Repeat-sales Model Research Articles

An approach for constructing spatially paired pseudo repeat-sales housing price indices in China

AbstractConstructing a reliable housing price index is crucial for accurately reflecting housing price dynamics and enhancing transparency in the housing market. However, existing methods for constructing housing price indices often confront many challenges, such as omitted variable issues in the hedonic model and constrained samples used in the repeat-sales model. To address these challenges, this study identifies a spatially paired relationship between complexes and develops a Spatially Paired Pseudo Repeat-Sales model to construct the housing price index. This approach offers two significant advantages: first, it enlarges the sample size used in the repeat-sales model at least 1.8 times; second, it effectively estimates the effects of spatial dependency and physical housing factors on prices while mitigating the impacts of unobservable factors through differentiation. The findings of this paper suggest that using the spatially paired pseudo repeat-sales model can significantly improve the estimation of housing price volatility, by approximately 13%. Moreover, the constructed housing price index model demonstrates significant robustness, even when the spatial weight settings are altered. This research provides convincing evidence of improved housing market transparency for stakeholders, including governments, institutional developers, and individual investors. Additionally, the constructed model can inform other similar research in housing price index construction by providing a spatially pairing perspective on housing complexes.

Yes or Not in My Backyard (YIMBY vs. NIMBY)? The Impact of New Social Housing Construction on Single-Family House Prices in Quebec City (Canada)

The development of new social housing faces important resistance by local population, a phenomenon knows as the “not in my backyard” movement. One argument from residents to oppose such project is the idea that new construction will negatively impact property values. This is what this paper aims to investigate. The analysis is based on a complete recension of the new social housing projects built between 2000 and 2020 and on single-family house transactions that occurred between 2004 and 2020 in Quebec City (Canada). A repeated sales model integrating a difference-in-differences estimator is developed to isolate the net price premium related to the emergence of a new social housing building while accounting for the possible heterogeneity impact related to characteristics of the building, including the number of apartments and the type of clientele hosted as well as the local characteristics, such as the spatial concentration of social housing buildings and distance to the city center. The results show a complex net price premium rent function that leads to mixed conclusions and has important implications for the development of new social housing projects.

Love thy neighbours or do ethnic neighbourhood qualities matter? Ethnic price differentials in a multi-ethnic housing market

New Zealand is a multi-ethnic society that embraces multiculturism. Many studies have examined how the concentration of ethnic minorities affects residential property values within small neighbourhoods. However, very few studies have recognised that characteristics of neighbourhoods other than ethnic concentration may cause such price differentials. We use the repeat-sales model, based on more than 66,000 housing transactions in the most ethnically diverse city in New Zealand, to control the unobserved biases and identify the effects of changes in the concentration of ethnic minorities on house prices over time. We argue that the commonly perceived ethnic housing price discount may not be a consequence of taste-based discrimination but statistical discrimination of prospective homebuyers on neighbourhood qualities. After controlling neighbourhood characteristics, which can be unobserved and are assumed to be unchanged over the course of the four censuses, the effect of the ethnic price differential, either increase or decrease, becomes insignificant on house prices. The statistical discrimination hypothesis is further confirmed using the Special Housing Area (SHA) as an exogenous amenity shock in a spatial-temporal differencing model. Using the conventional hedonic model without considering the neighbourhood qualities can be misleading.

What matters more, school choices or neighbourhoods? Evidence from a socioeconomic based school zoning

Neighbourhood effects are often asserted to be attributable to differences in school zones. However, few studies explore the confounding interactions between the quality of school zones and those of neighbourhoods. This study examines whether the effects of school quality interact with neighbourhood effects in determining house price premia. Using micro-level student data from the New Zealand Ministry of Education, we operationalise school quality as the variation in university entrance rates over the years. We then exploit the overlapping geographically defined school zones and a unique socioeconomically based funding system in New Zealand to decompose the total effect of neighbourhoods and school qualities. Our results from the hedonic pricing, boundary-discontinuity, and repeat-sales model indicate that school quality, school decile, and school options are complement to each other that leads homebuyers to have a higher willingness to pay. We also discuss the planning implications on school segregation.

