Hedonic Price Research Articles

The Impact of the Type and Abundance of Urban Blue Space on House Prices: A Case Study of Eight Megacities in China

Urban blue spaces (UBS) have been shown to provide a multitude of cultural ecosystem services to urban residents, while also having a considerable impact on the surrounding community’s house prices. However, the impact of different types of UBS and the effect of their abundance on house prices have been largely understudied. This study aims to address this gap by examining the impact of different types of UBS on house prices using eight megacities in China as a case study. Spatial hedonic price models are developed to assess the impact of different types of UBS on house prices, and differences in their impact across cities are identified. Variance partitioning analysis is also used to decompose the relative contributions of UBS variables and explore the relationship between UBS-attributable premiums and the abundance of UBS. The results indicate that lakes and the main river have a significant positive impact on house prices in most cities, while the impact of small rivers on house prices varies across cities. The influence of UBS variables differs significantly across cities, but these differences are not solely driven by the abundance of UBS. This study provides valuable information for UBS planning and management and contributes to the equitable distribution of urban public services.

Proximity to Neighborhood Services and Property Values in Urban Area: An Evaluation through the Hedonic Pricing Model

Neighborhood services, property attributes, and their associated amenities have positive impacts on land and property values. This impact is estimated by the hedonic pricing model, which is considered an effective method used in previous studies for such evaluations. The study uses Geographical Information Science by digitizing the point of interest in the study area for spatial modeling of data collection points and multi-linear regression as a statistical analysis of hedonic measurements. The hedonic measurements include the data of structural, locational, environmental, and community attributes of a property at a given time and space at a walkable distance from the neighborhood for measuring proximity. The results of the study are represented through the summary of the regression model, which expresses the impact of every individual variable on the entire value of the property, and the appropriateness of the results is shown by values R, R2, and adjusted R2. The result of the study concluded that property characteristics are varied from location to location, and that is why it is difficult to measure the exact market values, particularly in areas that lack urban planning and heterogeneous data. Research on such burning issues is essential for sustainable urban development.

Ready-to-Eat Innovative Legumes Snack: The Influence of Nutritional Ingredients and Labelling Claims in Italian Consumers’ Choice and Willingness-to-Pay

The global offer of legume-based snacks has sharply increased in recent years. However, to date, few studies have focused on the relationship between product supply and demand concerning the importance of attributes of such innovative foods. In this research, we identified the key internal and external determinants that affect legumes snack (LS) price and choice by Italian industries and consumers, respectively. In parallel, we investigated their preferences and perceptions towards these foods. We used the hedonic price model (HPM) and the discrete choice experiment (DCE) approach for these purposes, respectively. HPM revealed that the monetary value of LS was determined to greater significance by the: (i) size of the package; (ii) presence of rice, presence of lentils; (iii) presence of the nutritional information; and (iv) the discount shops as site of purchase. DCE revealed that the: (i) origin certification, (ii) recyclability of the package, and (iii) use of extra virgin olive oil of LS provided Italian consumers a high utility, for which they were willing to pay an average price premium of EUR 3.85, 3.64, and 1.87, respectively. On the contrary, the sunflower oil induced a decrease in their function utility. As such, this paper contributes to define potent market-segmentation strategies and to deliver effective private and public nutrition interventions for healthy eating.

Disentangle the price dispersion of residential solar photovoltaic systems: Evidence from Germany

Although Germany has the largest capacity of installed residential photovoltaic (PV) systems in Europe, comprehensive evidence on transparent pricing information remains missing. This study disentangles why PV quote prices are subject to significant dispersion and analyzes which factors influence particularly low- and high-priced systems in Germany. We create a comprehensive cross-sectional dataset of 19 561 PV system quotes from 2011 to 2022 and use regression analyses to investigate the effects of system characteristics, installation scope, and location-related parameters on quoted prices. Our results reveal highly volatile annual price dispersion consistent over 11 years and large price differences despite similar system characteristics. Applying hedonic regression techniques, we reveal spatially fine-resolved price heterogeneity with up to 20% difference in the German PV market. System characteristics such as battery usage, installation scope, and system capacity have the most significant effect sizes and are instead control variables. More insightful, the installer density shows price-lowering effects, whereas more PV installations per region, higher solar radiation, and higher labor wages cause price-increasing effects. Quantile regression results reveal that installer density promotes the price reduction of high-priced systems more. Scaffolding, AC installation, and elevation are significant price-increasing factors but with small effect sizes. Finally, DC optimizers affect the levels of high-priced systems more than low-priced ones.

