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Measuring Changes in Local House Prices: An Empirical Investigation of Alternative Methodologies
Abstract
This paper investigates whether reliable house price indices can be constructed using a limited set of descriptive variables on a large number of observations. Four primary index methods are compared: (1) median sale price, (2) restricted hedonic, (3) repeat sales, and (4) the assessed-value technique. The paper examines the precision and accuracy of each of the alternative indices.
... This model is simple to use since it uses only one regression but because the data is pooled together, the potential changes in the implicit real estate price attributes are not controlled (Bourassa et al., 2006). Regarding the SCS model, the implicit prices of the real estate characteristics are estimated in a separate hedonic regression for each time period, thereby allowing the implicit prices to vary over time (Gatzlaff and Ling, 1994). Clearly, the method is very cumbersome as a separate regression will have to be run for each of the time periods covered by the index. ...
... The SCS hedonic method is an alternative to the explicit-time variable hedonic method and helps to deal with the biases which are associated with the latter as a result of the potential changes to the implicit house price attributes over time. With this method, the implicit characteristic prices are estimated in a separate hedonic regression for each time period, thereby allowing the implicit attribute prices to vary over time (Gatzlaff and Ling, 1994). That is, the same regression equation is used to run a separate regression at each period using each period's cross-sectional data. ...
... The ETV model groups all the data for adjacent time periods and then includes discrete time periods as independent variables. The SCS model also runs separate hedonic regression for each time period but excludes the time dummies, thereby allowing the implicit prices to vary over time (Gatzlaff and Ling, 1994). ...
... The additional flexibility can be by, for example, estimating the implicit prices with a time trend or by including a series of time dummies for each hedonic characteristic. With the SCS model, the implicit characteristic prices are estimated in a separate hedonic regression for each time period, thereby allowing the implicit attribute prices to vary over time (Gatzlaff and Ling, 1994). That is, the same regression equation is used to run a separate regression at each period using each period's cross-sectional data. ...
Purpose
The purpose of this paper is to test whether temporal aggregation matters when constructing hedonic house price indices for developing markets using Ghana as a case study.
Design/methodology/approach
Monthly, quarterly, semi-yearly and yearly hedonic price indices are constructed and six null hypotheses are tested using the F-ratios to examine the temporal aggregation effect.
Findings
The results show that temporal aggregation may not be a serious issue when constructing hedonic house price indices for developing markets as a result of the smaller sample size which these markets normally have. At even 10 per cent significance level, none of the F-ratios estimated is statistically significant. Analysis of the mean returns and volatilities reveal that indices constructed at the lower level of temporal aggregation are very volatile, suggesting that the volume of transactions can affect the level of temporal aggregation, and so, the temporal aggregation level should not be generalised, as is currently observed in the literature.
Originality/value
The diversification importance of real estate and the introduction of real estate derivatives and home equity insurance as financial products call for the construction of robust and accurate real estate indices in all markets. While almost all empirical research recommends real estate price indices to be conducted at the lower level of temporal aggregation, these studies are largely conducted in developed markets where transactions take place frequently and large transaction databases exist. Unfortunately, little is known about the importance of temporal aggregation effect when constructing indices for developing real estate markets. This paper contributes to fill these gaps.
... While there is no formal theoretical directive for the functional form, a number of studies have relied on this explicit time variable model for comparing the predictive power of hedonic models with models of repeat sales and nonparametric models with similar results, achieved with each format. The general form of this model is as follows (Gatzlaff and Ling, 1994): ...
... A frequently used technique involves entering the variables of interest into quadratic form to allow for ease of interpretation of first and second order effects while entering all other variables in their linear form. Gatzlaff and Ling (1994) estimated four explicit time-variable models to evaluate alternative functional forms for a hedonic model: (1) exponential; (2) semi-log; (3) double-log; and (4) linear. 7 The four functional forms were applied to an observation set and compared on the basis of the R 2 statistic. ...
The objective is to contribute to the discussion on property tax inequity by employing the methodologies developed to test for vertical inequity in a tax system that currently does not rely on some form of market value in the assessment process. There is strong evidence that the property tax and the ''True Tax Value'' assessment procedure employed in Indiana contains progressive vertical inequities rather than regressive inequities as is typically perceived. This is unique, as previous findings tend to support the notion that the property tax is regressive. It provides potentially pertinent information in light of the ongoing discussion surrounding the restructuring of Indiana's property tax assessment and property tax debates elsewhere.
... In many countries, House Price Index (HPI) is commonly used to calculate house price inflation for residential properties [4,5]. One of the basic methods of constructing HPI is to refer to the median price for each period [6][7][8]. This type of index is easy to construct, but it has the disadvantage of having little or no control over quality [9,10]. ...
In every period, housing price prediction has always been a fascinating topic. Fluctuations in housing price are not only relevant to each individual resident but also to the politics and economy of the country. This essence of this research project is the usage of some real influencing factors to predict housing prices. In the Ames Housing dataset from Kaggle.com, five real factors that have a relatively strong correlation with housing prices are the overall material and finish quality, the above ground living area, the size of garage in car capacity, the garage area, and the total basement area. Based on these five real factors, two multiple linear regression models are constructed for predicting residential prices in Ames, Lowa, US. According to the analysis, when two independent variables are closely related, removing one of them does not necessarily reduce the fit of the model significantly, even if both independent variables are closely related to housing price. Therefore, choosing more appropriate variables is very important to increase the fit of the model. These results shed light on guiding further exploration of using more significant variables to find more accurate models to fit actual housing prices.
... While we incorporate adjustments for spatial and temporal autocorrelation, our estimates only reflect land values revealed by transactions. An extensive body of literature has studied the problem of estimation bias when samples are truncated because some potential transactions are excluded due to mismatches between buyers and sellers (Bishop et al. 2020;Haurin 1997, 1998;Gatzlaff and Ling 1994;Munneke and Slade 2000). In our case, the most likely source of truncation bias is inherited land with very high salinity and/or cyclone risk, for which non-market factors may create a reservation price that exceeds very low offers from buyers. ...
