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It turns out, however, that MTO led to neighborhood change, but it did not lead to much schoolquality change. Parents who were offered assistance to move went from living in census tracts where 53 percent of residents were classified as low income to tracts where 37 percent were classified as low income (on average, and including those who did not move). Their children, however, were about as likely to end up at a charter or magnet school as those from the control group. The percentile rankings of children’s schools based on state exams were also similar between the control and experimental groups (about 25th, on average). DeLuca and Rosenblatt (2010) and Ferryman et al. (2008) discussed multiple reasons why little changed. Most children stayed in the same school district, where all schools within a district were of similar quality. Some stayed in the same school because parents believed that taking children away from friends and familiar places would be disruptive. In other cases, although children moved into census tracts with fewer low-income people, nearby public schools did not fare much better than the ones from which they came, because more affluent residents chose to send their children elsewhere. Parents also seemed to lack information that would have helped them better consider charter and magnet schools in the area. Jacob (2004) observed similar responses from households given housing vouchers to move from their units in a large project in Chicago.
208 Moving to Opportunity Moving Neighborhoods Versus Reforming Schools: A Canadian’s Perspective Overall, the MTO results suggest that policies to relocate low-income households from areas of highly concentrated poverty to areas of less concentrated poverty are likely to be ineffective, especially relative to costs, in improving education outcomes. Perhaps assistance relocating to much more affluent areas or much less segregated areas would be more successful, but such movement on a large scale is not possible without unrealistic financial cost, and it is not clear how many lowincome households would want to go. Parents from poor neighborhoods seem to focus on a desire to reduce exposure to crime and drug activity, but many also seem reluctant to move far from their current residence. Even if movement to more affluent or less segregated areas were possible, policymakers would want to consider the potential negative effects on households already living in these neighborhoods. I am not aware of any MTO research that has examined this possibility.
The tendency for voucher holders to move into neighborhoods where crime rates are increasing or school conditions are deteriorating complicates the investigation of potential negative externalities from providing vouchers (for example, Ellen, Lens, and O’Regan, 2011).
Another reason for caution about the potential effectiveness of mobility programs on improving educational outcomes is that low-income households move often. Even households from MTO’s control group moved, on average, more than twice over about 12 years, with less than 30 percent of the control group in public housing by the end of this period. As a consequence, differences in neighborhood quality between the experimental and control groups dissipated over time. This result may explain why initial effects on test score performance in two MTO sites (Chicago and Baltimore) died out over time (Burdick-Will et al., 2011). In general, more than one-half of lowincome households entering high-poverty neighborhoods leave within 3 years (Quillian, 2003).
Thus, the period during which households are exposed to high-poverty neighborhoods may not be long enough to produce significant influence, or individuals who receive assistance to move into more attractive neighborhoods may not stay for long.
As the final report notes, the MTO results do not imply that school quality never matters because the experiment had little effect on school quality. In fact, a growing body of evidence suggests impressive gains from attending charter schools, especially among minority students living in high-poverty areas (for example, Angrist, Pathak, and Walters, 2011). Winning a lottery to attend a charter school in Boston increased student achievement by about 0.2 standard deviations per year in English language arts and by about 0.4 standard deviations per year in math compared with achievement in traditional public schools. Lottery studies in New York City and Washington, D.C., showed similar gains. Angrist, Pathak, and Walters (2011) and Dobbie and Fryer (2011) concluded that these schools were effective because of an adherence to a “no excuses” approach to urban education, emphasizing instruction time, intensive tutoring, high expectations, and traditional math and reading skills.
Two other studies used exogenous refugee placement into different neighborhoods and different schools. Gould, Lavy, and Paserman (2004) examined Ethiopian children airlifted to Israel over 3 days and placed in absorption centers throughout the country in essentially random order.
Children who attended schools in wealthy and urban settings were substantially less likely to drop out of high school and more likely to pass a matriculation exam than were children assigned to less developed and smaller towns. The effects remained even after accounting for community characteristic differences, leading the authors to conclude that school-quality differences explained the
results. Gould, Lavy, and Paserman (2011) also concluded, from a study of Yemenite refugees, that children airlifted to Israel and placed in areas with more modern infrastructure were more likely to obtain post-secondary education.
