Chapter 9.6 · Offers, moves and policies

What moving can change

Randomized offers of housing vouchers, studies of children whose families moved at different ages, and a trial of help with the housing search find changes for particular families under particular conditions, from 15% to 53% of families moving to high-mobility areas in one trial, and none of them measures what the gradients in this book would become if places changed.

Author: Vishal Singh
Affiliation: NYU Stern
Published: 28 October 2026

Full report: every estimate with its interval, and every figure as a table.

DraftFigures and numbers may change as the analysis is rebuilt.what is still being checked

Draft. The chapter reports published estimates in words and borrowed facts; figures that redraw the studies' estimates with their intervals, and a study-level table, are planned.

In a randomized trial among families with children issued housing vouchers in Seattle and King County, 53% of the families offered information, short-term financial help and customized help with the housing search moved to a neighborhood with high upward mobility, against 15% of the families in the control group.[1] That result answers a question the rest of this book cannot. The earlier chapters compare places and the people who already live in them. They show where outcomes are higher or lower and how they move with deprivation, and they cannot say what would happen to a family that moved, or to a place that changed.

This chapter reports the studies the book cites whose designs separate what a place, or a change to it, does for a family from the selection of families into places. It groups them by what was changed: an offer of a voucher, the years a child spent in a place, help with the search for housing, a forced move, and a change to a place or an institution. Each study describes its own population and period, and none of the estimates is pooled with another or attached to a gradient in an earlier chapter.

Questions the designs answer

What was changed	Design	Question it can answer	What it cannot answer
An offer of a housing voucher	Randomized experiment (Moving to Opportunity)	What changed for the families offered the voucher, compared with families not offered it	What any move to any less poor neighborhood would do
The years a child spent in a place	Movers design, comparing children who moved at different ages	How much of the difference between places a child's outcome takes on per year of exposure	Which feature of a place produces the change
Help with the housing search	Randomized experiment (Creating Moves to Opportunity)	Whether assistance changes where families with vouchers move	What the moves do to children's adult outcomes, which the trial has not yet observed
A forced move from public housing	Comparison of children in demolished and nearby buildings that were not demolished	What a displacement out of public housing changed for children	What a voluntary move would change

A fifth group of studies changes a place or an institution rather than who lives there. Those studies are reported in the chapters on the outcomes they measure and are listed in the last section.

An offer of a voucher changed some outcomes for some members of the family

Causal evidenceRandomized housing-voucher experiment

Moving to Opportunity: adults' health and well-being and children's later income

From 1994 to 1998 the Department of Housing and Urban Development randomly assigned families in public housing in high-poverty tracts to a voucher usable only in a low-poverty tract, with counseling, to an unrestricted voucher, or to no voucher. Only 48% of the families offered the low-poverty voucher used it to move.

In a survey of the women in 2008 to 2010, the prevalence of a glycated hemoglobin level of 6.5% or more, a marker of diabetes, was 4.3 (95% CI 0.8 to 7.8) points lower in the group offered the low-poverty voucher than in the control group, and the prevalence of a body-mass index of 40 or more was 3.4 (95% CI 0.4 to 6.4) points lower.[2] A decade or more after assignment, the offer of a move raised a standardized answer to one question about how happy things are by 0.098 (95% CI 0.022 to 0.174) standard deviations, with no detectable change in the adults' economic self-sufficiency.[3]

The children's adult incomes depended on their age at the move. Children assigned the experimental voucher before age 13 had an annual income 14% higher in their mid-twenties than the control group, an intention-to-treat comparison that includes families who did not move. Scaled by take-up, the estimate for children of families who used the voucher is 31%. The estimated effects for children who were teenagers at the move were negative.[4]

The estimates compare groups by the offer they received, and the offer went to volunteers living in public housing in the poorest tracts of large cities. They describe what an offer did for those families. They do not give the change that a move along the full range of the deprivation index would produce, and none of the studies measured life expectancy.