A Spatial Dynamic Factor Repeat Sales Model for Real Estate

A Spatial Dynamic Factor Repeat Sales Model for Real Estate

Expected Transport Accessibility Improvement and House Prices: Evidence from the Construction of the World’s Longest Undersea Road Tunnel

This paper studies the impact of expected transport accessibility improvement on house prices. We identify the effect exploiting a quasi-natural experiment created by the approval and construction of the Ryfast tunnel system in Rogaland, Norway, which shortened the travelling time to the affected municipality from 62 to 24 minutes. Estimates of a repeated sales model in a difference-indifferences framework show that the expectation of improvement in transport accessibility connected with the construction of the tunnel system led to an increase in house prices by 10.1–12.8% on average. That effect grew as the opening of the tunnel drew closer and was driven by less valuable houses.

Clean Electricity, Dirty Electricity: The Effect on Local House Prices

Renewable energy production is one of the most important policy instruments to fight climate change. However, despite global benefits, renewable energy production entails some local challenges, such as requiring more space per unit production capacity. In this paper, we study the external effects of large-scale conventional and renewable electric power generation facilities on local house prices. We combine information of all coal, gas, and biomass plants, as well as all wind turbines in the Netherlands, with 1.5 million housing transactions over a period of 30 years. Using a difference-in-difference as well as a repeated sales model, we study the effects of facility openings and closings. Our results show negative external price effects for gas plants and wind turbines, but positive effects for biomass plants, conditionally upon ex-ante lower priced locations. The external effects of power generating facilities on local housing markets are important to consider, especially with the current focus of public policies on the expansion of renewable energy generation. Our paper is one of the first to present a large-scale study, using detailed information, and comparing several different energy sources in one framework.

The more you know, the better: A Heckman repeat-sales price index

The Repeat-Sales (RS) model controls quality by using the prices of the same items in various time periods. However, this methodology suffers from sample selection bias. To address this issue, a Heckman two-stage procedure has been applied to a sample of Picasso paintings from 1990 to 2016. Contrary to the literature — which argues sample selection bias comes from buy-ins — in this paper, bias is modelled to capture information on items sold only once. The research field frequently uses the standard (RS) index, yet empirical evidence shows systematic differences between the standard RS index and the Heckman RS index. These differences are relevant when buyers make decisions on art investments.

Examining the effects of green infrastructure on residential sales prices in Omaha, Nebraska

Green infrastructure (GI), practices consisting of using vegetation and soil to manage stormwater runoff (e.g., rain gardens, vegetated roofs, bioswales, etc.), has been adopted by cities across the world to help address aging water infrastructure, water quality, excess water quantity, and urban planning needs. Although GI’s contribution to stormwater control and management has been extensively studied, the economic value of its benefits is less known. In Omaha, NE, GI projects have been completed in several public parks. Using a repeat-sales model based on 2000–2018 housing data, we examined the effect of GI on the value of single-family homes within various buffer distances of parks where GI was installed. After controlling for changes associated with home deterioration and renovation, non-stationary location effects, and time-invariant characteristics, we did not find any statistically significant relationships between housing values and GI. This finding is consistent with the notion that homeowners place little value on modifications to existing greenspace, but may also stem from homeowners’ lack of familiarity with GI practices or data limitations.

Controlling Unobserved Heterogeneity in Repeat Sales Models: Application to the Anchoring Effect in Housing

Stocks, art, housing and other assets are often studied in a two-stage repeat sales framework to control unobserved heterogeneity. But unobserved variables that influence both first and second sales remain a troubling source of omitted heterogeneity. We develop an iterative simulation algorithm to mitigate omitted variable bias which can be estimated with standard hedonic data in many repeat sales studies. We illustrate our model with an application to seller anchoring to the price paid for a house. We find that premiums on expected losses are reduced by about 50% compared to conventional models, as expected if our algorithm reduces unobserved heterogeneity. We also show that the probability of sale is strongly negatively associated with quality-adjusted expected losses, consistent with theory and previous empirical evidence on anchoring and sales volume. In contrast, losses measured conventionally produce the opposite results. Our study has general implications for two-stage estimation in the finance literature.

