years. This decline in hours is heavily concentrated in recessions: hours and earnings at the bottom fall sharply in recessions and do not fully recover in subsequent expansions. Motivated by this evidence, we build a structural model to explore the possibility that recessions cause persistent increases in inequality; that is, that the cycle drives the trend. The model features skill-biased technical change, which implies a trend decline in low-skill wages relative to the value of non-market activities. With this adverse trend in the background, recessions imply a potential double-whammy for low skilled men. This group is disproportionately likely to experience unemployment, which further reduces skills and potential earnings via a scarring effect. As unemployed low skilled men give up job search, recessions generate surges in non-participation. Because non-participation is highly persistent, earnings inequality remains elevated long after the recession ends.