Robust hedonic price indexes

2016 ◽  
Vol 9 (1) ◽  
pp. 47-65 ◽  
Author(s):  
Steven C Bourassa ◽  
Eva Cantoni ◽  
Martin Hoesli
Keyword(s):  
House Price ◽  
Ordinary Least Squares ◽  
Robust Methods ◽  
Hedonic Price ◽  
Omitted Variables ◽  
Systematic Analysis ◽  
Content Type ◽  
Robust Techniques ◽  
Price Indexes ◽  
Hedonic Indexes

Purpose – The purpose of this paper is to demonstrate the application of robust techniques to the estimation of hedonic house price indexes. Design/methodology/approach – The authors use simulation analysis to compare an index estimated using ordinary least squares (OLS) with several indexes estimated using robust techniques. The analysis uses sales transactions data from a US city. The authors then explore how robust methods can correct for omitted variables under some circumstances and how they affect the revision problem that occurs when longitudinal hedonic indexes are updated. Findings – Robust methods can resolve missing variable problems in some circumstances and also can substantially reduce the revision problem in longitudinal hedonic indexes. Practical implications – Robust techniques may be preferable to OLS when constructing longitudinal hedonic indexes. Originality/value – This is the first paper to undertake a systematic analysis of the applicability of robust techniques in constructing hedonic house price indexes.

Income capitalisation method and hedonic model: an integrated approach

2019 ◽  
Vol 37 (3) ◽  
pp. 289-300
Author(s):  
Gaetano Lisi
Keyword(s):  
Real Estate ◽  
Discount Rate ◽  
House Price ◽  
Integrated Approach ◽  
Hedonic Model ◽  
Alternative Methods ◽  
Hedonic Price ◽  
Hedonic Prices ◽  
Content Type ◽  
Pull Out

Purpose The purpose of this paper is to provide an integrated approach that combines the two methods usually used in the real estate appraisals, namely, the income capitalisation method and the hedonic model. Design/methodology/approach In order to pull out the link between the income capitalisation approach and the hedonic model, the standard hedonic price function is introduced into the basic model of income capitalisation instead of the house market value. It follows that, from the partial derivative, a direct relation between hedonic prices and discount rate can be obtained. Finally, by using the close relationship between income capitalisation and direct capitalisation, a mathematical relation between hedonic prices and capitalisation rate is also obtained. Findings The developed method allows to estimate the capitalisation rate using only hedonic prices. Indeed, selling and hedonic prices incorporate all of the information required to correctly estimate the capitalisation rate. Furthermore, given the close relation among going-in and going-out capitalisation rates and discount rate, the proposed method could also be useful for determining both the going-out capitalisation rate and the discount rate. Practical implications Obviously, it is always preferable to estimate the capitalisation rate by just using comparable transactional data. Nevertheless, the method developed in this paper is especially useful when: the rental income data are missing and/or not entirely reliable; the data on rental income and house price are related to different homes; the capitalisation rate, in fact, should compare the rent and value of identical homes. In these cases, therefore, the method can be a valuable alternative to direct estimation. Originality/value The large and important literature on real estate economics and real estate appraisal neglects the relationship between hedonic prices and capitalisation rate, thus considering the hedonic model and the income capitalisation approach as two separate and alternative methods. This paper, instead, shows that integration is possible and relatively simple.

A housing price index with the improvement-value adjusted repeated sales (IVARS) method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chung Yim Edward Yiu ◽  
Ka Shing Cheung
Keyword(s):  
Price Index ◽  
Simulation Analysis ◽  
House Price ◽  
Housing Price ◽  
Housing Quality ◽  
Repeat Sales ◽  
Open Market ◽  
Hedonic Price ◽  
Content Type ◽  
Price Movements

Purpose The repeat sales house price index (HPI) has been widely used to measure house price movements on the assumption that the quality of properties does not change over time. This study aims to develop a novel improvement-value adjusted repeat sales (IVARS) HPI to remedy the bias owing to the constant-quality assumption. Design/methodology/approach This study compares the performance of the IVARS model with the traditional hedonic price model and the repeat sales model by using half a million repeated sales pairs of housing transactions in the Auckland Region of New Zealand, and by a simulation approach. Findings The results demonstrate that using the information on improvement values from mass appraisal can significantly mitigate the time-varying attribute bias. Simulation analysis further reveals that if the improvement work done is not considered, the repeat sales HPI may be overestimated by 2.7% per annum. The more quality enhancement a property has, the more likely it is that the property will be resold. Practical implications This novel index may have the potential to enable the inclusion of home condition reporting in property value assessments prior to listing open market sales. Originality/value The novel IVARS index can help gauge house price movements with housing quality changes.

