Hedonic Regression Approach Research Articles

Does Retrofitting Pay Off? An Analysis of German Multifamily Building Data

Several studies have investigated the relationship between the energy performance of buildings and housing prices. First, this paper identifies a price premium for energy efficiency within the German rental market. Then, the indexed price differences and associated marginal benefits are compared with the marginal costs of energy retrofits. An extensive database of Germany’s largest online platform for housing over a time span from 2016 to 2020 is used in a hedonic regression approach. In addition, to extract the marginal costs of energy consumption abatement, a dataset of 1048 rental units regarding green-retrofit measures is utilized. Although a significant green premium is identified in the rental market, the findings suggest that it is not high enough to compensate landlords for the money they have to spend to retrofit. The marginal costs exceed the marginal benefits by far. Furthermore, it is found that the German government’s recent plans to split the carbon tax between landlords and tenants do not change this because the price per metric ton of carbon is insufficiently high. Limitations with respect to the data basis and consequently to the interpretation of the results exist. Nevertheless, the findings can help both tenants and landlords in their decision-making, as well as policy makers in the implementation of decarbonization efforts.

Does energy retrofitting pay off? An analysis of German multifamily building data

Several studies have investigated the relationship between the energy performance of buildings and housing prices. First, this paper identifies a price premium for energy efficiency within the German rental market. Then, the generated price differences and associated marginal benefits are compared to the marginal costs of energy retrofits. An extensive database of Germany’s largest online platform for housing over a time span from 2016 to 2020 is used in a hedonic regression approach. Additionally, to extract the marginal costs of energy consumption abatement, a dataset of 1.048 rental units regarding green-retrofit measures is utilized. While a significant green premium is identified in the rental market, the findings suggest that it is not high enough to compensate landlords for the money they have to spend to retrofit. The marginal costs exceed the marginal benefits by far. Furthermore, it is found that the German government’s recent plans to split the CO2 tax between landlords and tenants does not change this because the price per metric ton of carbon is insufficiently high. The findings can help both tenants and landlords in their decision-making, as well as policy makers in the implementation of decarbonization efforts.

Pricing office rents in Sydney CBD: testing the water on automated rent reviews

PurposeAutomated valuation models (AVMs) are statistical asset pricing models omnipresent in residential real estate markets, where they inform property tax assessment, mortgage underwriting and marketing. Use of these asset pricing models outside of residential real estate is rare. The purpose of the paper is to explore key characteristics of commercial office lease contracts and test an application in estimating office market rental prices using an AVM.Design/methodology/approachThe authors apply a semi-log ordinary least squares hedonic regression approach to estimate either contract rent or the total costs of occupancy (TOC) (“grossed up” rent). Furthermore, the authors adopt a training/test split in the observed leasing data to evaluate the accuracy of using these pricing models for prediction. In the study, 80% of the samples are randomly selected to train the AVM and 20% was held back to test accuracy out of sample. A naive prediction model is used to establish accuracy prediction benchmarks for the AVM using the out-of-sample test data. To evaluate the performance of the AVM, the authors use a Monte Carlo simulation to run the selection process 100 times and calculate the test dataset's mean error (ME), mean absolute error (MAE), mean absolute percentage error (MAPE), median absolute percentage error (MdAPE), coefficient of dispersion (COD) and the training model's r-squared statistic (R2) for each run.FindingsUsing a sample of office lease transactions in Sydney CBD (Central Business District), Australia, the authors demonstrate accuracy statistics that are comparable to those used in residential valuation and outperform a naive model.Originality/valueAVMs in an office leasing context have significant implications for practice. First, an AVM can act as an impartial arbiter in market rent review disputes. Second, the technology may enable frequent market rent reviews as a lease negotiation strategy that allows tenants and property owners to share market risk by limiting concerns over high costs and adversarial litigation that can emerge in a market rent review dispute.

The Application of Machine Learning Approaches on Real-Time Apartment Prices in the Tokyo Metropolitan Area

AbstractThe widely applied hedonic regression approach for the relationship between property prices and housing attributes is subject to assumptions and specifications of models as well as the availability and content of second-hand official data. In a cross-disciplinary spirit, this study employs machine learning techniques to examine hedonic apartment prices in the Tokyo Metropolitan Area of Japan based on online sales data extracted by web-parsing technology. With 14,579 apartment observations, two machine learning regressions—decision tree (DT) and random forest (RF)—are compared to conventional ordinary least squares regression (OLS) for hedonic modelling. Empirical results demonstrated that RF regressions led to the highest accuracy in model prediction performance, followed by DT and OLS. The comparison with results across models revealed that the housing features that have consistent influences on apartment prices tend to be those associated with living quality (including management funds, repair fund fees, floor size, located floor, total floor of the building, and location in Tokyo). Other commonly appreciated features, such as southward orientation or corner-lot location, did not demonstrate importance, possibly due to changes in residents’ preferences. In this big-data era, the adaptation of real-time data and machine learning approaches should add value to the variable selection process and model performance.