Real Estate Dictionaries Across Space and Time

Leveraging high-dimensional variable selection methods, we show the textual information provided in real estate agents’ remarks about a property can be used to address spatial and temporal heterogeneity in housing markets. Including the textual information in the pricing model decreases in-sample prediction errors by as much as 18.7% at the MSA-level and 39.1% at the zip code level. These results are robust to transforming the raw text using a real estate specific word list, the choice of n-grams, word stemming, and heteroscedasticity in the hedonic and repeat-sales models. These findings suggest the raw text in the remarks can be included directly in predictive pricing models.

Instrumental Variables and Simulation of Bias. Online Appendix for Controlling Unobserved Heterogeneity in Repeat Sales Models: Application to the Anchoring Effect in Housing

This is the Online Appendix for: Controlling Unobserved Heterogeneity in Repeat Sales Models: Application to Anchoring to Purchase Price Stocks, art, automobiles, housing, corporate bonds and other assets are often studied in a repeat sales framework in order to control unobserved heterogeneity. But unobserved variables that influence both first and second sales remain a troubling source of omitted heterogeneity for a large group of two-stage repeat sales models. We develop a simulation algorithm to correct omitted variable bias. Our algorithm is based on a function of the variance of the unobserved as a proportion of a measurable value: the total variance of unobserved plus random noise associated with the first sale. We illustrate our model with an application to seller anchoring to the price paid for a house. Our simulation results suggest that premiums on expected losses are reduced by about 50% compared to conventional models, as expected if our algorithm reduces unobserved heterogeneity. We use property tax assessed value data to control endogeneity and to validate our simulation algorithm. Our algorithm can be estimated with standard hedonic data and it is relevant to many two-stage studies, including boundary effects models, studies of credit spreads in bond markets and firm acquisitions.

The Validity of Hedonic Models for Estimating Heterogeneous Assets Returns

In this paper, we examine the validity of hedonic models for estimating heterogeneous assets returns. We look into the art markets, and show that the returns on hedonic indices strictly depend on the specifications of the model. Different sets of variables lead to different returns. This means that the researcher may implicitly decide on the performance of the hedonic index. These results are confirmed by conducting the same analysis on different samples, but they can be also deduced with simulated data. We conclude that hedonic models are sufficient for studying movements in the market; however, for studying art or other heterogeneous assets as an investment and comparing its performance to other asset classes, the repeat-sales models are more adequate.

The impact of flooding on property prices: A repeat-sales approach

In this paper we use a repeat-sales model to analyse the price path of properties affected by flooding in England between 1995 and 2014. Our dataset contains information on 4.8 million houses with at least one repeat-sale. This database is merged with high-definition GIS data delineating the spatial extent of all recorded flood incidents in England covering a total area of 2,654 km2. Our results show that immediately after a flood event the price of property in a postcode entirely inundated by inland flooding is on average 24.9% lower than non-flooded property, whereas for property in a postcode entirely inundated by coastal flooding the price reduction is 21.1%. Nonetheless, we find that this discount is short-lived and the discount is no longer statistically significant for properties affected by inland flooding after 5 years, which falls to just 4 years for properties affected by coastal flooding. For lower-priced properties however, the post-flood price discount can be observed up to 6–7 years for both inland and coastal flooding. The magnitude of the impact also depends on the characteristics of the properties, the characteristics of the flood and the existence of flood protection assets.

Research note: The effect of stream restoration project attributes on property sale prices

Attributes of stream restoration projects, such as if restoration occurred in-stream or streamside, if the project site was purchased and permanently protected from development, or if there is public access, may affect the sale price of nearby properties. We use a repeat-sales model to estimate the effect of eight project attributes for 209 restoration projects in the Johnson Creek Watershed, Oregon. Estimated effects are found to vary by attribute, distance, and project phase. In-stream restoration efforts are positive while restoration that occurs streamside has mostly negative effects. Nearby property owners experience positive effects if land is purchased for the project, and if recreation facilities are available on site, but negative effects if restoration involves heavy machinery. The effects of some project attributes are capitalized even before restoration work begins.

