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Demography

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01-02-2013

Population Trends as a Counterweight to Central City Decline, 1950–2000

Authors: Leah Boustan, Allison Shertzer

Published in: Demography | Issue 1/2013

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Abstract

The share of metropolitan residents living in central cities declined dramatically from 1950 to 2000. We argue that cities would have lost even further ground if not for demographic trends such as renewed immigration, delayed childbearing, and a decline in the share of households headed by veterans. We provide causal estimates of the effect of children on residential location using the birth of twins. The effect of veteran status is identified from a discontinuity in the probability of military service during and after the mass mobilization for World War II. Our results suggest that these changes in demographic composition were strong enough to bolster city population but not to fully counteract socioeconomic factors favoring suburban growth.

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A series of popular essays have pointed to the effect of demographic shifts on city growth (Ehrenhalt 2008; Leinberger 2008). To our knowledge, this is the first scholarly article to investigate this connection in detail.

The relationship between demographic characteristics and residential location derive from a complex interaction between household preferences and institutional and social constraints. For example, veterans bought new homes in the suburbs not only because of their own preference for suburban residence but also because new housing construction after World War II was disproportionately located in the suburban ring. In documenting these relationships, we do not aim to distinguish between these demand-side and supply-side mechanisms.

See Rappaport (2003) for a discussion of similar trends. Panel a of Fig. 1 includes all metropolitan areas anchored by a city that had at least 50,000 residents in either 1940 or 1970. The core analysis relies instead on metropolitan areas whose residents can be identified by location (city or suburb) in the census microdata in each year.

The share of the total population living in a central city declined only from 31 % in 1950 to 25 % in 2000 because the metropolitan shift to the suburbs was partially offset by rural-to-urban migration.

The growth of central cities is partly driven by the expansion of city land area via annexation. In 1940, the average city in this sample was 48 square miles; by 2000, it had grown to 117 square miles.

The presence of higher quality public goods and more affluent neighborhoods in the suburbs is not an inherent feature of cities in developed economies. Indeed, many European cities are organized differently, with the most desirable neighborhoods located in the city center. For a U.S.-European comparison, see Brueckner et al. (1999).

The FHA began insuring mortgages initiated by private lenders in the mid-1930s. As a result, mortgage rates fell from 6 % to 8 % in the 1920s to 2 % to 3 % in the 1940s (Jackson 1985:205).

We do not include data from 1950 because, in that year, veteran status was asked only of individuals on the sample line.

IPUMS does not report central city status if doing so would allow users to identify geographic areas with fewer than 100,000–250,000 residents. Depending on the year, we are able to identify observations from between 91 and 143 metropolitan areas. We analyze a consistent sample of 109 metropolitan areas in Table 2.

The five cohort groups in the main specification were born in 1869–1910, 1911–1930, 1931–1950, 1951–1970, and after 1970 (the omitted category). We identify age, period, and cohort effects by constraining that cohort effect to be identical within these 20-year intervals. Results are robust to using finer cohort groups.

A portion of the relationship between veteran status and residential location is driven by an association between having served in the military and being married (see column 5).

We experimented with adding a richer set of dummy variables and found no statistical difference between having two versus three children, three versus four children, and so on.

The “empty nest” indicator is available from 1960 to 1990 only. In these years, the census added a question about children ever born for all women who were at least 15 years old.

We include divorced and widowed household heads in the control group because these marital transitions often lead to residential mobility. Results are similar if we instead compare the ever- and never-married.

Married men have higher labor-market earnings than their single counterparts, which may allow married couples to afford a suburban residence (Ginther and Zavodny 2001; Korenman and Neumark 1991). When we control for household income, the effect on marital status declines by 20 % (results not shown). We interpret the results in column 5 as the total effect of marriage on residential location, including a potential earnings channel.

For example, between 1980 and 1990, the number of counties included in the average metropolitan area increased from 4.6 to 7.5.

We exclude 1960 and 1970 because of additional data restrictions in these years. In 1960, the microdata do not report metropolitan area of residence; and in 1970, either place of residence (central city versus suburb) or metropolitan area is known, but not both.

Bound and Turner (2002) and Page (2008) used a similar approach to study the effect of the G.I. Bill on educational attainment. Because quarter of birth is available in the census only from 1960 to 1980, we focus on these years in our IV estimation.

We also estimated this system using a seemingly unrelated bivariate probit model. The IV probit results are quite similar to the two-stage least squares estimates (coefficient = −0.076, SE = 0.030). Results are also similar when we shorten or lengthen the treatment window.

We also experimented with appropriate probit methods (bivariate probit or probit IV). However, the resulting estimates were either implausibly large or implausibly small. Therefore, we follow Angrist and Pischke (2009:204–05) in reporting the more robust two-stage least squares coefficients.

Because our IV regressions are estimated on selected samples, we use the ratio between the OLS and IV estimates in Tables 3 and 4 to scale the coefficients for the whole population from Table 1. Specifically, we augment the veterans coefficient by 2.3 (−0.067 / –0.029 from Table 3, columns 1 and 2), and we augment the “any child” coefficient by 1.6 (−0.052 / –0.032 from Table 4, columns 3 and 4).

Similar work by Crowder et al. (2011) has shown that, for the native-born, the log odds of moving increase with the foreign-born share of the neighborhood.

The extent of price increases depends on the elasticity of housing supply; at the extreme, prices will not respond to in-migration if each new arrival is met with the construction of a new housing unit.

An earlier literature used total cohort size to assess the relationship between population growth and housing prices. Mankiw and Weil (1989) documented large effects of the entry of baby boomers into the housing market in the United States, while Engelhardt and Poterba (1991) found no effect in Canada. This evidence is hard to interpret because it is based on national time series.

Over this period, around 40 % of metropolitan residents lived in a central city. Therefore, city population would have needed to increase by 7.5 % in order for the share of the metropolitan area living in a central city to increase by 3 percentage points.

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Title: Population Trends as a Counterweight to Central City Decline, 1950–2000
Authors: Leah Boustan
Allison Shertzer
Publication date: 01-02-2013
Publisher: Springer US
Published in: Demography / Issue 1/2013
Print ISSN: 0070-3370
Electronic ISSN: 1533-7790
DOI: https://doi.org/10.1007/s13524-012-0137-5

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