Towards the hedonic modelling and determinants of real estates price in Morocco

In this paper, we propose a new approach to modeling a real estate price index in Morocco, based on the hedonic regression approach. The basic idea of this paper is to verify the importance of the characteristics of the real estate in the real estate price. Thus, based on data from the three major cities of the capital region of Morocco (RABAT Region), we estimated a hedonic model that takes into account spatial autocorrelation. The results obtained through this modeling generally confirm that the surface area and location of the real estate (land, house, villa and apartment) have a significant influence on the price of real estate.

Estimating the impact of crime risk on housing prices in Malaysia

PurposeThe purpose of this study is to examine the impact of crime risk on housing prices at a national level in Malaysia during the period from 1988 to 2016.Design/methodology/approachA hedonic regression approach was used to estimate the Malaysian households’ valuation for crime risk. Specifically, the state-level property index on the state-level reported crime rate was regressed while controlling for state-level socioeconomic variables. The macroeconomic panel nature of the data set provides the merit to use a panel dynamic model instead of the traditional static panel data techniques (fixed effects or first difference).FindingsPanel dynamic estimators consistently show a negative impact of crime risks on housing prices. The estimated elasticity of housing prices with respect to crime risks ranges from −0.141 to −0.166, in line with existing literature using micro level data. In fact, householders in crime hotspot states are willing to pay more for crime reduction compared to householders in non-hotspot states. The willingness to pay has also increased since the implementation of nationwide crime reduction plans in 2010.Research limitations/implicationsThis is the first study that has examined the Malaysian people’s willingness to pay to reduce crime. This information is important in determining the optimal level of government expenditures for public safety.Originality/valueThis is the first study to examine the relationship between crime rates and housing prices in Malaysia. This study contributes to the literature by examining the impact of crime rates on housing prices at a national level by using panel dynamic models. The macro level data results are consistent and complement the existing literature based on micro level data.

Landscape view, height preferences and apartment prices: evidence from major urban areas in Indonesia

PurposeLandscape view is a crucial factor in house-buying decisions. Landscape views provide an amenity to residents, and this can influence the house or apartment owners in their residence decisions. Yet, the relative value of different types of view potentially differs. Additionally, the value of each type of view may differ depending on an apartment’s elevation above the ground level. In this study, the authors aim to estimate the value of landscape views on apartment prices in major urban areas in Indonesia.Design/methodology/approachThis paper evaluates to what extent various landscape views including mountain, sea, river, lake, street, urban village, garden and sports center views affect apartment prices in major urban areas in Indonesia. Two hedonic regression approaches are used: ordinary least squares and semiparametric regression. The latter is used to accommodate a possible non-linearity in the relationship between price and apartment characteristics. The model also incorporates housing and locational characteristics as control variables.FindingsUsing online apartment market data, the estimates in this paper show some degree of heterogeneity in the value of various views to the extent of providing negative externalities. Mountain, street and sports center views are associated with higher apartment prices. Sea, lake and garden views are statistically insignificant in explaining the prices. In contrast, the unappealing nature of the rivers and their surrounding creates a negative impact on prices. The estimates also suggest that an apartment’s floor height plays a significant role in the valuation of views.Originality/valueThere is little research on landscape view effects on apartment prices, especially in Indonesia. In addition, the relationship between the value of views and height preferences has seldom been analyzed. This paper provides the valuation of an extensive list of landscape views in urban areas in Indonesia. The estimation results also suggest that the value of views may differ depending on the floor on which an apartment lies.