The outcome of online social interactions on Facebook pages

2019 ◽  
Vol 29 (1) ◽  
pp. 2-23 ◽  
Author(s):  
Hamid Khobzi ◽  
Raymond Y.K. Lau ◽  
Terence C.H. Cheung
Keyword(s):  
Social Interactions ◽  
Panel Data Analysis ◽  
Message Framing ◽  
Theoretical Models ◽  
Ordinary Least Squares ◽  
Omitted Variables ◽  
Content Type ◽  
Engagement Behavior ◽  
Facebook Pages ◽  
The Impact

Purpose The purpose of this paper is to investigate the impact of different ways of message framing on users’ engagement behavior regarding the brand posts on Facebook and to determine whether users’ thumbs-up and reply moderate this impact. Design/methodology/approach A panel data analysis was conducted on a panel with 11,894 observations on 850 unique brand posts from the Facebook pages of the world’s most valuable brands over a seven days window with two observations each day. A system of equations was estimated using ordinary least squares, Hausman–Taylor IV and seemingly unrelated regressions to test study’s hypotheses. Findings The empirical findings confirm that more positively and negatively framed comments result in increased users’ engagement. Also, an increase in thumbs-up ratio for neutrally and negatively framed comments results in less engagement. The reply ratio might also have a positive and negative moderation effect on the influence of neutrally and positively framed comments on engagement behavior, respectively. Practical implications This study provides an in-depth understanding of online social interactions on Facebook pages for firms’ managers and marketers. Online social interactions might be either harmful or fruitful for firms depending on the type of interaction and engagement behavior. Findings can help managers and marketer to improve their strategies for leveraging Facebook for electronic marketing. Originality/value This is likely to be the first study that examines the moderating effect of users’ thumbs-up and reply on the relationship between message framing and users’ engagement behavior. By providing robust findings by addressing issues like omitted variables and endogeneity, the findings of this study are promising for developing new hypotheses and theoretical models in the context of online social interactions.

scholarly journals Which aspects of CSR predict firm market value?

2018 ◽  
Vol 2 (1) ◽  
pp. 50-69 ◽  
Author(s):  
Stevan Bajic ◽  
Burcin Yurtoglu
Keyword(s):  
Firm Value ◽  
Fixed Effects ◽  
Market Value ◽  
Ordinary Least Squares ◽  
Specific Aspect ◽  
Social Dimension ◽  
Omitted Variables ◽  
Firm Level ◽  
Content Type ◽  
The Social

Purpose There is evidence that corporate social responsibility (CSR) practices predict higher firm value, but little evidence on which specific aspects of CSR drive this relationship. The purpose of this paper is to study this question in a sample drawn from 35 countries over 2003-2016. Design/methodology/approach The authors employ a research design that analyzes observational data with panel data methods including ordinary least squares, firm-random effects, and firm-fixed effects. Findings The authors find in a sample drawn from 35 countries over 2003-2016 an economically significant relationship between an overall CSR measure and firm value. The overall CSR score builds on data from Asset4 and is comprised of three indices for environmental, social, and corporate governance aspects of CSR. The authors find that the social index consistently predicts higher market value. The authors also show that the use of particular elements of CSR can lead to substantial omitted variables bias when predicting firm value. The results also suggest a similar bias in studies that focus on a single index, which captures a specific aspect of CSR, but omits the remaining aspects. Research limitations/implications The study is subject to limitations common to observational studies. Practical implications The authors find robust evidence that CSR predicts market value using a country-benchmarked overall CSR index. The power to predict firm value comes solely from the social dimension of this measure, which captures firm-level practices related to treatment of employees and stakeholder relations including those with customers and the broader community. Three elements drive the social index: customer/product responsibility, human rights, and employment quality. None of the remaining 12 elements significantly predicts firm vale in an empirical setting with firm-FE and extensive covariates. The authors also show that omitted aspects of CSR can easily lead to an omitted variable bias and that the magnitude of this bias is potentially greater with an OLS specification. Social implications Among the many dimensions of CSR, only a subset drives firm value. Policies that target to improve the CSR performance of firms adopt a broader definition of CSR. Originality/value The authors provide first-hand evidence on which specific aspects of CSR drive firm market value.

scholarly journals House prices and neighbourhood amenities: beyond the norm?