Combining an agent-based model, hedonic pricing and multicriteria analysis to model green gentrification dynamics

Household mobility dynamics are a complex phenomenon due to the multi-faceted human-environment interactions involved. These dynamics are affected by a variety of variables, spanning economic, structural, political and environmental. With respect to this latter aspect, much research has explored the relationship between the development of urban green areas, the increase of price and the formation of gentrification. Within this context, the present work explores housing mobility and gentrification dynamics proposing a mixed-method approach that combines a spatially explicit agent-based model (ABM), a Multicriteria Decision Analysis (MCDA) and a Hedonic Price (HP). The case study of the transformation project of Victoria Park in Brisbane (Australia) is used to verify the applicability of this integrated approach. In the methodological framework proposed, the ABM simulates the housing mobility of the residents through an individual decision-making process, where the likelihood of mobility is based on various empirical endogenous factors (i.e., household socio-economic characteristics) and exogenous ones (i.e., market variation). The MCDA supports the identification of the relative importance of these factors using a panel of local experts and stakeholders. The Spatial HP explores the impact of urban parks on real estate prices. The current study found the abilities of MCDA and HP to reduce the assumptions of ABM by generating quali-quantitative information of citizens' behaviors and estimating price increase. Moreover, the model highlights the importance of considering both supply and demand sides when analyzing gentrification. The specific results of the case study show the influence of the park in the formation of green gentrification.

High‐Temperature Exposure and Land Transactions in China

AbstractWe estimate the relationship between high‐temperature exposure and land transaction using daily transaction data from 2013 to 2018 in China. Standard hedonic price method is used to perform multidimensional fixed effects regression on 458,564 transaction samples. This study shows that each additional day of the extremely high temperature increases the average bid price by 0.6%, which is equivalent to an additional annual increase of 15.018 billion yuan in land transaction costs. The effect of high temperature on land prices is considerably stronger for residential and commercial lands. We further find that high‐temperature‐induced changes of mood and cognition play a role. Extreme gradient boosting (XGBoost) algorithm is used to calculate price deviation, which overcome missing eigenvalues and reduce nonlinear measurement error. Our findings indicate that heat can make investors more aggressive, which occurs when bidders continue to raise prices to win. The number of bidding behavior will not drop due to the hidden costs of land transactions. Specially, bidding experience offsets the cognitive output bias. This study contributes to the behavioral finance and decision‐making literature, helps investors make better investment management decisions, and alleviates the negative effect of land transaction premium on the real estate market.

주택시장 하락기에 국제학교 입지가 아파트 매매 가격에 미친 영향

This study examines the effect of the Songdo International School on apartment sales prices in surrounding area during the downturn of the housing economy. It also compares the result with its effect in stable period of housing economy in surrounding area. The variables affecting the housing sales prices at the time of analysis are considered and the conventional hedonic price modeling is applied. As a result, the accessibility of the international school has a positive effect on the apartment sales prices regardless of housing market conditions. The effect of the accessibility of the international school is greater during the stable period than during the downturn period of housing economy. In addition, the effect of population inflow due to the international school is estimated as the result of the increase in the population of Songdo new town area and the increase in the proportion of the local population in Yeonsu-gu.

득수와 거수가 아파트 가격에 미치는 영향

This study analyzed how the direction of the gaining water and draining water in the apartment along the Jeong-neung stream in Dongdaemun-gu affect the apartment sales price using the Hedonic Price model. In this study, the dependent variable was the actual apartment sales price. As independent variables, the direction of water extraction and draining water , elapsed years, the trading floor, the number of apartments building, the distance subway station, elementary school, and middle school were used. As a result of the analysis, it was analyzed that the direction of gaining water, the higher number of elapsed years, the higher number of apartments building and the higher the trading floor had a positive (+) effect on apartment sales prices. In addition, it was analyzed that direction of the draining water and the farther the distance to the subway station, elementary school, and middle school, the negative (-) effect on the apartment sales price.

