Journal of Housing Economics最新文献

We study the relationship between density and COVID during three distinct waves of the pandemic in New York City. Unlike prior work, our analysis uses individual Medicaid claims records, which include a rich array of demographic characteristics and pre-existing medical conditions and cover a near universe of low-income New Yorkers. In brief, our results suggest that living in higher density neighborhoods did not heighten the risk of COVID hospitalization. The size of a multifamily building made little difference either, and people living in public housing developments, which are typically highly dense environments, were less likely to be hospitalized for COVID. However, while neighborhood and building density do not seem to matter, we find significant, positive relationships between COVID hospitalization rates and household size. Specifically, we see that people living in large households or in neighborhoods with high levels of crowding were more likely to be hospitalized for COVID. In other words, our results suggest that crowded living quarters – which can occur at any level of population density – and not density itself, increase the risk of COVID hospitalization. We also see a strong correlation between being unstably housed or living in institutional settings and COVID hospitalizations.

This paper uses a correspondence experiment across the northeastern corridor of the US to examine landlord responses to prospective tenants inquiries through a low-income housing rental web site. We find multiple forms of discrimination against African-American tenants, including less responses, responses with less greeting and polite words being used, and levels of discrimination that progressively increases along measures of school quality and neighborhood characteristics. In contrast, we find substantially less evidence of discrimination against voucher holders. Voucher holders do not see lower rates of response, though responses arrive later on average and they face lower rates of responses in neighborhoods with very high quality schools. The results demonstrate that racial discrimination is substantial even in a context where landlords advertise to low-income families, though discrimination against voucher holders may be attenuated.

Distressed property sales, which are carried out under court order by online auction, have increased rapidly in China in recent years. We examine how the implementation of home purchase restrictions (HPR) by the Chinese government in 2017 has affected the market for distressed properties in Beijing. We first use a stylized second-price auction model to derive theoretical predictions for how HPR should impact the number of auction entrants, auction prices/premia, and auction bidders’ average willingness to pay. We then test those predictions using data on court sales from the Taobao online auction platform from 2015 to 2018. By comparing legal auctions of housing before and after April 2017, we obtain empirical results consistent with the model's predictions. Specifically, our analysis documents that auction entrants fell by approximately 70% and auction premia by 16%–27% after the HPR policy was implemented. Furthermore, the average bidder's willingness to pay relative to the seller's valuation fell from 80% to 40%, which suggests that bidders who were affected by HPR had higher valuations, on average, than bidders who weren't.

This paper develops a new approach to estimate the value of urban land. We extend AMM theory by adding the assumption of partial irreversibility. Bundled goods assumptions imply that land value with a structure can evolve differently than as-if vacant value, even in the first decades of structure life. We develop a hybrid model that nests bundled goods with land residual methods and we develop a new test of predictive accuracy. Granular house price indices produced by machine learning are used to estimate hybrid economic structure and land values.

We fit hybrid models to Maricopa County assessor data on houses up to 25 years old during a bust and recovery period (2007–2018). Results support structure value that evolves at some fraction (<1.0) of property value: i.e., partial bundling. The hybrid model achieves substantially lower Coefficients of Dispersion (CODs) than the land residual method, and both methods easily beat standard AVMs that do not separate land and structure values.

Imperfect and costly information generates price dispersion in the market. This study employs data on housing assets listed for sale on a leading online classified home service in Israel to assess the effect of quality-adjusted housing price dispersion on time-on-market. Using survival analysis estimation, we find evidence that the hazard rate of sale significantly decreases with quality-adjusted price dispersion: a 1% increase in the standard deviation of the quality-adjusted housing price is associated with a decrease of about 0.63% in the likelihood of a sale. Results are robust to a series of model and sample specifications. As information is associated with decreased price dispersion in the market, our study supports the call for increased availability of information in real estate markets that would decrease time-on-market and transaction costs associated with the time, search, and negotiation required for achieving a transaction.

This paper documents stylized and empirical facts associated with co-borrowers in the US mortgage market since the early 1990s. The share of mortgages with a co-borrower has declined dramatically across different income and demographic groups. We show that this decline, despite being a universal phenomenon across the US, evinces significant regional heterogeneity which contributes to the divergence in local mortgage markets outcomes. Regions with a lower co-borrower share have higher mortgage default rates. Further, in an event of an adverse shock, regions with a low share of mortgages with a co-borrower experience persistently lower house price growth, and lower purchase and refinance mortgage growth.

Land prices are at the heart of urban economics but are generally not observed directly. Though they are central to household and firm location choices, land-only sales in urban areas are rare and often outliers. Indeed, urban areas are in part defined by a largely contiguous area of high land-use intensity – those places in which developable land is scarce. In this paper, we make use of more-common market data to infer land prices: house sales. Using locally weighted regressions, we estimate the value of a standardized structure across two urban counties: Maricopa, Arizona and Sedgwick, Kansas. Because the value of the standardized structure should be invariant across different locations in a metropolitan area, any remaining variation in the value surface should reflect differences in land values. By pinning down this surface using vacant lot sales at the periphery, we are able to extract land values throughout the metropolitan area, even in locations where vacant land sales are rare.