Data scarcity has hindered studies on the impacts of climate change on land prices in the coastal regions of developing countries. Focused on the Indian Sundarbans, this paper is at the forefront of such research. Market conditions in the region feature unregulated transactions, unenforced zoning, and a lack of disaster insurance. For many residents with hereditary land ownership, stark poverty eliminates any risk buffer provided by savings or other non-essential liquid assets. Using new household surveys and environmental data, our study hypothesizes that salinization and cyclone strikes have already adversely affected land prices. We quantify such impacts using a georeferenced panel of 342 salinity monitoring stations and a spatial raster database on all cyclonic storm strikes since 1970. Our econometric results reveal highly significant negative impacts for both factors. We use the regression results to predict land prices for the most and least favourable environmental conditions recorded in our database. The results show that these climate change–related conditions account for spatial differentials greater than an order of magnitude in land prices. Such extreme risk differentials suggest high financial and fiscal stakes, underscoring the critical importance of appropriately targeted adjustment policies. [] weblink: https://ecoinsee.org/journal/ojs/index.php/ees/article/view/567/243
... Various reviews have been carried out that compare these different approaches to property valuation and house price index construction. Mark and Goldberg (1984), Case and Quigley (1991), Crone and Voith (1992), Clapp and Giacotto (1992), Gatzlaff and Ling (1994), and Meese and Wallace (1997) have all compared the various variants of house price indexation models. It can be surmised from these studies that no one approach is generically superior: it ultimately depends on the use/application of the resultant index, type of data available and area under study. ...
In many developing countries, house price index construction is sparse, leaving decisions which hinge on housing performance data with little corroboratory evidence. Thus, the purpose of this research is to ascertain the micro-level determinants of house prices in Ghana. Using a qualitative approach, data are collected through semi-structured interviews with twenty expert property practitioners including valuers, academics, property developers, mortgage providers and housing agents. This research uncovers interesting findings including the relevance of unexpired lease terms, and the impacts of market dynamics such as the physical heterogeneity of properties and hearsay. The study also reveals that an index needs to be created and managed through a collaborative effort between the government and industry to ensure wide acceptability. This study lends guidance to housing policy decisions at the local and national levels, and provides a much-needed source of data for further academic inquiry into the housing dynamics in Ghana.
... Ensemble learning methods by Breiman (1996a) and Schapire (1989) have been successfully applied in a relatively few but growing number of econometric works (Graczyk et al. 2010;Inoue and Kilian, 2008). 1 The research work on the construction of real estate indices has had few improvements since Bailey et al. (1963) and Case and Shiller (1987). Construction methodologies include the use of median house price indices (e.g., Crone and Voith, 1992;Gatzlaff and Ling, 1994), hedonic pricing models (HPMs) (e.g., Balk et al., 2013;Geltner, 2015;Fisher et al., 1994), RSM (e.g., Calhoun, 1996), and hybrid models (e.g., Quigley, 1995;Meese and Wallace, 1997). ...
We develop an automated valuation model (AVM) for the residential real estate market by leveraging stacked generalization and a comparable market analysis. Specifically, we combine four novel ensemble learning methods with a repeat sales method and tailor the data selection for each value estimate. We calibrate and evaluate the model for the residential real estate market in Oslo by producing out-of-sample estimates for the value of 1,979 dwellings sold in the first quarter of 2018. Our novel approach of using stacked generalization achieves a median absolute percentage error of 5.4%, and more than 96% of the dwellings are estimated within 20% of their actual sales price. A comparison of the valuation accuracy of our AVM to that of the local estate agents in Oslo generally demonstrates its viability as a valuation tool. However, in stable market phases, the machine falls short of human capability.
... However, the results of and Gatzlaff and Haurin (1997) were more ambiguous. Furthermore, as shown by Gatzlaff and Ling (1994), Dombrow, et al. (1995), and Goodman and Thibodeau (1998), the use of an augmented repeated-sales model and controlling for heteroskedasticity with a large enough sample is another way of dealing with this issue. 8 9 1 9 9 0 1 9 9 1 1 9 9 2 1 9 9 3 1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 0 0 0 Table 4 presents the empirical results for seven specifications of Equation (1). ...
This paper provides the first study on the impact of noise barriers on the price of adjacent houses based on a repeat sale analysis (RSA). RSA allows us to empirically examine the differential between the prices of houses sold before and after an event that may have affected their value, and after other relevant variables such as the evolution of the real estate market and major renovations performed on the house are controlled. This paper focuses on the neighborhood of Laval, a suburb of Montreal, where a large noise barrier was built in 1990 along a highway. The data set contains transaction information on 134 houses that were sold at least twice from 1980–2000. The empirical result will show that the noise barrier induced a decrease of 6% in the house prices in our sample in the short run, while it had a stronger negative impact of 11% in the long run.
... Ensemble learning methods by Breiman (1996a) and Schapire (1989) have been successfully applied in a relatively few but growing number of econometric works (Graczyk et al. 2010;Inoue and Kilian, 2008). 1 The research work on the construction of real estate indices has had few improvements since Bailey et al. (1963) and Case and Shiller (1987). Construction methodologies include the use of median house price indices (e.g., Crone and Voith, 1992;Gatzlaff and Ling, 1994), hedonic pricing models (HPMs) (e.g., Balk et al., 2013;Geltner, 2015;Fisher et al., 1994), RSM (e.g., Calhoun, 1996), and hybrid models (e.g., Quigley, 1995;Meese and Wallace, 1997). ...
We develop an automated valuation model (AVM) for the residential real estate market by leveraging stacked generalization and a comparable market analysis. Specifically, we combine four novel ensemble learning methods with a repeat sales method and tailor the data selection for each value estimate. We calibrate and evaluate the model for the residential real estate market in Oslo by producing out-of-sample estimates for the value of 1,979 dwellings sold in the first quarter of 2018. Our novel approach of using stacked generalization achieves a median absolute percentage error of 5.4%, and more than 96% of the dwellings are estimated within 20% of their actual sales price. A comparison of the valuation accuracy of our AVM to that of the local estate agents in Oslo generally demonstrates its viability as a valuation tool. However, in stable market phases, the machine falls short of human capability.
