No abstract

The Affordable Care Act (ACA) aimed to achieve nearly universal health insurance coverage in the United States through a combination of insurance market reforms, mandates, subsidies, health insurance exchanges, and Medicaid expansions, most of which took effect in 2014. This paper estimates the causal effects of the ACA on health insurance coverage in 2014 using data from the American Community Survey. We utilize difference-in-difference-in-differences models that exploit cross-sectional variation in the intensity of treatment arising from state participation in the Medicaid expansion and local area pre-ACA uninsured rates. This strategy allows us to identify the effects of the ACA in both Medicaid expansion and non-expansion states. Our preferred specification suggests that, at the average pre-treatment uninsured rate, the full ACA increased the proportion of residents with insurance by 5.9 percentage points compared to 2.8 percentage points in states that did not expand Medicaid. Private insurance expansions from the ACA were due to increases in both employer-provided and non-group coverage. The coverage gains from the full ACA were largest for those without a college degree, non-whites, young adults, unmarried individuals, and those without children in the home. We find no evidence that the Medicaid expansion crowded out private coverage.

I assess the impact of losing public health insurance on the labor market decisions of women by examining a series of Medicaid eligibility expansions targeted toward young children. These targeted expansions severed the historical tie between AFDC and Medicaid eligibility. The reforms allowed a mother's earnings to increase without affecting her young children's public health insurance. Increasing the income limit for Medicaid resulted in a decrease in AFDC participation and an increase in labor force participation among these women. The effects were large for ever-married women, but were negligible for never-married women.

State and local governments imposed social distancing measures in March and April of 2020 to contain the spread of novel coronavirus disease 2019 (COVID-19). These included large event bans, school closures, closures of entertainment venues, gyms, bars, and restaurant dining areas, and shelter-in-place orders (SIPOs). We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020 and April 27, 2020. An event-study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate by 5.4 percentage points after 1-5 days, 6.8 after 6-10 days, 8.2 after 11-15 days, and 9.1 after 16-20 days. Holding the amount of voluntary social distancing constant, these results imply 10 times greater spread by April 27 without SIPOs (10 million cases) and more than 35 times greater spread without any of the four measures (35 million). Our paper illustrates the potential danger of exponential spread in the absence of interventions, providing relevant information to strategies for restarting economic activity.

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One goal of federal housing policy is to improve the prospects of children in poor families. But little research has been conducted into the effects on children of participation in housing programs, perhaps because it is difficult to find data sets with information about both participation and interesting outcome measures. This paper combines data from several sources to provide a first look at the effects of participation in public housing projects on housing quality and on the educational attainment of children. We first use administrative data from the Department of Housing and Urban Development to impute the probability that a Census household lives in a public housing project. We find that a higher probability of living in a project is associated with poorer outcomes. We then use a two-sample instrumental variables (TSIV) technique to combine information on the probability of living in a project, obtained from the 1990 to 1995 Current Population Surveys, with information on outcomes obtained from the 1990 Census. The instrument common to both samples is an indicator equal to one if the household is entitled to a larger housing project unit because of the sex composition of the children in the household. Families entitled to a larger unit because of sex composition are 24 percent more likely to live in projects. When we control for omitted variables bias using TSIV, we find that project households are less likely to suffer from overcrowding and less likely to live in high-density complexes. Project children are also 12 to 17 percentage points less likely to have been held back in school one or more grades, although this effect is confined to boys. Thus, most families do not face a tradeoff between housing quality and child outcomes-the average project improves both. There are other reasons for the shift in the composition of public housing from projects to vouchers. 1 Apgar (1990) and Olsen (1983) point out that it is typically cheaper to house a family in existing housing than to construct new housing, so that more families can be served for the same budget outlay. Olsen (1983) and Olsen and Barton (1983) also argue that in addition to being more efficient, an entitlement program of housing allowances would be more equitable than the current system in which some households receive benefits and other similar households do not. Finally, programs using existing housing do not crowd out private construction of low-rent housing as public construction projects might (Murray, 1983).

One goal of federal housing policy is to improve the prospects of children in poor families. But little research has been conducted into the effects on children of participation in housing programs, perhaps because it is difficult to find data sets with information about both participation and interesting outcome measures. This paper combines data from several sources to provide a first look at the effects of participation in public housing projects on housing quality and on the educational attainment of children.We first use administrative data from the Department of Housing and Urban Development to impute the probability that a Census household lives in a public housing project. We find that a higher probability of living in a project is associated with poorer outcomes. We then use a two-sample instrumental variables (TSIV) technique to combine information on the probability of living in a project, obtained from the 1990 to 1995 Current Population Surveys, with information on outcomes obtained from the 1990 Census. The instrument common to both samples is an indicator equal to one if the household is entitled to a larger housing project unit because of the sex composition of the children in the household. Families entitled to a larger unit because of sex composition are 24 percent more likely to live in projects. When we control for omitted variables bias using TSIV, we find that project households are less likely to suffer from overcrowding and less likely to live in high-density complexes. Project children are also 12 to 17 percentage points less likely to have been held back in school one or more grades, although this effect is confined to boys. Thus, most families do not face a tradeoff between housing quality and child outcomes-the average project improves both.There are other reasons for the shift in the composition of public housing from projects to vouchers.

The anonymity of Bitcoin prevents analysis of its users. We collect Google Trends data to examine determinants of interest in Bitcoin. Based on anecdotal evidence regarding Bitcoin users, we construct proxies for four possible clientele: computer programming enthusiasts, 10 speculative investors, Libertarians © and criminals. Computer programming and illegal activity search terms are positively correlated with Bitcoin interest, while Libertarian and investment terms are not.