Thus, rather than expend resources moving children away from high-poverty areas, facilitating greater access to better schools, preferably through public-school reform so that all children can take advantage of these potential gains, may be a more effective approach to improving long-run gains. Applying an evidence-based policy approach to improve schools also has the advantage of potentially benefiting all children. Moving at-risk youth to better neighborhoods, in contrast, could lead to negative outcomes for youth already living in these areas. To realize mental health gains found from MTO without mobility, perhaps continued revitalization of high-poverty neighborhoods into more mixed-income developments may help reduce crime and drug activity and, in turn, lower stress.
Even within high-poverty neighborhoods, the variance in long-run outcomes is high. In my study of children from Toronto public housing projects, some children ended up doing very well in terms of earnings by age 30, whereas others ended up earning almost nothing. Family differences, as measured by sibling outcome correlations, mattered a great deal, accounting for more than 30 percent of the earnings differences. Were we better able to understand what specific family factors lead some disadvantaged youth to rise above their circumstances, perhaps we could develop more effective tools to combat poverty. Until then, focusing on school reform seems to me the best bet.
Acknowledgments The author thanks Dionissi Aliprantis, Jens Ludwig, and Lisa Sanbonmatsu for stimulating discussion on this topic. All errors and opinions expressed in this article are my own.
Authors Philip Oreopoulos is a professor of economics at the University of Toronto and a research scholar at the Canadian Institute for Advanced Research.
References Angrist, Joshua D., Parag A. Pathak, and Christopher R. Walters. 2011. Explaining Charter School Effectiveness. NBER Working Paper No. 17332. Cambridge, MA: National Bureau of Economic Research.
Burdick-Will, Julia, Jens Ludwig, Stephen W. Raudenbush, Robert J. Sampson, Lisa Sanbonmatsu, and Patrick Sharkey. 2011. “Converging Evidence for Neighborhood Effects on Children’s Test Scores: An Experimental, Quasi-Experimental, and Observational Comparison.” In Whither Opportunity? Rising Inequality, Schools, and Children’s Life Chances, edited by Greg J. Duncan and Richard J.
Murnane. New York: Russell Sage Foundation: 255–276.
210 Moving to Opportunity Moving Neighborhoods Versus Reforming Schools: A Canadian’s Perspective Carrell, Scott, Ron Fullerton, and James E. West. 2009. “Does Your Cohort Matter? Measuring Peer Effects in College Achievement,” Journal of Labor Economics 27 (3): 439–464.
DeLuca, Stefanie, and Peter Rosenblatt. 2010. “Does Moving to Better Neighborhoods Lead to Better Schooling Opportunities? Parental School Choice in an Experimental Housing Voucher Program,” Teachers College Record 112 (5): 1443–1491.
Dobbie, Will, and Roland G. Fryer, Jr. 2011. Getting Beneath the Veil of Effective Schools: Evidence From New York City. NBER Working Paper No. 17632. Cambridge, MA: National Bureau of Economic Research.
Ellen, Ingrid Gould, Michael C. Lens, and Katherine O’Regan. 2011. “Memphis Murder Revisited:
Do Housing Vouchers Cause Crime?” U.S. Department of Housing and Urban Development Assisted Housing Research Cadre Report. Washington, DC: U.S. Department of Housing and Urban Development.
Ferryman, Kadija, Xavier de Souza Briggs, Susan J. Popkin, and María Rendón. 2008. Do Better Neighborhoods for MTO Families Mean Better Schools? Washington, DC: Urban Institute.
Friesen, Jane, and Brian Krauth. 2011. “Ethnic Enclaves in the Classroom,” Labour Economics 18 (5): 656–663.
Gould, Eric D., Victor Lavy, and M. Daniel Paserman. 2011. “Sixty Years After the Magic Carpet Ride: The Long-Run Effect of the Early Childhood Environment on Social and Economic Outcomes,” Review of Economic Studies 78 (3): 938–973.