... The difference in capital gains is completely caused by this switch to an annual index that does not control for quality. Low index quality, as defined by the degree to which the index adjusts for the changing quality of the underlying housing stock, results in apparently higher house price increases, as Gatzlaff and Ling (1994) and Eichholtz, Korevaar, and Lindenthal (2019) show. ...
This paper aims to determine the total rate of return to residential real estate. It employs hand-collected archival data for Paris (1809–1942) and Amsterdam (1900– 1979), combining microdata on rents, transaction prices and assessed values for the same homes, as well as information about taxes and costs. In all, we collected 131,711 observations of rents, prices or taxes, covering 26,211 properties. We find real total returns to housing, net of costs and taxes, of 4.9 percent per year for Paris and 5.3 percent for Amsterdam. Importantly, our annual returns correlate only weakly with the housing returns estimated in Jordà et al. (2019), and result in 35 percent lower Sharpe ratios than previously suggested. When housing returns are measured correctly – quality-adjusted, with actual yields observed from rents and prices for the same assets property-level, and property-level taxes and costs included – it seems that much evidence of a housing risk premium puzzle disappears.
... This introduces the possibility of bias when studying the effect of negative externalities on property prices because those homes may have been sold because of the negative externality or characteristic being studied. Clapp and Giaccotto (1992) and Gatzlaff and Ling (1994) argue assessed values are effective in the preparation of house price indices, with indices only as correct as the values upon which they are based. © Southern Regional Science Association 2016. ...
This paper uses a unique dataset containing property values and manually collected noise measurements in Memphis, Tennessee to estimate the impact of train noise pollution on commercial and residential property values. Results show that a residential property exposed to 65 decibels or greater of railroad noise results in a 14 to 18 percent decrease in property value. Once a 65 decibel measure is included, there is no additional impact on price of distance to the closest railroad crossing. For commercial property, neither crossing proximity nor noise level significantly affect property value. The results provide evidence of a negative externality that is created by railroad noise for households and the need for more exact measures of noise levels. The findings are also consistent with previous literature suggesting firms have different ideas than individuals about desirable locational attributes.
... In the real estate literature, major efforts are contributed to the measurements of mean and variance of returns (e.g. Geltner (1991), Gatzlaff and Ling (1994), Gatzlaff and Haurin (1997), Chau et al. (2005)), whereas only a few studies are devoted to the measurement of autocorrelation. Two types of biases in autocorrelations of real estate returns have been discussed in the literature, namely temporal aggregation and crosssectional transaction noise. ...
Real estate returns often show highly positive autocorrelation. However, with the Hong Kong housing market data, we found two anomalies. For one, the autocorrelations of the district-level submarket returns are mostly negative. For the other, despite the negative or insignificant submarket autocorrelations, the autocorrelation of the aggregate market returns is highly positive. This study explains the two patterns. First, we show analytically how observed autocorrelation, transaction noise, and the speed of return adjustment are related. The model suggests that even if return adjusts instantly to news, the transaction noise in observed prices will lead us to observe a negative autocorrelation. An empirical approach is derived to recovering the adjustment speed of returns from the negatively biased autocorrelation. Second, the autocorrelation of returns of a market is a function of not only the autocorrelations of its submarkets, but also the cross lead-lag relationships between the submarkets. Strong cross lead-lag relationships inflate the autocorrelation of the aggregate market returns. Two competing hypotheses for explaining the cross lead-lag relationships between submarkets, namely spatial information diffusion and transaction costs, are tested. Empirical tests based on Hong Kong housing market data support the transaction cost hypothesis against spatial diffusion.
... Home buyers take cues on such published indices before entering into a submarket. The same signals are used by developers (individual sellers) in setting prices for real estate in primary (secondary) markets with spatial heterogeneities (Gatzlaff and Ling, 1994). ...
This paper proposes the use of a semiparametric model based on a locally weighted approach that controls for dynamic agglomeration and diffusion effects in constructing localized housing price indices. Based on residential transaction records in Singapore, we create a three-dimensional interactive heat maps that allow for better measurement and visualization of spatial variations and heterogeneity in price appreciation. The heat map captures regional variations and temporal dispersions in price appreciation rates in the business cycle. Our methodology provides high-resolution information about price dynamics that could aid individual buyers, investors, and policy makers in making objective and informed decisions.
... This line of applied work leads to questions of whether the benefits from property characteristics are internalized in house prices (Linneman, 1980), how the marginal values of property characteristics differ across regions (Sirmans, MacDonald, Macpherson, and Zietz, 2006), and, more recently, how hedonic approaches are used to create land price indexes (Sirmans and Slade, 2012). Alternatives to the repeat sales approach certainly exist (Gatzlaff and Ling, 1994;Noeth and Sengupta, 2011); however, the simplicity and minimal data requirements have established it as a leading method for measuring housing market trends. ...
Trends in residential house values can be expressed by changes in house price indexes (HPIs). Since the recent housing crash, distressed sales have increased in numbers and have led to concerns about how they affect HPIs. This paper has three parts. First, the Federal Housing Finance Agency's (FHFA's) standard HPIs are compared to HPIs constructed without distressed sales. Second, FHFA's identification of distressed sales is validated against a public data source. Third, the distressed sale discount is shown to vary across time and place. The magnitude of the discount also depends on whether the current or prior recent sales are distressed.
... For instance, Bohlin (2014) applies both procedures to construct a housing price index for Gothenburg . Other studies also reports that repeated sales indices display a slower price growth than other methods, for example, Mark and Goldberg (1984); Gatzlaff and Ling (1994); and Case, Pollakowski, and Wachter (1991). Results are, however, not unequivocal. ...
