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The Journal of Real Estate Finance and Economics

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06-06-2020

Geographic Heterogeneity in Housing Market Risk and Portfolio Choice

Author: Tong-yob Nam

Published in: The Journal of Real Estate Finance and Economics | Issue 4/2021

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Abstract

The U.S. housing market is heterogeneous in that house price dynamics vary greatly across regions. Depending on the location of the main residence, households are exposed to completely different housing market risk. This paper examines how geographic heterogeneity in housing market risk affects household portfolio allocations. Housing supply elasticity largely explains variation in housing market risk across regions. Where housing supply elasticity is low, households face higher housing market risk since house price growth rates are more volatile and more positively correlated with stock returns and labor income growth rates. Using the restricted version of the Health and Retirement Study (HRS) data with detailed geographic information, I find that households in areas with low housing supply elasticity tend to hold less stock in their portfolios. This tendency, however, weakens after retirement when labor income risk disappears.

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The stock price of a company whose operations are closely related to the strength of the local economy can be affected by region-specific shocks. If stock investors prefer to hold stocks of locally specialized companies, their portfolios are vulnerable to region-specific shocks (Coval and Moskowitz 1999). However, in this paper, I assume that households hold an aggregate-level stock index; as a result, their portfolios are free of region-specific shocks.

Poterba (2000) briefly summarizes the evidence on the link between stock prices and real estate.

Among various elasticities, only the price elasticity of the housing supply is assumed to vary across regions, as indicated by subscript i in Eq. 2.

Glaeser et al. (2008) show that house prices are more volatile in areas where housing supply elasticity is low. Harter-Dreiman (2004) studies how housing supply elasticity explains the relationship between local house prices and local labor income dynamics.

Assuming the house price at t is 1, then the log house price at t + 1, p_t+ 1, can be interpreted as the house price growth rate.

Chetty et al. (2017) also assume no moving cost, but in their paper, households move only with an exogenous moving shock at a probability of 𝜃. Probability 1 − 𝜃 is interpreted as a commitment to the current house.

From this linear relationship, the correlation between the house price and labor income can be represented as follows: \(\rho _{py}=Corr(p_{t+1},y_{t+1})=\frac {Cov(\upbeta y_{t+1}+\psi _{t+1},y_{t+1})}{\sigma _{p}\sigma _{y}}=\upbeta \frac {\sigma _{y}}{\sigma _{p}}.\) Therefore, a high β means a high correlation between the house price and labor income ρ_py (\(\frac {\partial \rho _{py}}{\partial \upbeta }>0\)).

By contrast, the Panel Study of Income Dynamics (PSID), another longitudinal survey, tracks individuals in all age groups on an annual or biennial basis.

Prior to 1998, the HRS collected data in 1992, 1994, and 1996, while the AHEAD collected data in 1993 and 1995.

Although the HRS has surveyed more than 26,000 individuals, not all of them are relevant to this study. For example, the main focus of this paper being household portfolio allocation in the liquid financial wealth, households with little liquid assets are irrelevant to this study. Including irrelevant households in the sample impedes examination of the real effect of household portfolio allocation.

Although I include both married and single households, I exclude any household that experiences a change in marital status during the sample period. The reason I exclude this sample is that marital status change by itself causes a significant change in household portfolios that may affect the identification of the effect of other factors on portfolio choices.

The HRS does not provide a definition for household head. In this study, I define household head as the member of a household whose earnings are the highest among that household’s members across the survey period.

Since this paper studies the effect of housing assets on portfolio choices, I focus on homeowners in the main analyses. In a robustness test, I also consider the risky investment behavior of households that rent their residence.

In addition to the sample selection criteria listed here, I also exclude any households that have negative total wealth, zero total household income, a stock share greater than 1, or missing demographic information. The exclusion of these samples reduces total sample size from 16,751 to 16,231.

Because the size of MSAs varies greatly, the sample size for each MSA also varies. However, there is no significant variation over survey years within the same MSA.

Note that households can invest in the stock market through an IRA account. The portion of stock held in an IRA account may affect the household’s portfolio choice in their financial wealth. However, due to the limited information on IRA holdings in the HRS data, I am unable to analyze the effect of IRA holdings.

In the HRS, the value of a household’s housing assets is estimated based on the question: “What is its present value? I mean, what would it bring if it were sold today?” Since this question captures a self-estimation of an individual’s house value, the reported value may differ from the house’s market value. However, since the focus of this study is on the impact of perceptions of housing assets on a household’s portfolio decisions, the self-reported value represents an appropriate characterization of the housing assets’ value.

While the measure of housing supply elasticity developed by Saiz (2010) is often used as an instrument for local house prices, it does carry some limitations, as discussed in Davidoff (2016).

Here, home equity share is the portion of home equity (house value - remaining mortgage balance - home equity loan) in total wealth, while stock share is the portion of stock assets in total liquid assets. Although stock share is not directly related to home equity share in this set up, there could be a concern about a systemic relationship between home equity share and stock share. To address this concern, I use the home equity to income ratio to measure the relative importance of the housing asset in household finance. Even using this alternative measure as a control variable, the effect of housing supply elasticity on stock share remains significant.

As alternative specifications, I use home equity (dollar value) or home equity as a share of liquid assets, and obtain similar results.

For this grouping, I consider households with a home equity share between 0 and 1. Since home equity is the value of the house minus the mortgage amount, the home equity share cannot exceed 1 unless the household’s total non-housing wealth is negative. Similarly, the home equity share cannot be less than 0 unless the household’s home equity is negative. After grouping, each home equity share quartile group has home equity share 0 to 0.25, 0.25 to 0.5, 0.5 to 0.75, and 0.75 to 1, respectively. Samples used for this analysis are relatively well distributed across the four home equity share groups. There are 4,756, 6,045, 4,191, and 1,695 samples in groups with home equity shares of 0 to 0.25, 0.25 to 0.5, 0.5 to 0.75, and 0.75 to 1, respectively.

Flavin and Yamashita (2002) estimate the household mortgage holdings using the PSID data. The average LTV ratio for households whose head is aged between 18 and 30 is around 80 percent.

Since self-employment status is not available for retirees, I draw the subsample for this analysis from households in the labor force.

Since this paper defines the head of a household as the member whose labor income is higher than any other member throughout the survey period, the labor income of the household head, by definition, is always higher than that of the spouse. Working status of household head is thus more important to household portfolio choice. For some households, however, the difference in labor income between the household head and the spouse is insignificant, in which case, the spouse’s labor income may represent a considerable portion of the total household income.

For single households, head retirement status is the same as household retirement status.

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Title: Geographic Heterogeneity in Housing Market Risk and Portfolio Choice
Author: Tong-yob Nam
Publication date: 06-06-2020
Publisher: Springer US
Published in: The Journal of Real Estate Finance and Economics / Issue 4/2021
Print ISSN: 0895-5638
Electronic ISSN: 1573-045X
DOI: https://doi.org/10.1007/s11146-020-09762-9

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