2018 ◽  
Vol 11 (2) ◽  
pp. 263-289 ◽  
Author(s):  
Michael James McCord ◽  
Peadar Thomas Davis ◽  
Paul Bidanset ◽  
William McCluskey ◽  
John McCord ◽  
...  
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Ordinary Least Squares ◽  
Content Type ◽  
Conditional Quantiles ◽  
Price Distribution ◽  
Regression Techniques ◽  
High Level ◽  
The Impact

Purpose Understanding the key locational and neighbourhood determinants and their accessibility is a topic of great interest to policymakers, planners and property valuers. In Northern Ireland, the high level of market segregation means that it is problematic to understand the nature of the relationship between house prices and the accessibility to services and prominent neighbourhood landmarks and amenities. Therefore, this paper aims to quantify and measure the (dis)amenity effects on house pricing levels within particular geographic housing sub-markets. Design/methodology/approach Most hedonic models are estimated using regression techniques which produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price. This paper uses a quantile regression (QR) approach that provides a “more complete” depiction of the marginal impacts for different quantiles of the price distribution using sales data obtained from 3,780 house sales transactions within the Belfast Housing market over 2014. Findings The findings emerging from this research demonstrate that housing and market characteristics are valued differently across the quantile values and that conditional quantiles are asymmetrical. Pertinently, the findings demonstrate that ordinary least squares (OLS) coefficient estimates have a tendency to over or under specify the marginal mean conditional pricing effects because of their inability to adequately capture and comprehend the complex spatial relationships which exist across the pricing distribution. Originality value Numerous studies have used OLS regression to measure the impact of key housing market externalities on house prices, providing a single estimate. This paper uses a QR approach to examine the impact of local amenities on house prices across the house price distribution.

House prices and superstition among ethnic Chinese and non-Chinese homebuyers in Auckland, New Zealand

2018 ◽  
Vol 11 (1) ◽  
pp. 34-44 ◽  
Author(s):  
Michael Rehm ◽  
Shuzhen Chen ◽  
Olga Filippova
Keyword(s):  
New Zealand ◽  
House Prices ◽  
House Price ◽  
Hedonic Price ◽  
Content Type ◽  
Financial Investment ◽  
Ethnic Chinese ◽  
Hedonic Price Analysis ◽  
Price Effects ◽  
Over Time

Purpose Numerical superstition is well-known in Asian countries and can influence decision-making in many markets, from financial investment to purchasing a house. This study aims to determine the house price effects of superstition and understand if these have changed over time. Design/methodology/approach Using sales transactions of freestanding houses in Auckland, New Zealand, the authors use hedonic price analysis to investigate whether superstitious beliefs associated with lucky and unlucky house numbers affect property values. Findings The analysis reveals ethnic Chinese buyers in Auckland displayed superstitious home buying behaviour in the period 2003-2006 by attributing value to homes with street addresses starting or ending with the lucky number eight. However, this willing to pay higher prices for lucky numbers was not reflected in the analysis of 2011-2015 sales transactions. The disappearance of superstition price effects may indicate that ethnic Chinese in the Auckland housing market have, over time, assimilated New Zealand’s Western culture and have become less superstitious. Originality/value Unlike previous studies, the authors parse buyers into two populations of homebuyers, ethnic Chinese and non-Chinese purchasers, and model the two groups’ housing transactions independently to more accurately establish if numerical superstition influences house prices.

A Reconsideration of Hedonic Price Indexes with an Application to PC’s

2003 ◽  
Vol 93 (5) ◽  
pp. 1578-1596 ◽  
Author(s):  
Ariel Pakes
Keyword(s):  
Empirical Study ◽  
Hedonic Price ◽  
Price Changes ◽  
Market Values ◽  
Price Indexes ◽  
Hedonic Indexes ◽  
The Right

This paper compares hedonic to matched model indexes. Matched model indexes are averages of the price changes of goods that remain on sampled stores’ shelves. Since goods that disappear tend to have falling market values, matched model indexes select from the right tail of price changes. The BLS can construct hedonic indexes that correct for this selection and are justified by standard arguments. In an empirical study of PC’s hedonics produce sharp price declines while matched model indexes are near zero. Also, though there are modifications to hedonics that seem desirable, they are not those in current use.

scholarly journals Impact of crime on spatial analysis of house prices: evidence from a UK city

2016 ◽  
Vol 9 (4) ◽  
pp. 627-647 ◽  
Author(s):  
David McIlhatton ◽  
William McGreal ◽  
Paloma Taltavul de la Paz ◽  
Alastair Adair
Keyword(s):  
Spatial Analysis ◽  
House Prices ◽  
Spatial Association ◽  
House Price ◽  
Spatial Effects ◽  
Hedonic Price ◽  
Spatial Autoregression ◽  
Spatial Error ◽  
Content Type ◽  
The Impact

