Using two strategies, we show that consumers underreact to taxes that are not salient. First, using a field experiment in a grocery store, we find that posting tax-inclusive price tags reduces demand by 8 percent. Second, increases in taxes included in posted prices reduce alcohol consumption more than increases in taxes applied at the register. We develop a theoretical framework for applied welfare analysis that accommodates salience effects and other optimization failures. The simple formulas we derive imply that the economic incidence of a tax depends on its statutory incidence, and that even policies that induce no change in behavior can create efficiency losses. (JEL C93, D12, H25, H71)

Abstract We use administrative records on the incomes of more than 40 million children and their parents to describe three features of intergenerational mobility in the United States. First, we characterize the joint distribution of parent and child income at the national level. The conditional expectation of child income given parent income is linear in percentile ranks. On average, a 10 percentile increase in parent income is associated with a 3.4 percentile increase in a child’s income. Second, intergenerational mobility varies substantially across areas within the United States. For example, the probability that a child reaches the top quintile of the national income distribution starting from a family in the bottom quintile is 4.4% in Charlotte but 12.9% in San Jose. Third, we explore the factors correlated with upward mobility. High mobility areas have (i) less residential segregation, (ii) less income inequality, (iii) better primary schools, (iv) greater social capital, and (v) greater family stability. Although our descriptive analysis does not identify the causal mechanisms that determine upward mobility, the publicly available statistics on intergenerational mobility developed here can facilitate research on such mechanisms.

The Moving to Opportunity (MTO) experiment offered randomly selected families housing vouchers to move from high-poverty housing projects to lower-poverty neighborhoods. We analyze MTO's impacts on children's long-term outcomes using tax data. We find that moving to a lower-poverty neighborhood when young (before age 13) increases college attendance and earnings and reduces single parenthood rates. Moving as an adolescent has slightly negative impacts, perhaps because of disruption effects. The decline in the gains from moving with the age when children move suggests that the duration of exposure to better environments during childhood is an important determinant of children’s long-term outcomes.

We evaluate whether state-of-the-art macro models featuring indivisible labor are consistent with modern quasi-experimental micro evidence by synthesizing evidence on both the intensive and extensive margins. We find that micro estimates are consistent with macro estimates of the steady-state (Hicksian) elasticities relevant for cross-country comparisons on both the extensive and intensive margins. However, micro estimates of intertemporal substitution (Frisch) elasticities are an order of magnitude smaller than the values needed to explain business cycle fluctuations in aggregate hours by preferences. The key puzzle to be resolved is why micro and macro estimates of the Frisch extensive margin elasticity are so different.

We characterize the factors that determine who becomes an inventor in the United States, focusing on the role of inventive ability (“nature”) versus environment (“nurture”). Using deidentified data on 1.2 million inventors from patent records linked to tax records, we first show that children's chances of becoming inventors vary sharply with characteristics at birth, such as their race, gender, and parents' socioeconomic class. For example, children from high-income (top 1%) families are 10 times as likely to become inventors as those from below-median income families. These gaps persist even among children with similar math test scores in early childhood-which are highly predictive of innovation rates-suggesting that the gaps may be driven by differences in environment rather than abilities to innovate. We directly establish the importance of environment by showing that exposure to innovation during childhood has significant causal effects on children's propensities to invent. Children whose families move to a high-innovation area when they are young are more likely to become inventors. These exposure effects are technology class and gender specific. Children who grow up in a neighborhood or family with a high innovation rate in a specific technology class are more likely to patent in exactly the same class. Girls are more likely to invent in a particular class if they grow up in an area with more women (but not men) who invent in that class. These gender- and technology class-specific exposure effects are more likely to be driven by narrow mechanisms, such as role-model or network effects, than factors that only affect general human capital accumulation, such as the quality of schools. Consistent with the importance of exposure effects in career selection, women and disadvantaged youth are as underrepresented among high-impact inventors as they are among inventors as a whole. These findings suggest that there are many “lost Einsteins”-individuals who would have had highly impactful inventions had they been exposed to innovation in childhood-especially among women, minorities, and children from low-income families.

