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Housing

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Abstract

In many locations, properly positioned new housing that responds to changing housing markets can represent the foundation for mixed-use, walkable suburban centers. In 1920, most Americans lived in mixed-use, walkable urban neighborhoods, and both the suburb and the automobile were already well established in the nation’s culture and economy. Who could have foreseen that by the 1970s the typical new suburban neighborhood would be an isolated auto-dependent subdivision? And who in 1970 could have predicted, roughly four decades later, the rise of a new generation of mixed-use, walkable urban neighborhoods in cities and suburbs alike? Conventional demographic and life-stage analysis, based on historical norms, would forecast a boom in suburban and exurban neighborhoods as members of the millennial generation, the largest in the nation’s history, marry and begin families. But our research and experience suggest that historical norms are once again proving to be poor predictors of future settlement patterns. The assertion that the current urban preference is a mere pause in the dispersal of households, jobs, and shopping into the farther reaches of our metropolitan areas—the nation’s historical thinning out—ignores structural changes in every aspect of American life. Over the next several decades, demographic, technological, and, perhaps most importantly, changing values and lifestyles could combine to create a transformation of American settlement patterns equal in impact to the metro-area thinning out it would partly reverse. It is conceivable that, before too long, many auto-dependent suburbs will be struggling to remain economically viable, or even socially relevant.

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Notes

  1. 1.

    Editors’ note: Zimmerman/Volk has developed a unique, demographics-based methodology for projecting emerging and changing housing markets. The firm has successfully identified, analyzed, and quantified housing markets for new urban, mixed-use centers in both cities and suburbs.

  2. 2.

    Confirmation bias. “There are three kinds of lies: lies, damned lies, and statistics,” runs the oft-quoted quip Mark Twain attributed to Benjamin Disraeli. From the third, most pernicious, form of falsehood much mischief arises. Studies drawing dubious conclusions from statistics have provided fodder for articles, Internet “click bait,” vapid television news features, and countless silly graphics-supported speeches by politicians in venues ranging from local municipalities to C-SPAN. Studies—particularly those commissioned by entities with a specific advocacy position—often have bias built into the questions. Even more common is confirmation bias, which is the citation of selected findings that support a previously held position or opinion.

    Everyone has a confirmation bias. The trick is to guard against bias, particularly when presented with statistical evidence. One must examine the context, sample size, sample composition, error rates, and the myriad other elements that can compromise either a study or the interpretation of its findings. Take the hypothetical example of a reported 75% increase in millennial condominium purchases in suburban downtown X—a finding that might well be presented in a book like this. However, if the 75% represents merely an increase from 9 to 12 buyers out of a total of 200 sales, although the statistic is technically accurate, when presented as a percentage rather than actual numbers and outside the context of total sales, it falls firmly into the third category of lies.

  3. 3.

    Zimmerman/Volk Associates, Inc., proprietary target market analysis.

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    Elizabeth Kneebone and Alan Berube, Confronting Suburban Poverty in America (Washington, DC: Brookings Institution Press, 2013).

  5. 5.

    Officially December 2007 through June 2009.

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    J. A. Martin, B. E. Hamilton, M. J. K. Osterman, S. C. Curtin, and T. J. Mathews, “Births: Final Data for 2013,” National Vital Statistics Reports 12 no. 4 (2015).

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    R. A. Easterlin, “An Economic Framework for Fertility Analysis,” Studies in Family Planning 6 no. 3 (1975): 54–63.

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    National Association of Realtors, “2015 NAR Profile of Home Buyers and Sellers,” accessed August 6, 2017, https://www.nar.realtor/sites/default/files/reports/2015/2015-home-buyer-and-seller-generational-trends-2015-03-11.pdf.

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    US Federal Reserve System. “Consumer Credit: January 2016,” press release, http://www.federalreserve.gov/releases/g19/HIST/cc_hist_memo_levels.html.

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    KRC Research, Zipcar Annual Millennial Survey: “Millennial” Is a State of Mind (Boston: Zipcar, 2015).

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    US Census Bureau, “Annual Estimates of the Resident Population by Sex, Single Year of Age, Race, and Hispanic Origin for the United States: April 1, 2010 to July 1, 2014.”

  20. 20.

    M. Bertoncello and D. Wee, “Ten Ways Autonomous Driving Could Redefine the Automotive World,” released June 2016, accessed August 22, 2017, http://www.mckinsey.com/industries/automotive-and-assembly/our-insights/ten-ways-autonomous-driving-could-redefine-the-automotive-world.

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© 2018 Jason Beske and David Dixon

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Volk, L., Zimmerman, T., Volk-Zimmerman, C. (2018). Housing. In: Beske, J., Dixon, D. (eds) Suburban Remix. Island Press, Washington, DC. https://doi.org/10.5822/978-1-61091-864-0_4

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