Bergman Flashcards
setting
Bergman and coauthors study the housing decisions of recipients of housing vouchers in Seattle
high-opportunity neighborhood
- Uses estimates of intergenerational mobility for each Census tract in the Seattle metro area from the Opportunity Atlas. The estimates of intergenerational mobility reveal the expected income rank of children who grow up in the neighborhood, conditional on having parents at the 25th percentile of the income distribution.
- These types of neighborhoods are identified by Census tracts as in the top third of neighborhoods in terms of intergenerational mobility. It categorizes these tracts as “high-opportunity” neighborhoods.
Preferences Explanation
low-income households prefer to live in low-opportunity
neighborhoods. Under this story, low-opportunity neighborhoods have certain desirable features that make them attractive to low-income households despite the fact that they are bad places for children grow up. For instance, a person may choose to live in a low-opportunity neighborhood if it is more affordable or if it allows close proximity to jobs, friends, and family.
Barriers Explanation
low-income households want to live in high-opportunity neighborhoods, but are prevented from doing so by barriers and frictions. For instance, low-income households may lack information on which neighborhoods are high-
opportunity. In addition, they may not be able to afford housing in high-opportunity areas, and landlords in these areas may not want to rent to them
Main question
The paper attempts to understand the relative contribution of preferences and barriers in explaining why low-income households live in low-opportunity areas. Moreover, it tries to learn about the types of barriers that are at fault. This way, policy can potentially be used to counteract them.
Sample & Observations
– The experiment focused on families in Seattle who received Housing Choice Vouchers (aka Section 8 vouchers) They are monetary payments from the government that a family can use to pay rent.
– the experiment dealt with families who received vouchers between April 2018 and April 2019. In addition, it focused only on families with a child below age 15. The sample included 430 families. These families were very poor, with a median household income of $19,000.
Treatment
– Families were randomly assigned to either the control group or the treatment group.
– Families in the control group had the normal experience with Section 8 vouchers. Families in the treatment group were given additional assistance in finding a place to live. This assistance came in different forms. First, the treated families were provided with information on which neighborhoods are high-opportunity.
– Second, they were given help with applying for units and dealing with landlords. Finally, they were given money (about
$1,000 per family) to cover security deposits and application fees. In total, the assistance
provided to the treatment group cost about $2,660 per family.
Potential outcomes
what a family’s outcomes would be under different values of the
treatment variable. In this setting, the treatment variable takes on two values, 0 or 1. Thus, there are two potential outcomes. A family’s potential outcome without the treatment is whether the family would choose to live in a high opportunity neighborhood on
their own, under the traditional Section 8 program. By contrast, a family’s potential outcome with the treatment is whether the family would choose to live in a high-opportunity neighborhood after receiving the additional assistance.
Individual Treatment Effect
the difference between potential outcomes for a particular family. It is the difference in where the family would live in the case in which the family gets the additional assistance versus the case in which the family doesn’t. Unfortunately, we can’t observe the individual treatment effect. This is due to the fundamental
problem of causal inference—i.e., we can see the family’s housing choice under only one state of the world.
Average treatment effect
the average of the individual treatment effects across a population. In this case, it is the average effect of receiving the additional assistance. Since the additional assistance is randomly assigned, we can observe the average treatment effect. It is the difference in the probability of living in a high-opportunity
neighborhood for the treatment group versus the control group
role of barriers
very large
families in the treatment group were 38 percentage points more likely to rent a unit in a high-opportunity neighborhood. Thus, the paper’s effort to remove barriers by providing information and assistance was successful in getting low-income families to live in better neighborhoods. In addition, the treatment had similar effects for different types of low-income families (e.g., immigrants v. non-immigrants, racial minorities v. white families, etc.). Thus, the results seem quite general
role of preferences
very large
In particular, only 53% of treated families chose to live in high-opportunity areas. The other 47% continued living in low opportunity areas, even despite the information and assistance
lifting barriers
an increase the share of low-income families who live in high-opportunity areas. However, this policy is unlikely to bring the share to 1. In addition, there are many questions about whether the policy can be scaled up. For instance, if many people start moving to high-opportunity neighborhoods, then these
neighborhoods may become unaffordable.