A spatial semiparametric M-quantile regression for hedonic price modelling

This paper proposes an M-quantile regression approach to address the heterogeneity of the housing market in a modern European city. We show how M-quantile modelling is a rich and flexible tool for empirical market price data analysis, allowing us to obtain a robust estimation of the hedonic price function whilst accounting for different sources of heterogeneity in market prices. The suggested methodology can generally be used to analyse nonlinear interactions between prices and predictors. In particular, we develop a spatial semiparametric M-quantile model to capture both the potential nonlinear effects of the cultural environment on pricing and spatial trends. In both cases, nonlinearity is introduced into the model using appropriate bases functions. We show how the implicit price associated with the variable that measures cultural amenities can be determined in this semiparametric framework. Our findings show that the effect of several housing attributes and urban amenities differs significantly across the response distribution, suggesting that buyers of lower-priced properties behave differently than buyers of higher-priced properties.

The Use of Machine Learning in Real Estate Research

This research seeks to demonstrate how machine learning, a branch of artificial intelligence, is able to deliver more accurate pricing predictions, using the real estate market as an example. Utilizing 24,936 housing transaction records, this paper employs Extra Trees (ET), k–Nearest Neighbors (KNN), and Random Forest (RF) to predict property prices and then compares their results with those of a hedonic price model. In particular, this paper uses a feature (property age x square footage) instead of property age in order to isolate the effect of land depreciation on property prices. Our results suggest that these three algorithms markedly outperform the traditional statistical techniques in terms of explanatory power and error minimization. Machine learning is expected to play an increasing role in shaping our future. However, it may raise questions about the privacy, fairness, and job displacement issues. It is therefore important to pay close attention to the ethical implications of machine learning and ensure that the technology is used responsibly and ethically. Researchers, legislators, and industry players must work together to create appropriate standards and legislation to govern the use of machine learning.

Consumer preferences for rice in East Africa

PurposeImproving the competitiveness of East Africa's rice industries necessitates increased and viable production of rice of the quality desired by consumers. This paper aims to understand consumer preferences for rice quality attributes in Uganda and Kenya to inform the countries' rice breeding programs and value chain development interventions.Design/methodology/approachRice samples are obtained from retail markets in various districts/counties across the two countries. The samples are analyzed in a grain quality laboratory for the rice's physicochemical characteristics and the resulting data are used to non-parametrically estimate hedonic price functions. District/county dummies are included to account for potential heterogeneity in consumer preferences.FindingsUgandan consumers are willing to pay a price premium for rice with a relatively high proportion of intact grains, but the consumers discount chalkiness. Kenyan consumers discount high amylose content and impurities. There is evidence of heterogeneity in consumer preferences for rice in Mbale, Butaleja and Arua districts of Uganda and in Kericho and Busia counties of Kenya.Originality/valueThe study makes a novel contribution to the literature on consumer preferences for rice in East Africa by applying a hedonic pricing model to the data generated from a laboratory analysis of the physicochemical characteristics of rice samples obtained from the market. Rather than base our analysis on consumers' subjective sensory assessment of the quality characteristics of rice, standard laboratory methods are used to generate the data, which enables a more objective assessment of the relationship between market prices and the quantities of attributes present in the rice samples.

The Impact of Water Body Restoration on the Sales and Rental Markets in Beijing

<h3>Abstract</h3> Black and odorous water bodies (BOWBs) are increasingly common in cities worldwide. This paper evaluates the impact of an urban water bodies restoration program in Beijing, China, based on detailed housing sale and rental transaction data. We implement a hedonic price model with a difference-in-difference and a triple difference approach and find that listing and restoration of a BOWB significantly increase house prices by 2.2-3.9 percent and 2.3-4.9 percent, respectively, while at the same time increase rents by 11.3-13.7 percent and 13.4-16.9 percent, respectively.

The Value of Craft Beer Styles: Evidence from the Italian Market.

This study aims to estimate the market value, or implicit prices, associated with the main craft beer attributes (e.g., beer style, organic, gluten-free, and package-related features) and support producers in detecting the more profitable marketing strategies. For this purpose, we conducted an empirical analysis employing sales data of craft beers from the Italian online market, and we estimated a hedonic price model via ordinary least squares. Results show that the type of package and cup only has moderate effects on price. Furthermore, a moderate premium price is found for gluten-free craft beers, while craft beers with organic labels and Italian origin do not benefit from the higher price. Instead, the beer style adopted strongly affected the product price: the highest premium prices were detected for Barleywine (+49.9%) and Italian Grape Ale (+39.6%) beer styles. Furthermore, relevant premium prices, higher than +25%, were estimated for other beer styles such as Sour, Fruit Beer, and Stout. Results suggest that artisanal breweries can effectively differentiate their product according to the beer style. To the best of our knowledge, the current study offers the first empirical evidence on how beer styles as well as other product characteristics affect the market price of craft beer by using secondary data.