———. 2004. “Immigrating to Opportunity: Estimating the Effect of School Quality Using a Natural Experiment on Ethiopians in Israel,” Quarterly Journal of Economics (May): 489–520.
Hoxby, Caroline. 2000. Peer Effects in the Classroom: Learning From Gender and Race Variation.
NBER Working Paper No. 7867. Cambridge, MA: National Bureau of Economic Research.
Jacob, Brian. 2004. “The Impact of Public Housing Demolitions on Student Achievement in Chicago,” American Economic Review 94 (1): 233–258.
Lavy, Victor, and Analia Schlosser. 2011. “Mechanisms and Impacts of Gender Peer Effects at School,” American Economic Journal: Applied Economics 3 (2): 1–33.
Oreopoulos, Philip. 2008. “Neighbourhood Effects in Canada: A Critique,” Canadian Public Policy 34 (2): 237–258.
———. 2003. “The Long-Run Consequences of Living in a Poor Neighborhood,” Quarterly Journal of Economics 118 (4): 1533–1575.
Quillian, Lincoln. 2003. “How Long Are Exposures to Poor Neighbourhoods? The Long-Term Dynamics of Entry and Exit From Poor Neighbourhoods,” Population Research and Policy Review 22: 221–249.
Sanbonmatsu, Lisa, Jens Ludwig, Larry F. Katz, Lisa A. Gennetian, Greg J. Duncan, Ronald C. Kessler, Emma Adam, Thomas W. McDade, and Stacy Tessler Lindau. 2011. Moving to Opportunity for Fair Housing Demonstration Program: Final Impacts Evaluation. Report prepared by the National Bureau of Economic Research for the U.S. Department of Housing and Urban Development, Office of Policy Development and Research. Washington, DC: U.S. Department of Housing and Urban Development, Office of Policy Development and Research.
Venkatesh, Sudhir Alladi. 2000. American Project: The Rise and Fall of a Modern Ghetto. Cambridge, MA: Harvard University Press.
212 Moving to Opportunity
MTO’s Contribution to a Virtuous Cycle of Policy Experimentation and Learning Margery Austin Turner Urban Institute When the Moving to Opportunity (MTO) for Fair Housing demonstration1 began in the mid-1990s, policymakers at the U.S. Department of Housing and Urban Development (HUD) were newly aware of the terrible damage inflicted on families and children living in severely distressed neighborhoods and the role federal housing policy played in concentrating and isolating poor (mostly minority) families in these neighborhoods. Findings from the Chicago Gautreaux experiment suggest that helping families escape from deeply poor neighborhoods and move to neighborhoods of opportunity might dramatically improve their well-being and life chances. At the time, however, few people (whether policymakers, practitioners, or scholars) saw HUD as a source of policy innovation or rigorous experimentation, and federal housing policy was an afterthought in most discussions about antipoverty strategies and welfare reform (Briggs, Popkin, and Goering, 2010).
Because reliable answers about what works in public policy are hard to find, labeling experiments like MTO as either “successes” or “failures” is tempting. Did the demonstration prove that using housing vouchers to relocate poor minority families works? If not, did it fail? In fact, MTO succeeded in ways no one anticipated when it was launched, generating valuable lessons and raising new questions about the effects of neighborhood distress and the potential role of assisted housing mobility. Findings to date have spurred successive rounds of policy innovation and research that test new hypotheses about how, where, and for whom neighborhoods matter and how both housing HUD randomly assigned residents of public and assisted housing projects who volunteered for the MTO demonstration to one of three groups. The experimental group received housing vouchers that, for the first year, families could use only in low-poverty neighborhoods, along with mobility counseling and search assistance. The Section 8 group received traditional housing vouchers that families could immediately use in any neighborhood. The control group continued to receive housing subsidies in the original development. Researchers have tracked MTO participants systematically over the intervening years to support analysis of long-term economic, educational, and health outcomes.