Earlier research describes the development of real housing prices as a ‘hockey stick’, i.e. of long stagnation followed by a sharp upturn in recent decades. A problem is that there are very few indices of residential property covering longer periods. Using a database of around 10,900 sales, this study presents a historical housing price index for Stockholm 1818–1875, which extend a previous index by 57 years, one of the longest for any city. A so-called repeated sales index is compared to a sales price appraisals ratio index. We show that in real terms there have been two long upswings, in 1855–1887 and 1993–2018. In other periods, real prices were stagnant or even slightly declining. The nineteenth century upturn did not end in a crash, but was followed by stagnation for a century. There are many similarities between the two upturns. For example, both coincided with the demographic expansion and were preceded by deregulations. During both periods, properties became more expensive relative income levels. Our new data, available at http://historia.se/StockholmResidentialPrices1818_1875.xlsx, reveals that the pattern of a ‘hockey stick’ between 1870 and 2012 is complemented by another hockey stick when the index is expanded.
... The difference in capital gains is completely caused by this switch to an annual index that does not control for quality. Low index quality, as defined by the degree to which the index adjusts for the changing quality of the underlying housing stock, results in apparently higher house price increases, as Gatzlaff and Ling (1994) and Eichholtz, Korevaar, and Lindenthal (2019) show. ...
We estimate total returns to rental housing by studying over 170,000 hand-collected archival observations of prices and rents for individual houses in Paris (1809–1943) and Amsterdam (1900–1979). The annualized real total return, net of costs and taxes, is 4.0% for Paris and 4.8% for Amsterdam, and entirely comesfrom rental yields. Our returns correlate weakly with the implied returns in Jorda et al. (2019) and are substantially lower. We decompose total return risk at the individual asset level, and find that yield risk becomes an increasingly important component of property-level risk for longer investment horizons.
... 14 This methodology was established by Court (1939) and further advanced by Griliches and Adelman (1961), Griliches (1971), and Rosen (1974). There is a large body of literature relating to hedonic price analysis and the accompanying benefits and challenges as it relates to improved properties (see, for example, Case and Shiller (1989), Fisher et al. (1994), Gatzlaff and Ling (1994), Knight et al. (1995), Slade (2000, 2001), and Fisher et al. (2003), Sirmans and Slade (2012), Nichols et al. (2013), and Slade (2014)). See Albouy et al. (2018) for a recent application of hedonic price analysis to estimate a cross-sectional index of transaction-based land values in U.S. metropolitan markets. ...
This study had two objectives: first, to evaluate the historical performance of urban land prices across 20 prominent U.S. metro markets; and second, to determine if urban land prices are a leading indicator for prices in the built environment. Using a time-varying econometric model with spatial controls, we constructed constant-quality metropolitan-level land price indices. We found that 1) from 2000 to 2017 (18 years) national residential and commercial-industrial urban land prices appreciated by 2.08% and 1.87% annually, respectively; 2) urban land prices exhibited greater volatility compared with improved property prices; 3) in many metro markets land prices began to decline before improved property prices leading up to the Great Recession; and 4) land prices were slower to recover after the Great Recession compared with prices in the built environment. Using Granger Causality tests on the national urban land market, we found evidence that from the peak of the market in 2007 through 2017, land prices were a leading indicator of prices in the built environment.
... Thereafter, many studies have emerged, with most of them focusing on the internal attributes, such as leasing, anchor tenants, and space allocation, of shopping malls. According to the studies concerning the leasing of shopping centers and the determinants of shopping center sales (Gatzlaff & Ling, 1994;Mejia & Benjamin, 2002), rents can indirectly reflect a mall's operating conditions. Sirmans and Guidry (1993) studied the market rents for shopping centers and found that customer drawing power was an important determinant, which was indicated by building area and age of the mall, as well as type of anchor tenant. ...
There are few studies on the externalities of shopping malls affecting the housing market. This study aims to discuss two issues: (1) What is the intensity of the impact of a shopping mall? (2) When does the external influence of a shopping mall begin to reveal itself? The West Intime Shopping Mall in Hangzhou offers a unique situation to research the questions. By dividing the study area into nine blocks, using hedonic price theory, and the price gradient approach with housing price data from 2011 to 2015, we found that in the space dimension, the mall exerted a significantly positive effect on the housing prices of nearby blocks. With the increase in distance from the mall, the positive effect decreased. There were more significantly positive effects in blocks far away from the city center. In the time dimension, the effects of West Intime did not reveal themselves until the mall had started to operate and gradually matured over time, implying that the mall did not have the obvious expected impact on housing prices before the mall had begun operating.
... 11 This problem of missing variables is just one prominent limitation of the hedonic approach. Other examples include multicollinearity and several forms of simultaneity among variables (for further details, see, for example, Follain and Jimenez, 1985;Gatzlaff and Ling, 1994;Zabel, 2004). ...
We examine the hypothesis that developers and consumers are more responsive to variations in the relative price of land in areas with a warmer climate. We proxy the climatic factor by the temperature in January, April, July, October, and the average of four months in 21 U.S. states. Using a HUD dataset of single-family newly-constructed housing units from 1996 to 1997, we employ the CES equilibrium equation to analyze the data. Regression analysis results support the research hypothesis. Land-to-structure elasticity of substitution (ES) rises significantly by 0.0149–0.0203 when the weather becomes one degree Fahrenheit warmer. The findings may be of assistance to real estate developers, agents, and appraisers in identifying the requirements of potential consumers and applying different lot subdivisions in warmer and colder climatic regions.
... Thus it is unlikely that the same mix of properties will transact in every period. Mark and Goldberg (1984), Crone and Voith (1992), and Gatzlaff and Ling (1994) compare indexes based on medians (and, in the first two cases, means) with indexes constructed using methods designed to control for quality. The empirical results reported in these articles suggest that indexes based on medians or means do not adequately control for quality changes. ...
The measurement of house price movements is a vital topic from both academic and practical perspectives and hence has been the focus of much research. There is almost unanimous consensus in the literature that house price indexes should control for the quality of properties; the most widely used methods to attain this aim are the hedonic and repeat sales approaches. The objective of this paper is to compare the Swiss house prices indexes published by the Swiss National Bank (SNB), which are constructed using medians of list prices as published in newspapers and on the internet, to hedonic indexes based on sale prices for the period 1985 to 2006. We find that the list price indexes exhibit quite a different price path than the hedonic indexes during the period. In particular, they appear to overstate price changes in housing markets. We attribute this, at least in part, to changes over time in the composition of the sample of properties on the market.