Does the renovation of waste-to-energy incineration plants attenuate the housing price gradient? Evidence from a quasi-natural experiment in Shenzhen, China

Waste-to-energy (WTE) incineration plants, which inevitably cause negative externalities due to their impacts on the surrounding environment, have encountered frequent protests from residents during their construction and operation. The negative externalities could lead to property value losses by impacting residents' marginal willingness to pay (MWTP). To assess whether the renovation of WTE incineration plants can attenuate the housing price gradient around the plants, we use the completion of the renovation project of Yantian Plant in Shenzhen as a quasi-natural experiment to exploit difference-in-differences (DID) estimators, and propose a hedonic price model based on resale apartment transaction data within 10 km of the plant. Results indicate that the renovation completion narrows the price gap between proximate and distant apartments from the plant by 35.25%, and the housing price gradient begins to decrease significantly in the late construction period. Moreover, the effect on the housing price gradient remains sustained throughout the whole post-treatment period. Furthermore, the analysis of the underlying mechanism suggests that the renovation completion attenuates the housing price gradient through the improved environment.

Information, migration, and the value of clean air

Using a variant of the Rosen-Roback model of inter-city migration that incorporates public access to air quality information, we demonstrate that information constraints create a wedge between revealed and true hedonic prices for pollution that depends upon individuals’ perception biases. We empirically test our theoretical predictions by leveraging the unexpected disclosure of PM2.5 data in China. We find that migration decisions become much more responsive to pollution and that the hedonic price of avoiding PM2.5 exposure nearly doubles – from 171 to 336 Chinese Yuan – in response to the information shock. Our results highlight the role of imperfect information in migration decisions and its impact on non-market valuation in countries where public access to information is restricted.

Effects of Multifaceted Street Art on Price Premium of Pre War Commercial Buildings: The Case of Georgetown UNESCO World Heritage Site

Street art is promoted in most countries to intensify the cultural elements of the cityscape. Although street art provides cultural and social values, its impact on the prices of prewar historic property is still unknown. Therefore, an empirical study that examines the relationship between prewar shophouse prices and street art is needed to improve real estate professionals’ understanding of the historic preservation market. Using pre- and post-models for the years 2009 to 2019, this study systematically determined the actual location of 119 street art objects (in the form of sculptures and murals) and the 852 prewar shophouses sold in George Town, Penang. The price change of prewar shophouses correlates with the number of street art objects within 100 m, 500 m, and 1000 m of the properties. Due to the heterogeneous characteristics of the properties, six primary hedonic models were developed to extract the price premium of street art. This study has shown the impact of street art on a prewar commercial building, where an additional unit of sculpture could increase its price by 8.32%, 1.62%, and 0.74%, based on radii of 100 m, 500 m, and 1000 m, respectively, in the post-model (after 2012–2019). However, a mural painting has no significant effect on the price change of prewar shophouses. In addition, the position of street art (representing visibility) in the model was tested. The result shows that, unlike sculptures that were located at the back of prewar houses, such street art effects contributed positively to the price premium when they were located at the front of the buildings, with each additional unit of sculpture increasing the price premium of prewar houses by 1.13%. Sculptures as street art thus created a positive externality for the city, particularly with respect to the price premium for prewar shophouses.

The effect of proximity and spatial dependence on the house price index for Dar es Salaam

PurposeThis study aims to examine the effect of proximity and spatial dependence on the house price index for the nascent market Dar es Salaam, Tanzania. Despite the ongoing housing market transactions, there is no single house price index that takes into account proximity and spatial dependence. The proximity considerations in question are proximal to arterial roads, public hospitals, an airport and food markets. Previous studies on sub-Saharan Africa have focused on the ordinary least squares (OLS)-based hedonic model for the index and ignored spatial and proximity considerations.Design/methodology/approachUsing the OLS and spatial econometric approach, the paper tests for the significance of the two effects – proximity and spatial dependence in the hedonic price model with year dummy variables from 2010 to 2019. The paper then compares the three indices in the following configurations: without the two effects, with proximity factors only, and with both effects, i.e. proximity and spatial dependence.FindingsThe inclusion of proximity factors and spatial dependence – spatial autocorrelation – seems to improve the hedonic price model but does not significantly improve the house price index. However, further research should be called for on account of the nascent nature of the market.Originality/valueThe paper brings new knowledge by demonstrating that it may not be necessary to take into account proximity factors and spatial dependence for the Dar es Salaam house price index.

