«A Journal of Policy Development and Research HoPe VI Volume 12, Number 1 • 2010 U.S. Department of Housing and Urban Development Office of Policy ...»
Washington (continued) Bob Moore Development Corporation of Columbia Heights Oramenta Newsome Washington, DC LISC William Pittman DCHA Laurie Putscher DCHA Chris Smith William C. Smith Company Bernie Tetrault DCHA Acknowledgments The authors thank Deb Gross of the Council of Large Public Housing Authorities for her considerable work in helping to frame the study and collect information. They also thank Michael Mariano of Econsult Corporation for his invaluable assistance in data collection and modeling.
Authors Sean Zielenbach is a senior consultant at the Woodstock Institute.
Richard Voith is a senior vice president and principal at Econsult Corporation.
References Bair, Edward, and John M. Fitzgerald. 2005. “Hedonic Estimation and Policy Significance of the Impact of HOPE VI on Neighborhood Property Values,” Review of Policy Research 22: 771–786.
Dance, Betsy. 1993. “1 BR, Lrg Rats, Bg $$,” The Washington Post, October 31: C1.
Ding, Chengri, Robert Simons, and Esmail Baku. 2000. “The Effect of Residential Investment on Nearby Property Values: Evidence from Cleveland, Ohio,” Journal of Real Estate Research 19: 23–48.
Fukuyama, Francis. 1995. Trust: The Social Virtues and the Creation of Prosperity. New York: Free Press.
Galster, George C., Peter Tatian, and John Accordino. 2006. “Targeting Investments for Neighborhood Revitalization,” Journal of the American Planning Association 72: 457–474.
Galster, George C., Peter Tatian, and Robin Smith. 1999. “The Impact of Neighbors Who Use Section 8 Certificates on Property Values,” Housing Policy Debate 10: 879–917.
Goetz, Edward G., Hin Kin Lam, and Anne Heitlinger. 1996. There Goes the Neighborhood?
Subsidized Housing in Urban Neighborhoods. Minneapolis, MN: University of Minnesota, Center for Urban and Regional Affairs.
Joseph, Mark. 2006. “Is Mixed-Income Development an Antidote to Urban Poverty?” Housing Policy Debate 17: 209–234.
Knox, Bill. 2007. Personal communication (interview). Chief of Staff, District of Columbia Housing Authority. (Address not available.) Kovaleski, Serge. 1994. “Landlords Get Hefty Subsidies Despite Substandard Housing,” The Washington Post, July 27: B1.
Levy, Diane K., with Megan Gallagher. 2006. HOPE VI and Neighborhood Revitalization. Final report prepared by the Urban Institute for the John D. and Catherine T. MacArthur Foundation.
Washington, DC: The Urban Institute.
Loeb, Vernon. 1997. “Starting Over from Scratch,” Washington Post, April 24: D1.
Massey, Douglas S., and Shawn M. Kanaiaupuni. 1993. “Public Housing and the Concentration of Poverty,” Social Science Quarterly 74: 109–122.
Morenoff, Jeffrey D., Robert J. Sampson, and Stephen W. Raudenbush. 2001. “Neighborhood
Inequality, Collective Efficacy, and the Spatial Dynamics of Urban Violence,” Criminology 39:
Saegert, Susan, Gary Winkel, and Charles Swartz. 2002. “Social Capital and Crime in New York City’s Low-Income Housing,” Housing Policy Debate 13: 189–226.
Schill, Michael H., Ingrid Gould Ellen, Amy Ellen Schwartz, and Ioan Voicu. 2002. “Revitalizing Inner-City Neighborhoods: New York City’s Ten-Year Plan,” Housing Policy Debate 13: 529–566.
Turbov, Mindy, and Valerie Piper. 2005. HOPE VI and Mixed-Finance Redevelopments: A Catalyst for Neighborhood Renewal. Discussion paper prepared for the Brookings Institution Metropolitan Policy Program.
Wheeler, Linda. 1998. “Wilson Housing Reborn,” The Washington Post, November 5: J1.
Zielenbach, Sean. 2006. “Moving beyond the Rhetoric: Section 8 Housing Choice Voucher Program and Lower-Income Urban Neighborhoods,” Journal of Affordable Housing and Community Development Law 16 (1): 6-37.
———. 2003(a). “Assessing Economic Change in HOPE VI Neighborhoods,” Housing Policy Debate 14: 621–655.
