150 posts on "Labor Market"
January 12, 2026
Disability in the Labor Market: Earnings
In our previous post we learned that, in general, people with disabilities participate in the labor market at significantly lower rates, and that they are much more likely to be unemployed. Despite these patterns, we found that the labor force participation of workers with disabilities rose noticeably following the pandemic. A relevant question then is how earnings of workers with disabilities compare with workers without disabilities. In this companion post we investigate differences in weekly earnings for workers with and without disabilities. We find that workers with disabilities earn considerably less than workers without disabilities. Additionally, with few exceptions, their earnings have remained roughly constant in real terms since the pre-pandemic period.
Disability in the Labor Market: Employment and Participation
Among people in prime working age (25-54), around 7 percent have a disability of some kind. In this set of companion posts, we will examine how prime-aged workers with disabilities have fared in the labor market compared to the year prior to the pandemic. In this first post, we will show that people with disabilities are far less likely to be employed than people without disabilities, with both lower labor force participation and higher unemployment playing a role. We will also show that although employment rates of people with disabilities are very low, they have risen rapidly during the post-pandemic period, largely because of rising labor force participation. Our results are consistent with an increased prevalence of work from home (WFH) arrangements in the post-COVID period differentially benefiting people with disabilities.
January 8, 2026
Measuring Labor Market Tightness: Data Update and New Web Feature
Good measures of labor market tightness are essential to predict wage inflation and to calibrate monetary policy. In an October 2024 post, we introduced a new indicator of labor market tightness and showed that it tracked wage inflation best out of a broad range of tightness measures. In this post, we update our index through 2025 and show that it also forecasts future wage inflation best both in and out of sample. In addition, we highlight availability of the index as a new regularly updated feature on the New York Fed’s website.
October 15, 2025
A Danger to Self and Others: Consequences of Involuntary Hospitalization
Every state in the country has a law permitting involuntary hospitalization if a person presents a danger to themselves or others as a result of mental illness. If a person reaches this high bar, the logic goes, they should be confined in a psychiatric hospital for treatment until they are stabilized. (The process is also sometimes called involuntary commitment, involuntary psychiatric hold, or sectioning.) Although there is no definitive national accounting, it is estimated that about 1.2 million involuntary psychiatric hospitalizations occur every year (Lee and Cohen 2021). This puts the magnitude on par with the 1.2 million individuals imprisoned in state, federal, and military prisons every year (Carson 2022). In a new Staff Report, we use data from Allegheny County, which includes Pittsburgh, to measure how psychiatric commitments are impacting an individual’s risk of danger to themselves or others, earnings, and housing.
October 2, 2025
Do Employers Comply with Pay Transparency Requirements in Job Postings?
Over the past few months, New Jersey and Vermont have joined a growing number of U.S. states in requiring employers to include an estimated salary range in their online job listings. Has this push for greater pay transparency been effective? In this post, we use granular data on U.S. job postings from Lightcast to assess employers’ compliance with these new regulations. Focusing on the jurisdictions that adopted pay transparency laws early on, we find that many employers ignore pay transparency requirements; roughly a quarter of job listings covered by these laws fail to include salary information.
Posted at 7:00 am in Labor Market | Permalink
September 4, 2025
Are Businesses Scaling Back Hiring Due to AI?
The swift advancement of artificial intelligence (AI) has sparked significant concern that this new technology will replace jobs and stifle hiring. To explore the effects of AI on employment, our August regional business surveys asked firms about their adoption of AI and if they had made any corresponding adjustments to their workforces. Businesses reported a notable increase in AI use over the past year, yet very few firms reported AI-induced layoffs. Indeed, for those already employed, our results indicate AI is more likely to result in retraining than job loss, similar to our findings from last year. That said, AI is influencing recruiting, with some firms scaling back hiring due to AI and some firms adding workers proficient in its use. Looking ahead, however, layoffs and reductions in hiring plans due to AI use are expected to increase, especially for workers with a college degree.
June 2, 2025
How Much Does Immigration Data Explain the Employment‑Gap Puzzle?
A puzzling feature of official U.S. employment statistics in recent years has been the increase in the gap between the nonfarm payroll and household employment numbers. This discrepancy is not trivial. From the end of 2021 though the end of 2024, net job gains in the payroll survey were 3.6 million larger than in the household survey. In this Liberty Street Economics post, we investigate one potential explanation for the emergence of this gap: a sharp rise in undocumented immigration during the post-COVID period that would be differentially reflected in the two surveys. We leverage industry-level data to study the relationship between our estimate of employment of likely undocumented migrants and the payroll-household employment gap. These data suggest that factors besides undocumented immigration likely contributed to the emergence of the gap between the two measures of U.S. employment.
May 15, 2025
The College Economy: Educational Differences in Labor Market Outcomes
It is intuitive that workers with higher levels of education tend to earn more than workers with less education. However, it is also true that workers with more education are much more likely to be employed, and this employment advantage of education has, if anything, grown in recent years. In this post, we document profound differences in labor market outcomes by educational attainment. Drawing on the Economic Heterogeneity Indicators, we find that the gap in employment rates between workers who have completed college and workers who have not is 12 percentage points—which is larger than the employment gaps between workers of different races/ethnicities or between men and women—and is wider than the pre-pandemic gap. Moreover, most of this gap and its recent movements are driven by differences in labor force participation rates rather than by differences in unemployment rates. Fostering higher labor force participation of workers without a college degree thus would be quite helpful in promoting maximum employment.
January 6, 2025
The R&D Puzzle in U.S. Manufacturing Productivity Growth
In a previous post, we provided evidence for a broad-based slowdown in productivity growth across industries and firms in the U.S. manufacturing sector starting in 2010. Since firms’ investment in research and development (R&D) for new technologies constitutes a central driver of productivity growth, in this post we ask if the observed slowdown in productivity may be due to a decline in R&D. We find that “R&D intensity” has been increasing at both the firm and industry level, even as productivity growth declines. This points to a decline in the effectiveness of R&D in generating productivity growth in U.S. manufacturing.
November 15, 2024
To Whom It May Concern: Demographic Differences in Letters of Recommendation
Letters of recommendation from faculty advisors play a critical role in the job market for Ph.D. economists. At their best, they can convey important qualitative information about a candidate, including the candidate’s potential to generate impactful research. But at their worst, these letters offer a subjective view of the candidate that can be susceptible to conscious or unconscious bias. There may also be similarity or affinity bias, a particularly difficult issue for the economics profession, where most faculty members are white men. In this post, we draw on our recent working paper to describe how recommendation letters differ by the gender, race, or ethnicity of the job candidate and how these differences are related to early career outcomes.
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