Employment and participation rates for US prime‐age women rose steadily during the second half of the 20th century. After 2000, however, those rates stagnated, even as employment and participation rates for women in other industrialized countries continued to rise. This session will review the critical role that women's employment has played in our understanding of full employment during the past 50 years. It will then investigate labor market frictions and institutional barriers, such as limited childcare availability, that may be curtailing employment among American women today. The COVID-19 pandemic likely increased barriers to female participation due to women's increased family responsibilities during this period. But the pandemic could turn out to have a positive long-term effect on women's participation if it has enhanced the ability of women to work from home.

Historically, maximum employment has occurred alongside large racial gaps in unemployment rates and employment‐to‐population ratios. What does current research say about the sources of these gaps and how they are affected by cyclical variations in economic activity? What kinds of policies might be effective in reducing these racial employment gaps? For instance, would improving access to credit for individuals belonging to traditionally disadvantaged groups and/or for new business owners help foster more entrepreneurship and provide better, longer‐lasting employment opportunities? Are there alternative definitions of full employment that would generate greater benefits for traditionally disadvantaged groups?

The maximum-employment mandate was conceived at a time of great optimism for job‐training programs, which could potentially foster full employment by equipping workers with in‐demand skills. Over the years, US job‐training programs have had a mixed record of success, but sector‐specific programs such as WorkAdvance, Project Quest, and Year Up have shown positive signs recently. A range of degree and certificate programs at community and for-profit colleges also provides such skills. This session will ask whether job‐training programs can contribute meaningfully to full employment today. What constraints do effective programs face when scaling up to meet the needs of additional workers? Can job-training programs make up for longstanding failures of the US educational system with respect to historically disadvantaged groups? The session will also consider potential lessons from successful job‐training programs in other countries, such as Denmark and Germany, where publicly funded retraining is an important complement to the receipt of unemployment insurance benefits.

The gig economy has become a source of flexible employment opportunities for a large portion of the US workforce. This session will explore how policymakers should view the gig economy as they evaluate progress on the full-employment mandate. In describing the characteristics of gig workers and their motivations, the session seeks to gain insight into whether gig-economy jobs represent a last resort for people who cannot find more stable jobs or instead reflect a preference for flexible work. The session will also consider the cyclical aspects of gig‐economy employment, such as whether participation and hours increase during periods of elevated unemployment, and whether an increase in gig employment reveals information about labor market slack that is not captured in standard employment surveys.

With its new monetary policy strategy in 2020, the Federal Open Market Committee indicated that it would not preemptively tighten policy due only to employment approaching levels consistent with the committee's estimate of full employment. Before implementing tightening, the FOMC would also need to see evidence that such employment levels were resulting in above‐target inflation. Absent unwanted increases in inflation or other risks that could impede the attainment of the committee's goals, high employment would not by itself be a cause for concern. The panel will discuss whether this approach to probing for full employment is effective, especially given the inflation experience after the initial phase of the COVID‐19 pandemic. Does waiting for an inflation signal from a strong labor market imply that monetary policy will inevitably be behind the curve? Alternatively, should policymakers pay more attention to sector‐specific dislocations, or are there other indications of an economy approaching full employment that are timelier than an increase in inflation? Also, are there situations where the benefits of probing, regardless of the approach, outweigh some of the costs?

The prison population is comprised predominately of prime‐age men, and more than 400,000 state and federal prisoners were released in 2021. More than 70 percent of those released were under some sort of conditional release, such as probation. The formerly incarcerated and others with felony convictions face a host of challenges when attempting to gain employment; some jobs are formally closed to persons with criminal records, while others are effectively closed by hiring practices and other firm‐level policies. How prevalent are criminal histories among US labor force participants, and how do people with criminal histories compare to those without in terms of employment and earnings? Are firms more willing to hire people with criminal histories when the labor market is especially tight and workers are hard to find? And which public policies can best promote an appropriate reintegration of people with criminal histories into the workforce?

This panel will discuss the latest research measuring maximum employment in real time. Economists typically view the unemployment rate as a reliable summary statistic of broader labor market conditions and use an estimate of the equilibrium unemployment rate, or U*, to capture maximum employment. However, measuring U* in real time is challenging, and economists have historically appealed to noticeable ex post increases in inflation as indicating an economy at or beyond full employment. What are the benefits and drawbacks of such an approach? Are there alternative approaches to estimating U* in real time that can help overcome some of the measurement challenges? Can the recovery from the pandemic‐induced shutdowns, when the unemployment rate seemingly hit a floor near 3.5 percent, offer relevant insight into alternate labor market measures that may better capture maximum employment? Or are estimates of U* built from a bottom‐up approach drawing on demographic or other population and labor market characteristics that are more reliable and better suited to measuring maximum employment?