———. 2003(b). “Catalyzing Community Development: HOPE VI and Neighborhood Revitalization,” Journal of Affordable Housing and Community Development Law 13: 40–80.
Additional Reading Ellen, Ingrid Gould, Amy Ellen Schwartz, Ioan Voicu, and Michael H. Schill. 2007. “Does Federally Subsidized Rental Housing Depress Neighborhood Property Values?” Journal of Policy Analysis and Management 26: 257–280.
Galster, George C. 2002. A Review of the Existing Research on the Effects of Federally Assisted Housing Programs on Neighboring Residential Property Values. Report prepared for the NATIONAL ASSOCIATION OF REALTORS®, National Center for Real Estate Research. Detroit, MI: Wayne State University.
Holin, Mary Joel, Larry Buron, Gretchen Locke, and Alvaro Cortes. 2003. Interim Assessment of the HOPE VI Program Cross-Site Report. Prepared by Abt Associates for the U.S. Department of Housing and Urban Development.
Holloway, Steven R., Deborah Bryan, Robert Chabot, Donna M. Rogers, and James Rulli. 1998.
“Exploring the Effect of Public Housing on the Concentration of Poverty in Columbus, Ohio,” Urban Affairs Review 33: 767–789.
Lee, Chang-Moo, Dennis P. Culhane, and Susan M. Wachter. 1999. “The Differential Impact of Federally Assisted Housing Programs on Nearby Property Values: A Philadelphia Case Study,” Housing Policy Debate 10: 75–93.
Turner, Margery Austin, Mark Woolley, G. Thomas Kingsley, Susan J. Popkin, Diane Levy, and Elizabeth Cove. 2007. Estimating the Public Costs and Benefits of HOPE VI Investments: Methodological Report. Washington, DC: Urban Institute, Metropolitan Housing and Communities Policy Center.
Cityscape 131 132 HOPE VI Moving Toward a Shrinking Cities Metric: Analyzing Land Use Changes Associated With Depopulation in Flint, Michigan Justin B. Hollander Tufts University Abstract Cities around the globe have experienced depopulation or population shrinkage at an acute level in the last half century. Conventional community development and planning responses have looked to reverse the process of depopulation almost universally, with little attention paid to how neighborhoods physically change when they lose population.
This article presents an approach to study the physical changes of depopulating neighborhoods in a novel way. The approach considers how population decline creates different physical impacts (more or less housing abandonment, for example) across different neighborhoods. Data presented from a detailed case study of Flint, Michigan, illustrate that population decline can be more painful in some neighborhoods than in others, suggesting that this article’s proposed approach may be useful in implementing smart decline.
Introduction Many modern cities throughout the world are facing population declines at an unprecedented scale. Over the past 50 years, 370 cities throughout the world with populations of more than 100,000 have reported a decline in population of at least 10 percent (Oswalt and Rieniets, 2007).
Wide swaths of the United States, Canada, Europe, and Japan are projecting double-digit declines in population in the coming decades. Internationally, scholars and practitioners of the built environment have responded to this crisis by reconceptualizing decline as shrinkage and have begun to explore creative and innovative ways for cities to successfully shrink (Hollander and Popper, 2007;
Stohr, 2004; Swope, 2006).
Cityscape 133 Cityscape: A Journal of Policy Development and Research • Volume 12, Number 1 • 2010 U.S. Department of Housing and Urban Development • Office of Policy Development and Research Hollander Popper and Popper (2002) define smart decline as “planning for less—fewer people, fewer buildings, fewer land uses” (Popper and Popper, 2002: 23). The clearest practical example of smart decline is their proposal to establish a “Buffalo Commons” in severely shrinking parts of the Great Plains (Matthews, 1992). The Poppers’ research (1987) found that the preservation of a large portion of the Great Plains as “somewhere between traditional agriculture and pure wilderness” offered “ecologically and economically restorative possibilities” (Popper and Popper, 2004: 4).
Vergara (1999) proposes an “American Acropolis” in downtown Detroit to preserve the scores of abandoned skyscrapers. He sees cultural benefit in establishing a park at the site to attract visitors to walk the crumbling streets. Also, Clark (1989) encourages preservation of declining areas as vacant, arguing that these areas can be converted to “parkland and recreational spaces” (Clark, 1989: 143)—a suggestion echoed recently by Schilling and Logan (2008). Armborst, D’Oca, and Theodore (2005) introduced the idea of widespread sideyard acquisitions of vacant lots as a means for reducing housing density, a process they described as “blotting.” They found that the urban fabric of Detroit was changing daily, not by city plan or regulation, but by the actions of individual landowners in expanding their lots to more closely mirror density patterns seen in suburbia.
