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Resilient Urban Housing Markets: Shocks Versus Fundamentals

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COVID-19: Systemic Risk and Resilience

Part of the book series: Risk, Systems and Decisions ((RSD))

Abstract

In the face of current challenges due to a pandemic, urban protests, an affordability crisis, and a series of other shocks to the quality of urban life, is the desirability of housing in dense urban settings at a turning point? Assessing the future of cities’ long term trends remains an empirical question. The first part of this chapter describes the short-run dynamics of the housing market in 2020. Evidence from prices and price-to-rent ratios suggests expectations of resilience. Zip code-level evidence suggests a short-run trend towards suburbanization, and some impacts of urban protests on house prices. The second part of the chapter analyzes the long-run dynamics of urban growth between 1970 and 2010. It analyzes what, in such urban growth, is explained by short-run shocks as opposed to fundamentals such as education, industrial specialization, industrial diversification, urban segregation, and housing supply elasticity. This chapter’s original results as well as a large established body of literature suggest that fundamentals are the key drivers of growth, and that the shocks considered in this paper have not had historically a measurable long-term impact on metropolitan population growth. The chapter illustrates this finding with two case studies: the New York City housing market after September 11, 2001; and the San Francisco Bay Area in the aftermath of the 1989 Loma Prieta earthquake. Both areas rebounded strongly after these shocks, suggesting the resilience of the urban metropolis.

I would like to thank the Johns Hopkins Coronavirus Research Center, the Inter-university Consortium for Political and Social Research, Zillow, the OpenStreetMap Foundation, and Microsoft Research, for access to microdata. I would like to thank Ambika Gandhi for her careful comments on the manuscript.

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Notes

  1. 1.

    The causal impact of urbanization on health is ambiguous. For instance Singh and Siahpush (2014) displays a life expectancy that is 2.7 year longer in urban areas vs rural areas of the United States. Urbanization can lead to worse health outcomes in urban slums (Riley, Ko, Unger, Reis). While statistical correlations also suggest that urbanization is a necessary condition for growth, there are examples of urbanization without growth, e.g. in Sub-Saharan Africa and in South Asia (Annez and Buckley, Chapter 1 in Spence, Annez, Buckley, 2009; Chauvin, Glaeser, Ma, Tobio,).

  2. 2.

    Table 17.1 presents regressions suggesting a statistically significant positive correlation between county population density and confirmed cases per capita.

  3. 3.

    This statistic uses geocoded protest location data and Zillow’s definition of metropolitan area boundaries. These data are described in Sect. 17.2.4.

  4. 4.

    Recent data includes information on more than 900 metropolitan areas. The 1970–2010 longitudinal data of the Neighborhood Change Database allows an analysis of 306 metropolitan areas.

  5. 5.

    This chapter was written in September 2020.

  6. 6.

    While 2020 county-level population numbers have not yet been released, a similar correlation would arguably hold with updated data.

  7. 7.

    Confirmed cases are also reported as cases per million. Using this alternative scaling does not affect this chapter’s analysis.

  8. 8.

    “New Yorkers Look To Suburbs and Beyond. Other City Dwellers May Be Next”, National Public Radio, July 8, 2020. “New Yorkers Are Fleeing to the Suburbs: ‘The Demand Is Insane’“, New York Times, August 30, 2020.

  9. 9.

    While many other factors than density explains the variance of cases across locations, there is a significant and positive correlation between population density and cases per capita, as displayed in Table 17.1. Marcelle Sussman Fischer, the New York Times, July 2016.

  10. 10.

    See above footnote.

  11. 11.

    Other potential sources of recent geocoded data include the Crowd Counting Consortium. Further literature may focus on Factiva’s news archive as an alternative source of information on protests.

  12. 12.

    For a discussion of this empirical approach, see Goldsmith-Pinkham et al. (2018).

  13. 13.

    CGS Information Warehouse: Regulatory Maps.

  14. 14.

    “What is liquefaction?”, Natural Hazards, U.S. Geological Survey.

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Authors and Affiliations

  1. Associate Professor of Economics, HEC Montreal 3000, Chemin de La Côte Sainte Catherine, Montreal, H3T 2A7, QC, Canada

    Amine Ouazad

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Correspondence to Amine Ouazad .

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  1. Engineer Research and Development Center, US Army Corps of Engineers, Concord, MA, USA

    Igor Linkov

  2. Tulane University, New Orleans, LA, USA

    Jesse M. Keenan

  3. Engineer Research and Development Center, US Army Corps of Engineers, Concord, MA, USA

    Benjamin D. Trump

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Ouazad, A. (2021). Resilient Urban Housing Markets: Shocks Versus Fundamentals. In: Linkov, I., Keenan, J.M., Trump, B.D. (eds) COVID-19: Systemic Risk and Resilience. Risk, Systems and Decisions. Springer, Cham. https://doi.org/10.1007/978-3-030-71587-8_17

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