A child's adult income moves toward the destination's with each year spent there

Causal evidenceMovers design

Childhood exposure to a place and adult income

Chetty and Hendren compared children whose families moved between areas when the children were at different ages, including siblings in the same family. The identifying assumption is that the selection that sends a family to a better or worse place does not vary with the child's age at the move, which they test with sibling comparisons, controls for changes in parental income and marital status, and moves that followed displacement shocks. Children's adult income ranks move toward those of children of permanent residents of the destination by 0.04 percentile for each year of childhood spent there and each percentile by which the destination's ranks are higher.[5] A companion paper estimates the causal contribution of each county.[6]

The Opportunity Atlas authors combine the experimental and movers estimates and report that 60% of the variation in outcomes across neighborhoods is driven by causal effects of the neighborhoods.[7]

The design estimates how much of a place's difference a child takes on, and its benchmark is the children of permanent residents at the same parent income. It does not say which feature of a place, its schools, its neighbors, its jobs or its safety, carries the effect, and the share attributed to causal effects belongs to the Atlas outcome and sample, not to the outcomes of other chapters.

Help with the housing search changed where families moved

Causal evidenceRandomized controlled trial

Creating Moves to Opportunity: assistance with the housing search

Bergman and coauthors randomly assigned families with children issued housing vouchers in Seattle and King County to the usual voucher process or to a program that combined information about high-opportunity neighborhoods, short-term financial assistance, customized help with the search and connections to landlords. The program raised the share of families who moved to a high-upward-mobility area from 15% to 53%, and a second trial attributes most of the effect to the customized search assistance. The authors conclude that many low-income families do not strongly prefer low-mobility areas, and that barriers in the search for housing add to the segregation of families by income.[1]

The trial measures where families moved, not how their children fare as adults. Whether the moves change the children's outcomes is a question for the movers design and for later follow-up.

A forced move out of public housing

The families did not choose to move, so the comparison avoids the selection of volunteers in a voucher experiment. It describes one city's public housing in one period, and the change bundles a new neighborhood with the loss of the old building and its community.

Changes to places and institutions

Moving a family and changing a place are different interventions. Several chapters report designs that study a change to a place or to an institution, each beside the outcome it measures.

Chapter	What changed	Design
Chapter 8.1, Gun homicide and the causes of early death	Remediation of vacant lots	Cluster randomized trial
Chapter 4.2, Teen births	Access to long-acting contraception	Difference-in-differences
Chapter 2.3, Smoking in pregnancy	Cigarette taxes and state income support	Matched comparison states; difference-in-differences
Chapter 2.1, Birthweight and preterm birth	Income support and Medicaid eligibility	Difference-in-differences; simulated eligibility
Chapter 3.1, Test scores, class and race	Head Start funding and school finance reforms	Regression discontinuity; event study
Chapter 7.1, Health behaviors and the supply of care	Insurance coverage and community health centers	Randomized lottery; difference-in-differences
Chapter 8.2, Overdose, alcohol and suicide	Naloxone access laws	Staggered difference-in-differences
Chapter 5.2, Home value, income and redlining	The grading of neighborhoods on the HOLC maps	Boundary design
Chapter 6.1, Air pollution	Redlining and traffic near the home	Boundary design; difference-in-differences
Chapter 5.4, Renting, affordability and eviction	An eviction order	Random assignment of cases to judges
Chapter 3.4, School discipline and incarceration	Suspension and juvenile incarceration	Boundary change; random assignment of cases to judges
Chapter 7.4, Disability, retirement and Medicare	Medicare eligibility, disability allowance and Social Security benefits	Regression discontinuity; examiner assignment; difference-in-differences

Each study estimates what one policy or decision changed for the population it reached. None estimates how much a gradient across places would narrow if the policy were applied everywhere, and the estimates are not comparable with one another, since their outcomes, units and populations differ. The index of studies lists every study box in the book with its design, population and outcome.

What these data cannot show

The studies estimate effects for volunteers in public housing, for children whose families moved, for families issued vouchers in one metro area and for children displaced in one city, in the periods they cover. None follows the populations the earlier chapters compare. An effect of an offer is not an effect of a move, and an effect of a move is not an effect of changing the place a family left. The movers design identifies how much a child's outcome follows a place, not which feature of the place is responsible. No study here gives the share of any gradient in this book that a policy could remove, and the book reports none.