The impacts of pandemic on urban housing prices: evidence from the outbreak of COVID-19 in Beijing, 2020

PurposeThe COVID-19 pandemic has significantly raised economic risk and uncertainty worldwide. How does COVID-19 affect urban housing markets? Is there any difference when different areas encounter COVID-19? This study aims to investigate the impacts of the pandemic on housing prices by using Beijing’s housing markets data in 2020.Design/methodology/approachThe authors use transaction-level data from April to September in 2020 to conduct a hedonic price analysis of the housing markets in Beijing. The data included 70,843 transactions scraped from a real estate agent’s website. The authors use the difference-in-differences approach to evaluate the impacts of the COVID-19 outbreak from the Beijing Xinfadi market (the largest and most important food wholesale market in Beijing) in 2020.FindingsThis outbreak of COVID-19 caused a 6.3% drop in housing prices in Beijing from April to September in 2020. However, the impacts of COVID-19 on housing prices in different urban neighbourhoods were spatially heterogeneous. Housing prices in neighbourhoods with industries that rely on face-to-face communication were more affected by the pandemic, while those that can work remotely were less affected.Originality/valueBy investigating the impacts of COVID-19 on housing prices in Beijing, this study illustrates that urban housing prices would be impacted by the pandemic, at least in the short term. While the rise and fall of housing prices were found spatially heterogeneous in Beijing, it suggests that urban neighbourhoods with specific socioeconomic characteristics and geographic locations would unfold different resilience when encountering pandemic. By using data scraping and rigorous statistical tools, the study is probably one of the first ones examining the consequences of COVID-19 in intra-urban housing markets.

Urban property markets and security risk: explaining how neighborhood security shapes housing rental prices in Ojo Lagos, Nigeria

PurposeWhile the declining rate of urban security and its potential effects have been globally acknowledged, the ways urban neighborhood security shapes real estate markets in African cities remain largely unexplained. The purpose of this paper therefore is to present the findings from a study of the nexus between urban neighborhood security and home rental prices in Lagos, Nigeria.Design/methodology/approachThis paper is based on the hedonic price theory, an objectively derived urban neighborhood security index (UNSI) and property rental price data in Ojo, Lagos, Nigeria. This is a quantitative cross-sectional study that employs multistage sampling survey procedure. Data are analyzed using descriptive statistics, nonparametric correlation and hedonic price function with ordinary least squares (OLS).FindingsResults show that nearly 50% of the study area is prone to insecurity and average rental values in Ojo, Lagos range from N151329.41 ($302.66) to N167333.33 ($334.67) per annum. Correlation analysis shows that home rental prices have high, positive and significant correlations (rs = 0.725 and p < 0) with UNSI. After controlling for neighborhood and structural factors, it is found that urban neighborhood security positively influences home rental values as a unit improvement in security leads to N81000.00 ($162.00) increase in rental value per annum.Practical implicationsUrban neighborhood security risk threatens residential property values, creates unintended residential mobility and destabilizes families. Findings from this study point to the facts that security is a key component of urban housing values and developers, and real estate investors must ensure that this component is well factored into property design, construction and valuation.Originality/valueThis is perhaps the first study that uses an objectively derived UNSI to study home rental price dynamics in Nigeria. The study extends knowledge on urban housing price determinants and contributes to literature on the crucial place of security in property management.

Architectural Factors Influencing a Housing Market Value: A Theoretical Framework

ABSTRACT A housing price, not considering its change over time, is widely determined by hedonic properties. This is common in literature; however, there is a significant part of a price, the so-called unexplained variance, that is not captured by hedonic models. The scientific problem of this research is how to classify and visualize architectural factors that might have an influence on the market value of a dwelling. The object of the research are architectural factors in a housing market value analysis and the aim of research is to describe the theoretical framework that defines the structure and scope of architectural variables influencing a housing market value. Not all architectural factors described in the literature review are equal in terms of scale, measurability, public or private context, aesthetic or functional priority. A systematic approach would be to classify architectural factors as a matrix of built environment properties. Two orthogonal dimensions can be identified: architectural factors spanning from non-design (functional, utilitarian) to design (abstract, unexplained) and factors spanning from architectural design (private) to urban design (public). A multidimensional and complex system of architectural variables influencing a housing market value exists. Understanding this system is crucial for a housing development to succeed.