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on Housing and Real Estate |
| By: | Daniel Broxterman; William Larson; Anthony Yezer |
| Abstract: | Characterizing the level and change of housing prices in cities is central to many empirical questions, whether prices are measured using rents or asset values. The task is complicated by the heterogeneity of the housing stock, the joint consumption of housing and neighborhood, and differences in accessibility. This paper focuses on intra-city location which, based on economic theory, is systematically related to housing prices. The final conclusion is that a sufficient statistic to describe both the level of and change in the average housing price requires that prices be aggregated from relatively homogeneous market areas and weighted by housing quantities such as dwelling units or interior space. Common repeat-sales and hedonic indexes are generally not weighted in this fashion but could be modified to do so. |
| JEL: | R14 R21 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35144 |
| By: | Ronan C. Lyons; Allison Shertzer; Rowena Gray |
| Abstract: | The Rent of Primary Residence (RoPR) series constructed by the Bureau of Labor Statistics (BLS) implies that nominal rental prices increased by just 2.6% per year from 1914 to 2006 while overall prices grew by 3.3%. We show that this “falling real rents” puzzle can be explained by the evolving treatment of shelter in the Consumer Price Index (CPI). In this paper we construct a new, methodologically consistent shelter price series using the Historical Housing Prices (HHP) Project rental index. We also construct a revised set of shelter weights going back to 1914 and combine them with the price series to create an alternate CPI that applies the owners’ equivalent rent (OER) concept of shelter consistently across time. The HHP shelter price series increases by a factor of 28.4 (compared with the 10.7 increase in RoPR) and lifts average CPI growth from 3.3% to 3.6% per year. The revised series eliminates the long-run decline in real rents in the CPI and provides a new benchmark for assessing trends in the cost of living and real income in the U.S. over the twentieth century. |
| JEL: | N01 O18 R3 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35124 |
| By: | Manu García; Carlos Garriga |
| Abstract: | We analyze over 30 million home purchase mortgage applications from 2018-2024 using publicly available Home Mortgage Disclosure Act (HMDA) data to study the determinants of mortgage denial. We establish three primary findings. First, credit access is highly sensitive to monetary policy; the 2022-2023 tightening drove aggregate denial rates from 12.2% to 15.7% via the debt-to-income (DTI) channel. Second, we identify a critical nonlinearity in underwriting: While the 43% qualified mortgage (QM) threshold---below which lenders receive legal safe harbor from ability-to-repay claims---is non-binding in practice, denial rates jump by 15-17 percentage points at the 50% DTI mark, marking the functional market boundary. Third, substantial racial disparities persist; controlling for lender fixed effects and financials, Black applicants are 7.8 percentage points more likely to be denied than White applicants. Observable characteristics explain at most 41% of this gap. These results demonstrate how monetary tightening interacts with structural inequalities to disproportionately restrict credit access for vulnerable populations at the extensive margin. |
| Keywords: | mortgage lending; credit access; housing finance; homeownership; underwriting; monetary policy |
| JEL: | G21 R21 R31 D14 E52 |
| Date: | 2026–04–29 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedlwp:103090 |
| By: | Yashvant Premchand (Vrije Universiteit Amsterdam); Peter Mulder (Utrecht University) |
| Abstract: | Where should we build new housing under growing climate hazards? This paper develops a framework that balances the economic benefits of density against the geographically varying costs of climate adaptation. We apply it to the Netherlands, where demand for new housing is high, but much of the land lies in floodplains or subsidence-prone areas. Agglomeration benefits are proxied by land values, while adaptation costs are derived from engineering estimates of flood protection and soil subsidence. Combining these data allows us to map spatial trade-offs and identify where development remains welfare-enhancing. Our findings show that dense cities continue to generate strong net welfare gains, even in places with high costs, while low-density settlements generate a welfare loss for new housing. We identify density thresholds above which housing development becomes feasible. Many medium-sized Dutch cities already exceed these thresholds, making densification more beneficial than peripheral expansion. Climate adaptation thus strengthens—rather than weakens—the case for urban densification. |
| Keywords: | Housing development, Climate adaptation, Agglomeration effects, Land values, Urban density |
| JEL: | Q54 R11 R14 R31 R58 |
| Date: | 2025–12–18 |
| URL: | https://d.repec.org/n?u=RePEc:tin:wpaper:20250073 |
| By: | Miriam Steurer; Sabrina S. Spiegel |
| Abstract: | Missing data are a common feature of micro-level transaction data used to construct hedonic real estate price indices. Missingness typically occurs in the descriptive characteristics required for quality adjustment rather than in transaction prices. Since these characteristics are central to hedonic quality adjustment, complete-case analysis can skew measured price dynamics through sample-selection and composition effects. This paper proposes multiple imputation as a way to handle missing characteristic values in index construction. The aim is not to recover individual missing values, but to restore incomplete observations and reduce variability in the estimation sample. We employ multiple imputation by chained equations (MICE) as a flexible imputation framework. Since conventional aggregation rules for multiple imputation, Rubin’s rules, do not align with the multiplicative chaining structure of price indices, we introduce an alternative aggregation method based on pooled growth rates. Empirical evidence from two applications, a large dataset of Vienna apartment transactions and a smaller, more heterogeneous Austrian office market, shows that index estimates are relatively robust to missing data in large, homogeneous settings. In contrast, in thinner and more heterogeneous markets, imputation can materially affect index dynamics. In both settings, flexible MICE specifications with rich predictor sets perform better than simpler imputation methods. |
| JEL: | C55 C81 E31 R31 R33 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35139 |
| By: | Anke Hielscher (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg) |
| Abstract: | This short paper examines how green nudges can be utilized to promote sustainable behavior in the real estate sector. Based on central nudge approaches, concrete fields of application along the stages of development, usage, and marketing of real estate are identified. The objective is to provide impulses for practice-oriented measures as well as to highlight the need for further empirical research. |
| Keywords: | green nudges, nudging, real estate sector, sustainable behavior, behavioral economics |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:mag:wpaper:26003 |
| By: | Lindhe, Adam (Royal Institute of Technology (KTH)); Orrenius, Johan (Research Institute of Industrial Economics (IFN)) |
| Abstract: | We introduce a choice-set approach to defining markets and a novel method to empirically recover geographic markets using machine learning, Spatial and Categorical Bayesian Clustering (SCBC). SCBC leverages the identity of the seller for each observation to capture market structures in a novel way that is not captured by purely distance-based methods. Applied to real estate agents in Stockholm (Sweden), SCBC classifies sales more accurately than the baseline K-means algorithm. Finally, we investigate the correct number of clusters and find that the optimal number of clusters is close to the validation set based on industry knowledge. |
| Keywords: | Industrial organization; Competition policy; Market regulations |
| JEL: | C60 D47 L10 |
| Date: | 2026–04–29 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:iuiwop:1558 |