The Dynamics of the Racial Wealth Gap
We reconcile the large and persistent racial wealth gap with the smaller racial earnings gap, using a general equilibrium heterogeneous-agents model that matches racial differences in earnings, wealth, bequests, and returns to savings. Given initial racial wealth inequality in 1962, our model attributes the slow convergence of the racial wealth gap primarily to earnings, with much smaller roles for bequests or returns to savings. Cross-sectional regressions of wealth on earnings using simulated data produce the same racial gap documented in the literature. One-time wealth transfers have only ...
Assessing the Evidence on Neighborhood Effects from Moving to Opportunity
The Moving to Opportunity (MTO) experiment randomly assigned housing vouchers that could be used in low-poverty neighborhoods. Consistent with the literature, I find that receiving an MTO voucher had no effect on outcomes like earnings, employment, and test scores. However, after studying the assumptions identifying neighborhood effects with MTO data, this paper reaches a very different interpretation of these results than found in the literature. I first specify a model in which the absence of effects from the MTO program implies an absence of neighborhood effects. I present theory and ...
What Is Behind the Persistence of the Racial Wealth Gap?
Most studies of the persistent gap in wealth between whites and blacks have investigated the large gap in income earned by the two groups. Those studies generally concluded that the wealth gap was ?too big? to be explained by differences in income. We study the issue using a different approach, capturing the dynamics of wealth accumulation over time. We find that the income gap is the primary driver behind the wealth gap and that it is large enough to explain the persistent difference in wealth accumulation. The key policy implication of our work is that policies designed to speed the closing ...
Neighborhood Poverty and Quality in the Moving to Opportunity Experiment
Researchers suspect that some of the disparities that exist in such outcomes as health, employment, and education might be attributable to inequality of opportunity as determined by neighborhood environments. We study census data to identify neighborhood characteristics in addition to poverty that might help to explain these disparities. We focus on the Moving to Opportunity housing-relocation experiment and show that because program participants typically moved from one predominately black neighborhood to another, their new low-poverty neighborhoods may have provided little to no change in ...
A distinction between causal effects in structural and rubin causal models
Structural Causal Models define causal effects in terms of a single Data Generating Process (DGP), and the Rubin Causal Model defines causal effects in terms of a model that can represent counterfactuals from many DGPs. Under these different definitions, notationally similar causal effects make distinct claims about the results of interventions to the system under investigation: Structural equations imply conditional independencies in the data that potential outcomes do not. One implication is that the DAG of a Rubin Causal Model is different from the DAG of a Structural Causal Model. Another ...
Landlords and Access to Opportunity
Landlords in high-opportunity neighborhoods screen out tenants using vouchers. In our correspondence experiment, signaling voucher status cuts landlord responses in half. This voucher penalty increases with posted rent and varies little with signals of tenant quality and race. We repeat the experiment after a policy change and test how landlords respond to raising voucher payment limits by $450 per month in high-rent neighborhoods. Most landlords do not change their screening behavior; those who do respond are few and operate at small scale. Our results suggest a successful, systematic policy ...
What Determines the Success of Housing Mobility Programs?
There is currently interest in crafting public housing policy that combats, rather than contributes to, the residential segregation in American cities. One such policy is the Housing Mobility Program (HMP), which aims to help people move from disinvested neighborhoods to ones with more opportunities. This paper studies how design features influence the success of HMPs in reducing racial segregation. We find that the choice of neighborhood opportunity index used to define the opportunity areas to which participants are encouraged to move has limited influence on HMP success. In contrast, we ...
Measuring Deaths from COVID-19
Medical data are new to the analyses and deliberations of Federal Reserve monetary policymakers, but such data are now of primary importance to policymakers who need to understand the virus’s trajectory to assess economic conditions and address the virus’s impacts on the economy. The number of deaths caused by COVID-19 is one key metric that is often referred to, but as with other COVID metrics, it is a challenge to measure accurately. We discuss the issues involved in measuring COVID-19 deaths and argue that the change in the number of directly observed COVID-19 deaths is the most ...
Local average neighborhood effects from moving to opportunity
This paper estimates Local Average Treatment Effects (LATEs) of neighborhood quality from the Moving to Opportunity (MTO) housing mobility experiment in a generalized model with multiple treatment levels. We propose a new approach to identifying parameters that exploits the identification of unobservables in the multi-level model. The variation in neighborhood quality induced by MTO only allows us to identify LATEs of moving from the first to the second decile of the national distribution of quality, but in other applications the approach may allow for the estimation of Marginal Treatment ...
Although the U.S. poverty rate was the same in 2000 as it was in 1970, the geographic distribution of the poor has become more concentrated. A higher concentration of poor in poor neighborhoods is a concern because it may mean the poor are exposed to fewer opportunities that affect their outcomes in life, like employment and income. We show where and how poverty has become more concentrated in the United States, and who is most likely to be affected.