... One commonly used hedonic technique is the log-linear equation [25][26][27]. Right inferences could be reached using the log-linear form [28]. ...
... One commonly used hedonic technique is the log-linear equation [29][30][31]. Right inferences could be reached using the log-linear form [32]. ...
... Hedonic pricing models are used extensively in the real estate literature to measure the influence of housing characteristics on house prices. Gatzlaff and Ling (1994) find that only a few variables such as square footage, age, and lot size can often explain much of the variation in housing prices. Sirmans, Macpherson, and Zietz (2005) provide a comprehensive review of recent studies that have used hedonic models to estimate housing prices. ...
Although previous research indicates that condominium unit location within a development has an effect on its value, no research has examined oceanfront condominium units and the unique influences to which they are exposed. This study analyzes data from condominium sales along the Gulf Coast of Alabama using hedonic pricing models that account for the externalities associated with their location. The findings indicate that the positive externalities associated with upper-floor and corner units have a positive and substantial effect on value. Corner units offer even greater positive externalities and sell at a premium to interior units, primarily due to their more panoramic view. Failure to account for both the positive and negative externalities specific to resort type properties could result in serious misspecification when applying hedonic modeling to these property types.
... Como exemplo de aplicação do modelo de preços hedônicos na construção de índice de preços para imóveis, tem-se: Gatzlaff & Ling (1994), que estimaram índices para a Região Metropolitana de Miami-EUA entre 1971-1991 utilizando variadas especificações do modelo de preços hedônicos, assim como o modelo das vendas repetidas, não encontrando diferenças significativas nos índices gerados pelas diversas metodologias. Hoesli et al. (1997) utilizaram o modelo de preços hedônicos para o mercado imobiliário de Genebra-Suíça entre . ...
This paper focuses on measuring the price appreciation of several real estate types between 1995 and 2003. We used as sample transaction values of apartments, houses, huts, shops, halls, warehouses and land in Belo Horizonte. The hedonic pricing method was used once its basic premise is that the price of a marketed good is related to its characteristics. As a result, we could realize that the properties valuation was small in the period, in many cases below the inflation rate, due to the poor economy, high interest rates, and housing credit small volume.
Estimation of House Price Index (HPI) for policy assessments can facilitate planning for the market. In this study HPI for Tehran was estimated from 2010 to 2017 using hedonic dummy and imputation regression method. Hedonic method is assumed to be more advantageous for at least two reasons: 1. Impact evaluation of effective factors on price changes 2. Comparing two heterogeneous goods. However, the downside is the need for numerous and varied data. A major difference between the dummy and imputation hedonic regression is the presumption of constant and variable of effective factors on house price in the period being studied. The difference results in more accuracy in imputation method. The descriptive variables in the models with regard to the available data are: Tehran districts, age of buildings, area and structure type. The result of the two methods shows that the trend estimated by the two models is the same but are different in numbers. The estimated HPI between 2010 and 2011 using dummy method is 2 percent but using imputation method is 17 percent. The estimated HPI between 2010 and 2017using dummy and imputation method is 129 and 198 percent, respectively. The hedonic dummy regression shows that concrete structure decreases the price and age of the building 4 and 13 percent, respectively but increases the price by 1.2 percent. In addition district 3 experienced the most increase in price and district 18 experienced the least price increase compared to other districts in Tehran. The results of imputation method revealed that districts one, two and three experienced the most increase every year compare to other districts. Also, structure type results in dramatic increase in price but the age and area affect the price annually and with a constant rate.
There is a trade-off between how easy a housing price series is to construct and the extent to which it adjusts for changes in the mix of dwellings sold. Median house price measures are easily calculated, frequently used by industry bodies, and quoted in the media. However, such measures provide poor estimates of short-term changes in prices because they reflect changes in the composition of transactions, as well as changes in demand and supply conditions. This study uses a database of 3.5 million transactions in the six largest Australian cities to demonstrate that compositional shifts between higher- and lower-priced parts of cities can account for much of the noise in median price measures. Accordingly, a simple method of adjusting for compositional change through stratification is proposed. The measure differs from those commonly used internationally, as neighborhoods or small geographic regions are grouped according to the long-term average price level of dwellings in those regions. The measure of price growth produced improves substantially upon a median and is very highly correlated with regression-based measures.
The aims of this study were threefold: 1) study the research gap in carpark and price index via big data and natural language processing, 2) examine the research gap of carpark indices, and 3) construct carpark price indices via repeat sales methods and predict carpark indices via the AutoML. By researching the keyword “carpark” in Google Scholar, the largest electronic academic database covering Web of Science and Scopus indexed articles, this study obtained 999 articles and book chapters from 1910 to 2019. It confirmed that most carpark research threw light on multi-storey carparks, management and ventilation systems, and reinforced concrete carparks. The most common research method was case studies. Regarding price index research, many previous studies focused on consumer, stock, press and futures, with many keywords being related to finance and economics. These indicated that there is no research conducted on carpark price index, not to mention constructing carpark price indices based on repeat sales approach and predicting carpark price indices based on an AutoML approach. This study constructed repeat sales indices for 18 districts in Hong Kong by using 34,562 carpark transaction records from December 2009 to June 2019. Wanchai’s carpark price was about four times that of Yuen Long’s carpark price, indicating the considerable carpark price differences in Hong Kong. This research evidenced the features that affected the carpark price indices models most: gold price ranked the first in all 19 models; oil price or Link stock price ranked second depending on the district, and carpark affordable ratio ranked third.
There is comparatively little empirical evidence regarding the accuracy of regional housing sector forecasts. Much of the recent analysis conducted for this topic is developed for housing starts and indicates a relatively poor track record. This study examines residential real estate forecasts previously published for El Paso, TX using a structural econometric model. Model coverage is much broader than just starts. Similar to earlier studies, the previously published econometric predictions frequently do not fare very well against the selected random walk benchmarks utilized for the various series under consideration.