In Youngstown, Ohio, a city that has lost one-half of its population since 1950, community leaders adopted this smart decline approach with a new master plan to address its remaining population of 74,000 (U.S. Census Bureau, 2008). In the plan, the city came to terms with its ongoing population loss and called for a “better, smaller Youngstown,” focusing on improving the quality of life for existing residents rather than attempting to repopulate the city (City of Youngstown, 2005;
Hollander, 2009).1 Before the community development and planning fields move too far forward in “shrinking” these depopulating places through smart decline, practitioners need a clearer understanding of how neighborhoods physically change when they depopulate. A smart decline plan that ignores the projected quantitative change in structures or the qualitative change in use associated with depopulation will be hamstrung from the start.
A major stumbling block for scholars and practitioners is that current theory offers no widely accepted and intuitive measurement tool for studying the past and projected physical changes that occur in neighborhoods—the movement from active uses of land (such as homes and apartments) to successor land uses (such as vacant lots and abandoned buildings). The way we presently operationalize physical decline is by way of counting the number of vacant lots and abandoned buildings, a very labor-intensive approach that can make time series or longitudinal analysis challenging.
This article presents a thorough overview of how occupied-housing-unit density may be used as a metric to analyze changes in physical land use associated with population decline in urban neighborhoods. Such analysis can help local government officials and community leaders devise new plans and policies to respond to their problems resulting from fewer occupants and fewer occupied housing units. This article shows how a close examination of Flint, Michigan, through The New York Times Magazine recognized the city’s plan as one of the most creative ideas in 2006 (Lanks, 2006).
census data analysis, data collected from direct observation of neighborhood conditions, and data from interviews of residents demonstrates the value of the metric and begins to address some limitations of conventional methods of studying depopulation.
In the study, I calculated changing housing-unit density for three Flint neighborhoods and then validated the results through field research. Validation showed that some neighborhoods experience depopulation differently than others. The physical form of some neighborhoods changed to accommodate a smaller population and a smaller number of occupied housing units; other neighborhoods did not change, resulting in lower quality neighborhoods for the residents left behind. This finding initiates a new type of thought process for neighborhood-based community development that may be able to customize land use strategies to right-size the physical features of a neighborhood to match its smaller population. The remainder of this article presents relevant research on population decline, describes the data and methods used in the empirical study and the results, and concludes with a discussion about the implications of these results for federal and state policymakers, as well as local community development and planning practitioners.
Studying the Physical Form of Shrinking Neighborhoods Bowman and Pagano (2004) conducted an exhaustive study on this topic of shrinking neighborhoods, seeking to understand the extent of the vacancy problem in the United States. They administered written surveys to local officials and assembled a database of the number of abandoned buildings and the number of vacant lots across more than 100 cities in the United States. This survey-based method unfortunately has proved unreliable when cross-checked against housing-unit counts from the U.S. Decennial Census (Hollander, 2009). Local officials use very different strategies to account for vacancy and abandonment, making the use of locally distinct administrative data sources challenging. Hillier et al. (2003) examined Philadelphia’s housing databases to track vacancy and abandonment data, but their systems are not interoperable,2 making comparative analysis practically impossible. Wilson and Margulis (1994) developed a similar localized analysis in Cleveland. Ryznar and Wagner (2001) attempted to study the effects of population decline, using Geographic Information Systems and remote sensing techniques, but could measure only net change in forested and agricultural land, extrapolating their findings to housing and commercial land use changes.
One possible solution to this problem is to reconsider some of the data that are widely available from the Decennial Census. Data from the census provide total counts of occupied housing units for neighborhood-level census tracts every 10 years. Each housing unit in the United States is classified as either occupied or vacant. If vacant, the Census Bureau has devised several possible classifications to reflect different reasons for vacancy, including the house is for sale, it is a seasonal home, or it falls into a catch-all category—other vacant—that has been used by researchers to indicate abandoned homes (Hollander, 2009; HUD PD&R, 2004).3 Data cannot be viewed and manipulated from one system to another.
The U.S. Census Bureau only collects vacancy data for residential properties and not on commercial properties.