We present new evidence on trends in intergenerational mobility in the United States using administrative earnings records. We find that percentile rank-based measures of intergenerational mobility have remained extremely stable for the 1971-1993 birth cohorts. For children born between 1971 and 1986, we measure intergenerational mobility based on the correlation between parent and child income percentile ranks. For more recent cohorts, we measure mobility as the correlation between a child's probability of attending college and her parents' income rank. We also calculate transition probabilities, such as a child's chances of reaching the top quintile of the income distribution starting from the bottom quintile. Based on all of these measures, we find that children entering the labor market today have the same chances of moving up in the income distribution (relative to their parents) as children born in the 1970s. However, because inequality has risen, the consequences of the “birth lottery” - the parents to whom a child is born - are larger today than in the past.

The Spike at Benefit Exhaustion: Leaving the Unemployment System or Starting a New Job? by David Card, Raj Chetty and Andrea Weber. Published in volume 97, issue 2, pages 113-118 of American Economic Review, May 2007

Abstract A common challenge in estimating the impact of interventions (e.g. job training programmes, educational programmes) is that many outcomes of interest (e.g. lifetime earnings or other labour market outcomes) are observed with a long delay. In biomedical settings, this is often addressed by using short-term outcomes as so-called “surrogates” for the outcome of interest, e.g. tumour size as a surrogate for mortality in cancer studies. We build on this literature by combining multiple, possibly qualitatively distinct, short-term outcomes (e.g. short-run earnings and employment indicators) systematically into a “surrogate index”. Under the Prentice surrogacy assumption, which requires that the primary outcome is independent of the treatment conditional on the surrogates, we show that the average treatment effect on the surrogate index equals the treatment effect on the long-term outcome. We also relate the surrogacy assumption to a set of structural, causal assumptions. We then characterize the bias that arises from violations of each of the key assumptions, and we provide simple methods to validate these assumptions using additional observed outcomes. We apply our method to analyse the long-term impacts of a multi-site job training experiment in California. Rather than waiting a full 9 years to directly observe the long-term impact, we show that it is possible to use short-term (the first six quarters) outcomes as surrogates. Given the surrogacy assumption one could have estimated the programme’s long-term impacts on mean employment rates using the employment rates observed in the first six quarters, with a 35% reduction in standard errors relative to a simple difference in means estimator based on all 9 years of data.

Abstract Using 41 million observations on savings for the population of Denmark, we show that the effects of retirement savings policies on wealth accumulation depend on whether they change savings rates by active or passive choice. Subsidies for retirement accounts, which rely on individuals to take an action to raise savings, primarily induce individuals to shift assets from taxable accounts to retirement accounts. We estimate that each $1 of government expenditure on subsidies increases total saving by only 1 cent. In contrast, policies that raise retirement contributions if individuals take no action—such as automatic employer contributions to retirement accounts—increase wealth accumulation substantially. We estimate that approximately 15% of individuals are “active savers” who respond to tax subsidies primarily by shifting assets across accounts; 85% of individuals are “passive savers” who are unresponsive to subsidies but are instead heavily influenced by automatic contributions made on their behalf. Active savers tend to be wealthier and more financially sophisticated. We conclude that automatic contributions are more effective at increasing savings rates than subsidies for three reasons: (i) subsidies induce relatively few individuals to respond, (ii) they generate substantial crowd-out conditional on response, and (iii) they do not increase the savings of passive individuals, who are least prepared for retirement.

We show that differences in childhood environments shape gender gaps in adulthood by documenting three facts using population tax records for children born in the 1980s. First, gender gaps in employment rates, earnings, and college attendance vary substantially across the parental income distribution. Notably, the traditional gender gap in employment rates is reversed for children growing up in poor families: boys in families in the bottom quintile of the income distribution are less likely to work than girls. Second, these gender gaps vary substantially across counties and commuting zones in which children grow up. The degree of variation in outcomes across places is largest for boys growing up in poor, single-parent families. Third, the spatial variation in gender gaps is highly correlated with proxies for neighborhood disadvantage. Low-income boys who grow up in high-poverty, high-minority areas work significantly less than girls. These areas also have higher rates of crime, suggesting that boys growing up in concentrated poverty substitute from formal employment to crime. Together, these findings demonstrate that gender gaps in adulthood have roots in childhood, perhaps because childhood disadvantage is especially harmful for boys.