We compare four traditional repeat sales indices to a recently developed autoregressive index that makes use of the repeat sales methodology but incorporates single sales and a location effect. Qualitative comparisons on statistical issues including the effect of gap time on sales, use of hedonic information, and treatment of single and repeat sales are addressed. Furthermore, predictive ability is used as a quantitative metric in the analysis using data from home sales in 20 metropolitan areas in the United States. The indices tend to track each other over time; however, the differences are substantial enough to be of interest, and we find that the autoregressive index performs best overall.
This paper proposes the use of a semiparametric model based on a locally weighted approach that controls for dynamic agglomeration and diffusion effects in constructing localized housing price indices. Based on residential transaction records in Singapore, we create a three‐dimensional interactive heat maps that allow for better measurement and visualization of spatial variations and heterogeneity in price appreciation. The heat map captures regional variations and temporal dispersions in price appreciation rates in the business cycle. Our methodology provides high‐resolution information about price dynamics that could aid individual buyers, investors, and policy makers in making objective and informed decisions.
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2020 m. įvykęs ekonomikos šokas, sukeltas COVID-19 pandemijos, paveikė šalies ekonomiką ir nekilnojamojo turto rinką. Mokslo studijoje siekiama įvertinti Lietuvos nekilnojamojo turto rinkos pokyčius ekonomikos šoko kontekste. Aptariama ekonomikos šoko samprata, tipai, sąsajos su ekonomikos ciklais, pateikiami ekonomikos šokų stabilizavimo būdai, stabilumo ir ekonomikos šoko ryšio prielaidos, akcentuojant valstybės vaidmenį. Leidinys aktualus įvairiems ekonomikos dalyviams: namų ūkiams, dalyvaujantiems nekilnojamojo turto rinkoje ir ekonomikoje; įmonėms, tiesiogiai ir netiesiogiai susijusioms su šia rinka ir veikimu joje; vyriausybės ir valdžios organams; analitikams ir ekspertams.
Resumo Esse trabalho tem como objetivo discutir as metodologias hedônicas mais difundidas para a construção de índices de preços e aplicá-las para uma base de dados fiscais do município de Belo Horizonte, entre 1995 e 2012. Os resultados para os índices de preços pelos diversos métodos hedônicos estimados registraram uma intensa valorização imobiliária em Belo Horizonte, a partir de 2005, impulsionada pelo aumento na oferta de crédito imobiliário, que se tornou possível após as melhorias no instituo de alienação fiduciária, em 2004. Além disso, a redução nas taxas de juros, o crescimento econômico observado no período e o aumento da renda real das famílias também contribuíram para o bom desempenho dos preços dos imóveis. Mesmo após a crise mundial de 2008/2009, a valorização imobiliária continuou intensa até meados de 2012, possivelmente devido às políticas anticíclicas implementadas pelo Governo Federal. Esses resultados demonstram que a utilização da metodologia hedônica em uma base de dados fiscais constitui uma estratégia promissora para a implementação de um futuro índice de preços oficial para imóveis no Brasil.
La théorie hédonique stipule que les externalités sont internalisées dans le prix de vente des biens immobiliers. Pour la proximité aux autoroutes, le défi est de taille puisque ces infrastructures génèrent à la fois des effets positifs, une amélioration de l'accessibilité, mais également des effets négatifs, notamment sur la santé des individus. En utilisant les informations sur le marché immobilier, il est possible de recouvrer la prime nette exprimant l'équilibre entre ces deux types d'externalités. L'article propose de développer une approche permettant d'isoler la prime, ou volonté de payer, associée aux externalités négatives liées à la proximité des grands axes routiers. Une application est développée pour le territoire de la ville de Québec à partir d'une analyse par appariement des transactions résidentielles unifamiliales entre 1993 et 2004. Les résultats montrent que, selon le type d’infrastructure, une trop grande exposition aux externalités négatives engendre une baisse de la valeur variant entre 6% et 14% du prix moyen. Ces résultats soulignent la présence d’une forme d’iniquité environnementale liée à une trop grande proximité aux axes routiers.
Resumo Este trabalho tem como objetivo estimar índice de preços hedônicos-quantílicos para o mercado de apartamentos em Belo Horizonte, entre 1995 e 2012. A técnica de regressão quantílica foi utilizada pelo fato de o mercado imobiliário ser segmentado. Os resultados indicam que até 2004 a valorização imobiliária foi modesta. Contribuíram para esses resultados a falta de um marco institucional para o Sistema Financeiro da Habitação (SFH) e o ambiente macroeconômico incerto. Por essa razão, não houve um padrão para a valorização imobiliária nos diversos quantis. A partir de 2005, a valorização imobiliária foi intensa em todos os segmentos. Até 2009, os segmentos superiores exibiram maiores taxas de valorização. A partir de 2009, houve uma reversão desse padrão de valorização nos quantis, e os apartamentos dos segmentos inferiores passaram a exibir maior valorização. Parte dessa mudança pode ser atribuída às políticas anticíclicas adotadas pelo Governo Federal para atenuar os efeitos recessivos da crise mundial.
Changes in the prices of homes and the reasons for those changes may be more accurately predicted from repeat sales of the same homes after controlling for their changed attributes and differences in time between their sales and resales. This paper analyzes 346 of 583 sold houses in the Glengarry neighbourhood in Windsor, Ontario, that were sold more than once between 1981 and mid‐2017, and a corresponding 414 of 737 sold houses in the city's Wellington‐Crawford neighbourhood, sold more than once between 1986 and mid‐2017. After comparing types of resold homes with once‐sold ones, a repeat sales model predicts a first period of increasing annual percentage changes in resale prices compared to sale prices during the 1980s, followed by a second period of stagnation and possible decreases until 2011, and then increases during a third period after that. In addition, changes in resold homes’ attributes of the dwelling unit and neighbourhood are a second type of neighbourhood change in two inner‐city neighbourhoods during the past 30 or more years.