Purpose There is a lack of understanding in the literature on the spatial relationships between crime and house price. This paper aims to test the impact of spatial effects in the housing market, how these are related to the incidence of crime and whether effects vary by the type of crime. Design/methodology/approach The analysis initially explores univariate and bivariate spatial patterns in crime and house price data for the Belfast Metropolitan Area using Moran’s I and Local Indicator Spatial Association (LISA) models, and secondly uses spatial autoregression models to estimate the role of crime on house prices. A spatially weighted two-stage least-squares model is specified to analyse the joint impact of crime variables. The analysis is cross sectional, based on a panel of data. Findings The paper illustrates that the pricing impact of crime is complex and varies by type of crime, property type and location. It is shown that burglary and theft are associated with higher-income neighbourhoods, whereas violence against persons, criminal damage and drugs offences are mainly associated with lower-priced neighbourhoods. Spatial error effects are reduced in models based on specific crime variables. Originality/value The originality of this paper is the application of spatial analysis in the study of the impact of crime upon house prices. Criticisms of hedonic price models are based on unexplained error effects; the significance of this paper is the reduction of spatial error effects achievable through the analysis of crime data.

scholarly journals The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Graham Squires ◽  
Don Webber ◽  
Hai Hong Trinh ◽  
Arshad Javed
Keyword(s):  
New Zealand ◽  
House Prices ◽  
House Price ◽  
Empirical Work ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Content Type ◽  
Lag Effects ◽  
Long Run ◽  
Lag Variables

Purpose The purpose of this paper is to examine the relationship between house price affordability (HPA) and rental price affordability (RPA) in New Zealand. The cointegration of HPA and RPA is of particular focus given rising house prices and rising rents. Design/methodology/approach The study examines the lead-lad correlation between HPA and RPA. The method uses a generalised least square technique and the development of an ordinary least squares model. Findings The study shows that there is an existence of cointegration and unidirectional statistical causality effects between HPA and RPA across 11 regions in New Zealand. Furthermore, Auckland, Wellington and Canterbury are the three regions in which the results detect the most extreme effects amongst HPA and RPA compared to other places in the country. Extended empirical work shows interesting results that there are lead-lag effects of HPA and RPA on each other and on mortgage rates at the national scale. These effects are consistent for both methods but are changed at individual lead-lag variables and amongst different regions. Originality/value The study empirically provides useful insight for both academia and practitioners. Particularly in examining the long-run effects, cointegration and forecasting of the volatile interactions between HPA and RPA.

A systematic analysis of the spatial migration patterns and the linkages between market components in Greater Manchester, United Kingdom

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Le-Vinh-Lam Doan ◽  
Adipandang Yudono
Keyword(s):  
Housing Market ◽  
Metropolitan Area ◽  
Systems Approach ◽  
House Price ◽  
Market Area ◽  
Systematic Analysis ◽  
Migration Patterns ◽  
Content Type ◽  
Price Data ◽  
Large Metropolitan Area

Purpose This paper aims to bring together research on housing market area, submarket and household migration into a systems approach that helps us gain a better understanding of the structure and dynamics of a housing market and identify housing problems for a large metropolitan area. Design/methodology/approach The paper uses a geographic information system (GIS)-based method with simple quantitative techniques, including spatial analysis, location analysis, house price clustering and cross-tabulation. The analysis is based on migration data from the 2011 Census, house price data from the Land Registry in 2011 for Greater Manchester at the ward level and the output areas level. Findings The results show that different submarkets and housing market areas had different patterns of spatial migration and connections with other areas. Through a systematic analysis of migration and house price in combination, it also found a close connection between destination submarkets and the ages of migrants and identified specific problematic patterns for a large metropolitan area. Research limitations/implications The interactions between the owner-occupied sector and the social and private rented sectors are arguably an important omission from the analysis. Also, it is acknowledged that clustering ward units based on price differentials is subject to distortions in terms of specification, size and shape. Moreover, the use of the large samples may result in very small p-values, leading to the problem of the rejection of the predefined hypothesis. Practical implications A systematic analysis of migration and house price in combination may be used to gain a better understanding of the housing market dynamics and identify housing problems systematically for a large metropolitan. It may help to identify low-demand areas, high-demand areas and assist planners with decisions in allocating suitable land for new housing constructions. Social implications The GIS-based method introduced in the paper could be considered as an effective approach to provide a better basis for determining policy interventions and public investment designed to allocate land resources effectively and improve transport systems to change existing problematic migration patterns. Originality/value This paper fills a gap in the international literature in relation to adopting a systems approach that analyses migration and house price data sets in combination to systematically explore migration patterns and linkages and identify housing problems for a large metropolitan area. This systems approach can be applied in any metropolitan area where migration and house price data are available.

Sign in / Sign up

Export Citation Format

Share Document