Amanda M Michaud

We provide fresh evidence that labor supply is broadly counter-cyclical. Employed and laid-off workers both increase labor market attachment when unemployment is high. A workhorse search model is used to frame how these facts add nuance to our understanding of business cycles and of labor supply fundamentals: how many workers are near the margin of participation and what drives their choices? Additional results explore regularities of these patterns across cyclical episodes and in the cross section of workers. Additional microeconomic data that suggest income effects contribute to increased labor supply in recessions but are unlikely to be the complete story.

There is substantial variation in Social Security Disability Insurance (DI) across the United States, with DI beneficiaries accounting from less than one percent to more than one-fifth of a county's working-age residents. We combine county-level data on DI applications and awards with measures of labor market characteristics, living costs and population health to model the geographic dispersion of DI. We find that local differences in health and income levels are about equally important in determining geographic differences, with living-cost differences also playing an important role. The DI program redistributes across space, delivering ex ante welfare gains to residents counties at the 90th percentile in terms of DI receipt that are more than twice as large as in counties at the 10th percentile. The place-based effects of DI are larger than most public policy initiatives specifically designed to support local economic activity. NBER SI 2023 Slides

We characterize the little wage information contained in online job posts. Wage information is rare: only 14% of posts contain any information. Of these, wage ranges are more common than point wages, and are wide on average, spanning 28% of the midpoint (e.g. $32,000-$42,000/yr). Posted wages are highly selected in low income occupations: 40% higher than wages of employed workers. High wage firms are more opaque, with more and wider ranges. We find zero correlation between wage information and local labor market tightness. We provide an example of bias in econometric inference that worsens as wage information falls.

As married women's labor force participation has increased in the United States, the cyclical volatility of their employment has also increased. We provide a unified theory that can reconcile these facts. Lower volatility of married women's employment over the business cycle is driven by counter-cyclical motives to remain in the labor force to provide insurance against their spouse's income risk. Changes in fundamentals that increase attachment subsequently lower the ability of wives to adjust labor supply to provide insurance in recessions-- they are more likely to have permanently high labor supply anyway. The model predicts that some forces driving the growth in female participation-- increasing returns to tenure and decreasing fixed cost of work-- increase attachment and cyclical volatility. The closing gender wage gap, by contrast, reduces both. A quantitative evaluation predicts that the former two forces have dominated in the United States with some ebbing for recent cohorts. Microeconomic evidence support both this prediction and the specific mechanism of precautionary spousal labor supply. Implications for welfare and intra-household insurance are discussed.

This paper develops a quantitative framework to study the impact of Unemployment Insurance (UI) expansions to workers earning below eligibility thresholds. A model of how UI affects welfare and labor supply is developed and calibrated with microeconomic data, including consumption. The model predicts that the current ineligible would choose to stay on UI longer than the current eligible and the margins of why this is the case are quantified. The model is applied to the Great Recession by identifying ineligible workers in the data using machine learning and to an actual expansion during COVID-19 using administrative data. The UI duration for newly eligible under the expansion was 1.7 times longer than the previous eligible but is one-third shorter than the model's economic incentives predict. This suggests caution in extrapolating from the COVID-19 data and the model is used to predict impacts of smaller scale expansions during non-pandemic times.

In recent decades, Social Security Disability Insurance (SSDI) claims have risen rapidly. We evaluate the importance of changing macroeconomic conditions in shaping this trend. Our quantitative framework considers that economic conditions interact with individuals' health status in their decisions to apply for SSDI. Crucially, these factors are correlated through the nature of work: multiple sectors differentially expose workers to health and economic risks. Decomposing factors driving SSDI growth in a calibrated model, we find the secular deterioration of economic conditions concentrated in populations with high health risks accounts for about half of the increase in SSDI claims predicted by the model, about a third overall.

We argue that dynamics play a critical role in the evaluation of punitive incarceration reform on crime, inequality and the Macroeconomy. Individuals' past choices related to crime and employment under old policies have persistent consequences that limit their contemporaneous responses to future policy changes. Novel cohort evidence is provided in support of this mechanism. A quantitative model of this theory generates nuanced, non-monotone dynamics of crime and incarceration similar to the U.S. experience following a single permanent increase in punitive incarceration in the 1980s. Increased inequality and declining employment accompany these changes and are borne unequally across generations.

A large literature shows workers who are involuntarily separated experience wage scars: their hourly earnings fall initially by an average of 15.4% and remain much lower than their non-separated counterparts more than 20 years later. We find that this reduces average life-cycle wage growth by 14.7% and increases cross-sectional wage dispersion by 17.8%. We research variants of human capital theory capable of replicating scars, highlighting a tension in producing large, persistent wage scars alongside average life-cycle wage dynamics. An examination of labor market and demographic characteristics of workers who never recover suggests many theories of wage scars are operational, but on different groups of workers.

Living in a married household typically mitigates income risk. Is this true during a pandemic? On the one hand, the presence of two potential earners reduces the household income risk associated with a cut in hours, job loss, or a stay at home order. On the other, married couples are more likely to have children to care for during a stay at home order and larger households are more likely to have a member with a health condition that makes them vulnerable to severe illness if they contract the virus. Using a structural model of labor supply, we measure how these factors affect the welfare outcomes of different household types and the aggregate dynamics of employment in response to the COVID-19 pandemic.