This study presents the detailed methodology of generating house price indices for the Hungarian market. The index family is an expansion of the Hungarian housing market statistics in several regards. The nationwide index is derived from a database starting from 1990, and thus the national index is regarded as the longest in comparison to the house price indices available so far. The long time series allow us to observe and compare the real levels of house prices across economic cycles. Another important innovation of this index family is its ability to capture house developments by regions and settlement types, which sheds light on the strong regional heterogeneity underlying the Hungarian housing market.
This article estimates the effect of climatic variables on house prices near ski resorts in different regions in the United States. We find that among the climate variables we test, average winter temperature has the most significant and robust effect where an increase in this climate variable increases house prices near ski resorts at a decreasing rate. At the mean average winter temperature levels, an increase in average winter temperature reduces housing prices for all regions except the Northeast. The consumer surplus from projected average winter temperature changes is negative across all regions and the largest negative effects are in the Midwest and Mountain regions.
In this study we use a large database of real estate transactions to assess the magnitude of measurement error associated with using popular house price indices (HPIs) to value individual properties. In the 4 large U.S. counties that we analyze, we find that the bias associated with using these HPIs to value individual homes increased from near zero in 2005 to between 26% and 113% in 2010. In the second part of the analysis, we use data from Florida to demonstrate that forecast combination methods can be used to improve the accuracy of property-level valuations, in some cases reducing the estimated bias by more than a factor of 3. We find that even the simplest forecast combination method – a simple average – has the potential to significantly improve value estimates.
In this report, we first review the international experiences of House Price Index (HPI), and we then propose a methodology to apply this index in Egypt. (This report is in Arabic.)
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.
A real estate confidence index (RECI) is used to evaluate real estate industry development, and it has become an effective and powerful measure in China’s real estate market (REM). RECI research based on big data is the new trend in finance and economics. In this paper, we apply some methods of text classification to research on the construction of RECI. Firstly, the Naïve Bayes algorithm is used to evaluate data and to classify the extent to which this measure describes confidence in the real estate market. Secondly, experiments on different perspectives are performed to probe the relationship between variables and the accuracy of the classifier. Thirdly, we use the classifier to predict the weekly news. Ultimately, construction of the RECI based on financial and economic news is achieved by applying the classifier to the time and existence of major financial and economic news.
The paper studies the problems associated with the construction of price indexes for commercial properties that could be used in the System of National Accounts. Property price indexes are required for the stocks of commercial properties in the balance sheets and related price indexes for the land and structure components of a commercial property are required in the balance sheet accounts for the calculation of the Multifactor Productivity of the Commercial Property Industry. The paper uses a variant of the builder's model that has been used to construct Residential Property Price Indexes. Geometric depreciation rates are estimated for commercial offices in Tokyo using assessment data for REIT. The problems associated with the decomposition of property value into land and structure components are addressed. The problems associated with depreciating capital expenditures on buildings and with measuring the loss of asset value due to early retirement of the structure are also addressed.
This study analyzes noncredit, rural property transfers from colonial South Carolina. These records are used to measure the frequency, annual timing, geographic spread, and turnover rate of land sales. These data also are used to derive a hedonic land-price index. We argue that these estimates reflect variations in the local expectations of future economic growth and conclude that the rapid increase in land prices reflected the fact that the Low country economy was indeed fueled by plantation agriculture.
Motivation/Problem
Real estate has emerged as one of the most profitable investing options in Indian economy, and its valuation plays an important role in the process. Valuations of real estate are a debatable issue due to lack of research and support knowledge available to the stakeholders and market makers, namely, owners, such as sellers, buyers, brokers and valuers, and lenders, such as bankers and financial institutions. In this article, the author seeks to develop a residential estate valuation index, a consumer perspective.
Methodology
In the first stage the author has identified consumer-centric factors of residential valuation from literature review and grounded theory. In the second stage SPSS & MS Excel techniques are used to find out consumer-driven weights of each factor and to subsequently develop an index matrix.
Output
A residential estate valuation index has been developed. This study attempts to develop a residential estate valuation index for measuring the consumer behaviour with residential estate, residential estate seen as habitat that is an output/product architecture. This index will be helpful for stakeholders, market makers, sellers, buyers, brokers, valuers, bankers and financial institutions in high-involvement decision-making.
Using monthly data from New Zealand housing markets, this paper examined the longrun relationship between mortgage interest rates, rents and local house price movements in an error correction model. It was found that house prices, rents, and interest rates were cointegrated and local house prices mean revert to the fundamentals, as indicated by the present value model. During this dynamic price adjusting process, the effect of interest rates on housing prices differed significantly across local markets. In general, interest rates had a smaller impact than rents on house price movements and the speed of adjustment of house prices to their long-run equilibrium was slow. Finally, the paper demonstrates how analysts can use a short time series to compare fundamental value to market price in a way that may lead to some predictability of local house price movements.
This paper proposes an improved net rate methodology to use the assessed land values to proxy the land contribution in real estate appraisals. The assumption in the method is that neighbourhood effects are capitalised into uniform land assessments. Compared to the traditional sales comparison approach, the method has potential to extend the selection of comparable properties. Simulations based on the theoretical and empirical data suggest the method benefit greatly from compensating for assessment errors. Since more sales can be incorporated into the proposed method, it is contended the appraisal result will be more objective and accurate. In practice, the method provides an attractive solution for property valuations in areas where there are limited sales.
Having estimated a linear regression with p coefficients, one may wish to test whether m additional observations belong to the same regression. This paper presents systematically the tests involved, relates the prediction interval (for m = 1) and the analysis of covariance (for m > p) within the framework of general linear hypothesis (for any m), and extends the results to testing the equality between subsets of coefficients.