Using Revisions as a Measure of Price Index Quality in Repeat-Sales Models

Repeat-sales indexes are the most widely used type of transaction based property price indexes. However, such indexes are particularly prone to revision. When a new period of transaction data becomes available and is used to update the repeat-sales model, all past index values can potentially be revised. These revisions are especially problematical for commercial real estate (as compared to housing), due to the relative scarcity of transaction data and the heterogeneity of the underlying properties. From a methodological perspective, the magnitude of the revisions is a particularly useful measure of the index quality, as it directly reflects both the precision of the index and its practical usefulness in economic and business applications. This paper focuses on index revisions in thin, commercial property markets, the type of market that is most challenging. We present multiple specifications of the repeat-sales model (both existing and new), seeking to reduce revisions. We are able to reduce overall index revisions by more than 50%, compared to more traditional repeat-sales models.

Urban Stream Restoration Projects: Do Project Phase, Distance, and Type Affect Nearby Property Sale Prices?

Between 1990 and 2014, more than 200 restoration projects were implemented in the Johnson Creek Watershed, Oregon, to mitigate storm water runoff, restore floodplains, remove invasive plants, restore wetlands, and improve fish and wildlife habitat. We use a repeat-sales model to investigate if restoration projects have an effect on the sale price of nearby single-family residential properties, and if estimated effects vary by project phase, distance, and type. Properties in closest proximity to storm water, floodplain, and revegetation projects experience a positive effect during different project phases. Estimated effects for wetland projects are negative for 9 of the 12 distance/project phase variables.

Controlling Unobserved Heterogeneity in Repeat Sales Models: Application to the Disposition Effect in Housing

Controlling Unobserved Heterogeneity in Repeat Sales Models: Application to the Disposition Effect in Housing

House Price Models for Banking and Insurance Applications: The Impact of Property Characteristics

Abstract House price indices are needed to assess house price risk in households’ portfolio allocation decisions and in many housing-related financial products such as reverse mortgages, mortgage insurance and real estate derivatives. This paper first introduces nine widely-used house price models to the insurance, risk management and actuarial literature and provides new evidence on the relative performance of these models. We then show how portfolio-level house price indices for properties with specific physical and locational characteristics can be constructed for these different models. All analyses are based on a large dataset of individual property transactions in Sydney, Australia, for the period 1971-2011. The unrestricted hedonic model and a hybrid hedonic repeat-sales model provide a good model fit and reliable portfolio-level house price indices. Our results are important for banks, insurers and investors that have exposure to house price risks.

The Effect of Green Retrofitting on US Office Properties: An Investment Perspective

Buildings are responsible for over one-third of all resource consumption, greenhouse gas emissions, and energy consumption. Commercial buildings represent approximately half of that total. In mature economies such as the United States, new construction annually represents only a small fraction of the existing stock of buildings. Hence, retrofitting of commercial buildings, through major renovation projects, is extremely important for sustainability within the built environment. Most studies of green building economics have focused on new construction. This paper is one of the first to focus specifically on retrofit green. Based on a larger sample than most previous studies of new construction, we quantify the magnitude of value enhancement created by green retrofit of US office buildings. This paper is also the first to consider the subsequent investment price dynamics effects of such sustainability. Methodologically, we introduce an innovative way to control for other effects to isolate the value impact and the investment risk and return impact of green retrofitting. We do this by applying a repeat-sales model of only (and all) buildings which will ultimately be retrofitted (in our sample). By using new real estate price indexing methodology, namely a structural time series model employing a hierarchical repeat-sales (HRS) specification, we can build statistically rigorous comparative price indexes of retrofit green, versus non-green, office buildings in the US, quarterly for the 2005-2014 period, even with relatively scarce transaction price data (441 pairs). We find substantial value enhancement in green retrofit projects (between 10% and 20%), and we find evidence that retrofitted green buildings provide investors with lower asset price volatility. But during and just after the Financial Crisis the premium dropped temporarily to near zero, suggesting that the demand for green property investment is income-elastic.