Green pay off in commercial real estate in Germany: assessing the role of Super Trophy status

PurposeBased on a hedonic regression approach, the purpose of this paper is to relativize existing green pay off evidence by incorporating Super Trophy as a so far underrepresented determinant. The authors analyze a private panel database of 160 European office properties and confirm a significant green pay off; the positive impact of excellent environmental certification results on market values and net rents is significantly reduced when considering Super Trophy characteristics.Design/methodology/approachBased on a panel database of 160 European office properties, the survey applies a hedonic regression approach including an extensive set of control factors as, for example, location criteria, general property characteristics, climate adjustments, consumption data, refurbishment activities, green leases, sustainable certification and energy performance certificate figures.FindingsEven though our database still confirms a significant green pay off, the positive impact of excellent environmental certification results on market values and net rents is significantly reduced when controlling for Super Trophy characteristics.Practical implicationsEspecially, the question how sustainability can be integrated into real estate appraisal is of major interest. The paper at hand may help in two aspects: on the one hand, it provides further insight with regard to the quantitative impact of Super Trophy Buildings on rents and market values. On the other hand, a higher transparency in appraisals may result in structural specifications that help to consolidate appraisals and empirical evidence on a “green pay off.”Originality/valueThe study investigates a niche segment – landmark properties. The empirical analysis explicitly controls for potential Super Trophy status. It draws attention to the importance of a reasonable and complete set of control variables to increase statistical validity of future studies in that field.

Do urban tourism hotspots affect Berlin housing rents?

PurposeThis study aims to analyze whether urban tourism affects Berlin housing rents. Urban tourism is of considerable economic importance for many urban destinations and has developed very strongly over the past few years. The prevailing view is that urban tourism triggers side-effects, which affect the urban housing markets through a lack of supply and increasing rents. Berlin represents Germany’s largest rental market and is particularly affected by growing urban tourism and increasing rents.Design/methodology/approachThe paper considers whether urban tourism hotspots affect Berlin’s housing rents, using two hedonic regression approaches, namely, conventional ordinary least squares (OLS) and generalized additive models (GAM). The regression models incorporate housing characteristics as well as several distance-based measures. The research considers tourist attractions, restaurants, hotels and holiday flats as constituents of tourism hotspots and is based on a spatial analysis using geographic information systems (GIS).FindingsThe results can be regarded as a preliminary indication that rents are, indeed, affected by urban tourism. Rents seem to be positively correlated with the touristic attractiveness of a particular location, even if it is very difficult to accurately measure the real quantity of the respective effects of the urban tourism amenities, as the various models show. GAM outperforms the results of OLS and seems to be more appropriate for spatial analysis of rents across a city.Originality/valueTo the best of the authors’ knowledge, the paper provides the first empirical analysis of the effects of urban tourism hotspots on the Berlin housing market.

Household-specific housing capital gains and consumption: Evidence from Canadian microdata

This paper analyzes how household consumption decisions respond to accrued capital gains on owner-occupied housing using Canadian microdata. It makes an important methodological contribution by utilizing a hedonic regression approach to estimate household-specific capital gains instead of relying on house-price indices and other proxy measures that have been widely used in earlier literature. The results suggest that household consumption expenditures are increasing in the level of accrued capital gains on housing, and that the sustainability of these gains is important for the magnitude of this relationship. When the level of accrued capital gains is persistent over time, total household consumption increases by approximately 5.4 cents for every dollar of permanent capital gains and non-durable consumption increases by approximately 3.9 cents. Estimates of marginal propensity to consume for households in different age categories and other subgroups are also presented.

Feedback reviews and bidding in online auctions: An integrated hedonic regression and fuzzy logic expert system approach

In online auctions, user-generated feedback reviews provide first-hand information on the trustworthiness of transaction partners to the community. To examine how the feedback reviews are taken into account of the buyers' bidding decisions and thus affect the final winning price of an auction, we thoroughly examine how buyers mentally interpret the seller's reviews and adjust the bids accordingly. With ample bidding results data from a popular auction website eBay.com, this paper adopts an integrated approach of Fuzzy Logic Expert System (FLES) model and a statistical hedonic regression model to examine the research question. In particular, we use the hedonic regression approach to select key variables, which are then entered into a FLES analysis to generate knowledge base regarding the relationships between variables such as item characteristics, auction characteristics and review scores, and the final winning price. This integrated approach combines the advantages of both methods, and also overcomes their own limitations. In addition, we also present the insights gained from bidding behaviors utilizing each of the approaches.

The dynamics of brand equity: a hedonic regression approach to the laser printer market

The authors develop a dynamic hedonic regression approach to measuring the evolution of a comparative brand premium (pairwise price difference between two products that are identical in all respects apart from the brand). In contrast to existing approaches, the proposed Bayesian estimation method exploits the premia's intertemporal dependence structure, resulting in a higher level of accuracy of the estimated time paths of the brand premia. In addition, the authors present a novel, but straightforward way to construct confidence bands that cover the entire time series of brand premia with high probability. The authors apply their approach to a large, detailed data set on laser printers, which was gathered on a monthly basis over a 4-year period.