In reviewing the numerous papers reporting estimates of the price characteristics relationship for urban housing markets, a diversity of views about the correct specification of this relationship is evident. However, there has so far been little discussion of this diversity in the literature. Tries to fill part of that gap by examining the theoretical and empirical parameters of an 'approximately correct specification', and presents evidence that approximate correctness can be achieved with significantly fewer characteristics than is generally supposed. -Author
The appropriate functional form for a hedonic price equation cannot in general be specified on theoretical grounds. In this paper, a statistical procedure for the choice of functional form is proposed. A highly general functional form is specified that yields all other functional forms of interest as special cases. Likelihood ratio tests are used to test the appropriateness of alternative forms. The procedure is illustrated using cross section microdata for housing. For the case considered, the functional forms most commonly used in previous studies are strongly rejected.
Housing prices differ substantially among metropolitan areas. The rent and house price indexes used here measure this variation among 54 metropolitan areas. A model of metropolitan housing price determination is presented and used to identify the sources of intermetropolitan price variation. Reduced-form equations explain close to 90% of the variation in rental prices and close to 60% of the variation in house prices.
This paper extends hedonic price analysis to the formation of housing price indices measuring variation within a metropolitan area. In forming these indices fifteen submarkets, heterogeneous across time and space, are described within a short-run equilibrium model. Linear functional forms are generally rejected using a method proposed by Box and Cox. Aggregation of hedonic price coefficients into standardized units yields significantly higher housing prices in the central city than in its suburbs, as well as differential effects of structural and neighborhood improvements among submarkets.
This paper examines the hypothesis that the expected rate of return to speculation in the forward foreign exchange market is zero; that is, the logarithm of the forward exchange rate is the market's conditional expectation of the logarithm of the future spot rate. A new computationally tractable econometric methodology for examining restrictions on a k-step-ahead forecasting equation is employed. Using data sampled more finely than the forecast interval, we are able to reject the simple market efficiency hypothesis for exchange rates from the 1970s and the 1920s. For the modern experience, the tests are also inconsistent with several alternative hypotheses which typically characterize the relationship between spot and forward exchange rates.
Several studies of housing price trends recommend combining statistical analysis to repeat sales of residential properties. Recently, price indices derived from these techniques have formed the basis for inferences about the "efficiency" of housing markets. This paper presents an improved methodology which combines inflation on repeat sales of unchanged properties, on repeat sales of improved properties, and on single sales, all in one joint estimation. Empirical evidence, based upon a rich sample of transactions on single family houses in a single neighborhood, indicates the clear advantages of the proposed methodology, at least in one typical application. Copyright 1991 by MIT Press.
In this paper we estimate the price premium associated with organic baby food by applying a hedonic model to price and characteristic data for baby food products collected in two cities: Raleigh/Durham, North Carolina and San Jose, California. We use price per jar of baby food as the dependent variable and control for a number of baby food characteristics (e.g., brand, type, and stage) as well as store characteristics (e.g. type of retail establishment). We find the price premium associated with the organic characteristic to be approximately 12 cents per jar. To the extent this premium reflects parents’ preferences regarding the reduction of their baby’s exposure to pesticide residues, our results could be paired up with risk data to estimate the value of the health benefits associated with reduced exposure.
We begin with a description of three house price panel data sets for the period 1982 to 1991. Next, we estimate a model that assumes the three sources are derived from an underlying unobserved price series, and we construct composite indexes that report house prices for 135 locations. These series can be used either as explanatory variables in studies of household formation, housing demand, and migration or to test models of the determinants of spatial and intertemporal variations in house prices. Finally, we construct regional series (based, alternatively, on census and Salomon Brothers regions) and two national aggregates and describe their movements. Our series are compared to other local, regional, and national series. Copyright American Real Estate and Urban Economics Association.
This paper compares housing price indices estimated using three models with several sets of property transaction data. The commonly used hedonic price model suffers from potential specification bias and inefficiency, while the weighted repeat-sales model presents potentially more serious bias and inefficiency problems. A hybrid model combining hedonic and repeat-sales equations avoids most of these sources of bias and inefficiency. This paper evaluates the performance of each type of model using a particularly rich local housing market database. The results, though ambiguous, appear to confirm the problems with the repeat sales model but suggest that systematic differences between repeat-transacting and single-transacting properties lead to bias in the hedonic and hybrid models as well. Copyright American Real Estate and Urban Economics Association.
In this article we employ four different statistical techniques (geographic, AID, cluster and discriminant analysis) to define homogeneous groupings of houses within an urban area. Analysis of a sample of data from Fayette Country, Kentucky indicates that each of these methods produces distinguishable homogeneous groupings of properties. Predictions of house values are compared using data from Lane County, Oregon, San Mateo County, California, and Fayette County. The major conclusions of the study are that there are no discernible differences among the four methods and that predictions made ignoring the grouping information are as accurate as those obtained by grouping.
In this paper we estimate the price premium associated with organic baby food by applying a hedonic model to price and characteristic data for baby food products collected in two cities: Raleigh/Durham, North Carolina and San Jose, California. We use price per jar of baby food as the dependent variable and control for a number of baby food characteristics (e.g., brand, type, and stage) as well as store characteristics (e.g. type of retail establishment). We find the price premium associated with the organic characteristic to be approximately 12 cents per jar. To the extent this premium reflects parents’ preferences regarding the reduction of their baby’s exposure to pesticide residues, our results could be paired up with risk data to estimate the value of the health benefits associated with reduced exposure.
The tradeoff between risk and return in equity markets is well established. This paper examines the existence of the same tradeoff in the single-family housing market. For home buyers, who constitute about two-thirds of U.S. households, the choice about how much housing and which house to buy is a joint consumption/investment decision. Does this consumption/investment link negate the risk/return tradeoff within the single-family hosuing market? Theory suggests the link still holds. This paper supplies empirical evidence in support of that theoretical result.
This study tests the hypothesis that urban housing markets are segmented in the sense of significantly different prices per unit of housing services existing contemporaneously in spatially or structurally defined submarkets. Using an unusually rich data set for single-family, suburban Boston homes, significant differences in the prices of individual housing attributes are found; but these differences result in negligible differences in the overall price per unit of services. A main conclusion is that the market is working fairly efficiently to eliminate price premiums and discounts, at least in the portion of the market analyzed.