Objective: Quantify the effects of the COVID-19 pandemic on nursing home resident well-being. Design: Quantitative analysis of resident-level assessment data. Setting and participants: Long-stay residents living in Connecticut nursing homes. Methods: We used Minimum Data Set assessments to measure nursing home resident outcomes observed in each week between March and July 2020 for long-stay residents (eg, those in the nursing home for at least 100 days) who lived in a nursing home at the beginning of the pandemic. We compared outcomes to those observed at the beginning of the pandemic, controlling for both resident characteristics and patterns for outcomes observed in 2017-2019. Results: We found that nursing home resident outcomes worsened on a broad array of measures. The prevalence of depressive symptoms increased by 6 percentage points relative to before the pandemic in the beginning of Marchdrepresenting a 15% increase. The share of residents with unplanned substantial weight loss also increased by 6 percentage points relative to the beginning of Marchdrepresenting a 150% increase. We also found significant increases in episodes of incontinence (4 percentage points) and significant reductions in cognitive functioning. Our findings suggest that loneliness and isolation play an important role. Though unplanned substantial weight loss was greatest for those who contracted COVID-19 (about 10% of residents observed in each week), residents who did not contract COVID-19 also physically deteriorated (about 7.5% of residents in each week). Conclusions and Implications: These analyses show that the pandemic had substantial impacts on nursing home residents beyond what can be quantified by cases and deaths, adversely affecting the physical and emotional well-being of residents. Future policy changes to limit the spread of COVID-19 or other infectious disease outbreaks should consider any additional costs beyond the direct effects of morbidity and mortality due to COVID-19.

We find that experienced poker players typically change their style of play after winning or losing a big pot-most notably, playing less cautiously after a big loss, evidently hoping for lucky cards that will erase their loss. This finding is consistent with Kahneman and Tversky's break-even hypothesis and suggests that when investors incur a large loss, it might be time to take a vacation or be monitored closely.

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The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

This paper estimates the labor market effects of gaining eligibility for Supplemental Security Income (SSI) disability benefits during childhood. In theory, access to SSI could help children treat their disabilities, thus improving labor market outcomes in the long run. Alternatively, children who are designated as disabled may reduce their investment in human capital, which would harm future labor market outcomes. I identify the effects of qualifying for SSI benefits through a natural experiment-a Supreme Court decision eased the criteria to be considered disabled, especially for children with mental disorders. The policy change also occurred earlier in some people's lives than others. For individuals with a mental disorder, each additional year of exposure to eased standards during childhood increased their SSI receipt by 0.3 years and reduced cumulative labor market earnings through age 30 by $1,600. Importantly, this does not address the full range of outcomes that may be affected by receiving benefits. The author is grateful to Prashant Bharadwaj, Julie Cullen, Gordon Dahl, and Craig McIntosh for being so generous with their time and for many helpful discussions. I am extremely thankful to Jeffrey Hemmeter and John Jones at the Social Security Administration, who helped run programs and set me up with data access at SSA, and without whom this paper would not have been possible.