The “Right” Price for Art Collectibles: A Quantile Hedonic Regression Investigation of Picasso Paintings

Different art objects are likely to be priced by means of different systems of hedonic characteristics; more precisely, different evaluation procedures for high- and low-price items are often postulated. However, the empirical evidence on this point is scant. The purpose of this article is to fill this gap with a quantile hedonic regression approach. Using a dataset of 716 Picasso paintings sold at auction worldwide, the authors highlight the critical role of the price classes in determining the evaluation criteria of art items.

The “Right” Price for Art Collectibles:A Quantile Hedonic Regression Investigation of Picasso Paintings

Different art objects are likely to be priced by means of different systems of hedonic characteristics; more precisely, different evaluation procedures for high and low price items are often postulated. However, the empirical evidence on this point is scant. The main purpose of this paper is to fill this gap by using the quantile hedonic regression approach. The empirical evidence, based on a data set of 716 Picasso paintings sold at auction worldwide, highlights the critical role of the price classes in determining the evaluation criteria of art items.

The External Neighborhood Effects of Low-Income Housing Tax Credit Projects Built by Three Sectors

ABSTRACT:This study examines the external neighborhood effects of Low-Income Housing Tax Credit (LIHTC) Projects built in Santa Clara County, California from 1987 to 2000. Three types of developers have built LIHTC projects in this area: nonprofit, for-profit, and a county public housing authority. Using a difference-in-difference hedonic regression approach, this study finds that almost all the LIHTC projects examined have generated significantly positive impacts on nearby property value. In particular, the study also finds that most nonprofit projects have delivered benefits similar to those of for-profit projects. Yet projects built by some of the largest nonprofits and the county housing authority have generated the greatest neighborhood impacts. Low-income neighborhoods have also benefited more from LIHTC developments than other types of neighborhoods.

Enterprise in orbit: The supply of communication satellites

This study develops a general understanding of the evolution of the Western World commercial communication sate-llite supply industry. Initial information classifies this industry as an oligopoly with the vendors as price setters. Over three generations, the technical attributes of communication satellites are advancing. Taking the hedonic regression approach, the customer’s willingness to pay for characteristics is calculated. Exploring the relationship between price and complexity, it is demonstrated that in the short run, the oligopoly structure of this industry is accompanied by a simple form of cost plus price setting, whereas in the long run, the engineering satellite pricing ‘rule of thumb’ applies.

Casemix funding for a specialist paediatrics hospital: a hedonic regression approach.

This paper inquires into the effects that Diagnosis Related Groups (DRGs) have had on the ability to explain patient-level costs in a specialist paediatrics hospital. Two hedonic models are estimated using 1996/97 New Children's Hospital (NCH) patient level cost data, one with and one without a casemix index (CMI). The results show that the inclusion of a casemix index as an explanatory variable leads to a better accounting of cost. The full hedonic model is then used to simulate a funding model for the 1997/98 NCH cost data. These costs are highly correlated with the actual costs reported for that year. In addition, univariate regression indicates that there has been inflation in costs in the order of 4.8% between the two years. In conclusion, hedonic analysis can provide valuable evidence for the design of funding models that account for casemix.

The Duration of Marketing Time of Residential Housing

The marketing of unique durable goods such as housing presents a good example for the application of search theory. An optimal stopping rule strategy is employed to model sellers' behavior. The primary hypothesis is that the greater the atypicality of a house, the greater the expected variance of offers. Because a maximizing seller will wish to entertain more offers the greater is the variance, the marketing time of atypical houses will be relatively longer than that of standard houses. Using a sample of resale houses, the empirical study uses a failure time model to confirm the hypothesis. Extensions are mentioned, including discussions of the role of the list price and the limitations of the standard hedonic regression approach when applied to housing.

Automobiles and Hedonic Quality Measurement

Are price indexes biased upward because of quality change? One of the few pieces of firm evidence on this question is the study by Zvi Griliches (1961, 1964), who concluded that almost all of the recorded rise in the new automobile component of the Consumer Price Index (CPI) between 1954 and 1960 could be attributed to substantial improvement in the quality of automobiles. In view of the ubiquity of the quality problem in index number construction and the paucity of knowledge on the nature and extent of quality change, it is not surprising that Griliches' findings have been cited extensively in support of the charge that there is serious upward bias in our price indexes because of failure to make sufficient allowance for quality improvement. The present paper is devoted to further consideration of the problem. For the 1960-65 period, it is found that the Hedonic measures employed by Griliches indicate negligible quality improvement in automobiles and provide no substantiation for the belief in an upward quality bias in the CPI. However, certain biases in the Hedonic indexes themselves limit their validity as measures of quality change.