Data sources

Published estimates from cited studiesEstimates reported in the cited studies, most of them copied from the chapters that first report themYears: as reported in each study · Weights: as reported in each study · License: Quoted from published research for commentary
Opportunity AtlasThe share of variation across neighborhoods attributed to causal effects, as reported by the Opportunity Atlas authors and in Race, income and mobilityYears: 1978-1983 birth cohorts (2018 release) · Weights: as reported · License: Public use (Opportunity Insights and the U.S. Census Bureau)

All data sources

Methods

This chapter computes nothing. It reports studies whose designs assign an offer by lottery or compare children who moved at different ages, and every estimate describes the study's population and period, not the places compared elsewhere in the book.

Where the numbers come from

The Moving to Opportunity health and income estimates are copied from Place and the length of a life, the well-being estimate from Life evaluation and daily feelings, the exposure rate of the movers design from Eight types of neighborhood, and the Opportunity Atlas share from Race, income and mobility, with their populations, periods and intervals.

The move rates of the Creating Moves to Opportunity trial are copied from the abstract of Bergman and coauthors (2024). The study of Chicago public housing demolitions is reported in words, from the abstract of Chyn (2018).

Offers, moves and scaling

An intention-to-treat estimate compares groups by the offer they were randomized to, including families who did not move. A treatment-on-the-treated estimate divides it by the share that took up the offer, which assumes the offer changed nothing for families who did not use it. The chapter names which estimate each number is.

References

Bergman, Peter; Chetty, Raj; DeLuca, Stefanie; Hendren, Nathaniel; Katz, Lawrence F.; Palmer, Christopher (2024). Creating Moves to Opportunity: Experimental Evidence on Barriers to Neighborhood Choice. American Economic Review 114(5): 1281-1337. doi:10.1257/aer.20200407
Ludwig, Jens; Sanbonmatsu, Lisa; Gennetian, Lisa; Adam, Emma; Duncan, Greg J.; Katz, Lawrence F.; Kessler, Ronald C.; Kling, Jeffrey R.; Lindau, Stacy Tessler; Whitaker, Robert C.; McDade, Thomas W. (2011). Neighborhoods, Obesity, and Diabetes: A Randomized Social Experiment. New England Journal of Medicine 365(16): 1509-1519. doi:10.1056/NEJMsa1103216
Ludwig, Jens; Duncan, Greg J.; Gennetian, Lisa A.; Katz, Lawrence F.; Kessler, Ronald C.; Kling, Jeffrey R.; Sanbonmatsu, Lisa (2012). Neighborhood effects on the long-term well-being of low-income adults. Science 337(6101): 1505-1510. doi:10.1126/science.1224648
Chetty, Raj; Hendren, Nathaniel; Katz, Lawrence F. (2016). The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment. American Economic Review 106(4): 855-902. doi:10.1257/aer.20150572
Chetty, Raj; Hendren, Nathaniel (2018). The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects. The Quarterly Journal of Economics 133(3): 1107-1162. doi:10.1093/qje/qjy007
Chetty, Raj; Hendren, Nathaniel (2018). The Impacts of Neighborhoods on Intergenerational Mobility II: County-Level Estimates. The Quarterly Journal of Economics 133(3): 1163-1228. doi:10.1093/qje/qjy006
Chetty, Raj; Friedman, John N.; Hendren, Nathaniel; Jones, Maggie R.; Porter, Sonya R. (2018). The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility. NBER Working Paper 25147. doi:10.3386/w25147
Chyn, Eric (2018). Moved to Opportunity: The Long-Run Effects of Public Housing Demolition on Children. American Economic Review 108(10): 3028-3056. doi:10.1257/aer.20161352

How to cite

@misc{singh2026whatmovingcanchange,
  author = {Singh, Vishal},
  title = {What moving can change},
  year = {2026},
  url = {https://vishalsingh.org/zipcode/what-moving-can-change},
  note = {In ZIP Code Destiny. Published 28 October 2026.}
}