Hedonic Price Model Research Articles

Estimating the Drivers of Urban Apartment Valuation by Using Hedonic Pricing Models: A Study on Dhaka City

Estimating the Drivers of Urban Apartment Valuation by Using Hedonic Pricing Models: A Study on Dhaka City

Quality adjustment and analysis of human resource prices in China: Based on a hedonic price model.

The competition in the world has shifted from natural resources and capital resources to human resources. The human resources have become the real power source of the economic growth. Firstly, the price of human resources in China is calculated. Secondly, in order to measure the human resources quality adjustment index, the indicators system is constructed. Third, the Hedonic method is used to calculate the human resources "pure price" of 31 provinces (autonomous regions and municipalities directly under the Central Government) in China. The "pure price" has no the factor of human resources quality. Lastly, comparing the price of human resources before and after quality adjustment. The results show that: first, the number of human resources in China increased continuously during 1995-2015 and decreased during 2016-2020. Second, the price of nominal human resources in China keeps rising. In 2020, the nominal price is 39,087 yuan per person which is 15.44 times as many as in 1995. Thirdly, after the quality adjustment, the price of human resources has decreased significantly. The multiple between the actual and nominal price of human resources is between 1.75 and 2.12. Fourthly, the province with high human resource quality adjustment index generally have high quality human resource level or quantity. Fifth, the top five provinces of actual human resource prices are Shanghai, Beijing, Guangdong, Tianjin, Zhejiang, the bottom five provinces are Guizhou, Yunnan, Henan, Xizang, Gansu. Finally, the paper puts forward some policy recommendations: Improving the data collection mechanism of human resources accounting to provide a basic guarantee for the accurate accounting of human resources. Improving the price of human resources in the central and western regions to attract the talents to transfer to the central and western regions. Enhancing the skills training of human resources to improve the quality of human resources in the western region.

The reverse mortgage market in New Zealand: key drivers of loan determination

ABSTRACT This paper examines the drivers of loan principals in the reverse mortgage and equity release market in New Zealand using a hedonic price model (HPM) approach. Our analysis using reverse mortgages data between 2004–2021, sourced from one major reverse mortgage bank, provides four key findings. First, the term of payment for repaid reverse mortgages is positively associated with loan principals, implying that longer repayment terms allow applicants who were able to repay mortgages to borrow more. Second, there is partial evidence to suggest the presence of a positive linear impact of the value of the current property on its loan principal, in line with previous house price modelling studies. Third, older applicants (age 75+) borrow less than younger applicants, which may be due to their repaying ability. Fourth, we confirm a positive effect of interest rates on reverse mortgage amounts but reject the positive association between wider loan-to-value policy restrictions and equity release lending amounts. The results broadly highlight that the house price is more relevant than any individual characteristic of a property in determining loan principals, and that all drivers are relevant in the early stage of the development of the reverse mortgages market in New Zealand.

Does better accessibility always mean higher house prices?

Numerous studies have explored the correlations between house prices and spatial accessibility, but few have delved into the nonlinearities between both. This study uses Cardiff (UK) as a case study and applies interpretable machine learning algorithms, eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), to estimate the nonlinear effects of geometric locational accessibility and street network accessibility on house prices. The findings suggest (1) proximity to the CBD, typically the major determinant of land values in hedonic house price models, does not continuously yield higher prices; (2) street closeness centrality, a network-modelling approach to measuring accessibility, exhibits a more generalised pattern with house prices compared proximity to the CBD regardless of analytical spatial scales. The findings challenge the generalizability of Alonso’s bid-rent theory in accurately portraying the relationship between accessibility and house prices in specific urban contexts, highlighting the importance of re-evaluating classical urban theories in different city contexts using novel measures and modelling techniques.

Price Model for Transit-Oriented Developments in Kuala Lumpur, Malaysia

Abstract The idea of Transit Oriented Development (TOD) was to foster urban development around railway networks and has been strategically built and applied since the late 19th and early 20th centuries. Previous studies reported positive, negative, or irrelevant impact of TOD on prices of surrounding real estate. The study aims to evaluate the impact of TOD on property prices in Kuala Lumpur. It utilizes secondary data obtained from the National Property Information Centre (NAPIC), Malaysia, after data cleaning, Nine Thousand Five Hundred and Forty-Nine (9549) Housing Transactions between the periods 2009 and 2018 were used. The research design was quantitative, and the Hedonic Price Model (log-log model) was used for data analysis. The model revealed a multiple correlation coefficient (R) of 0.891 and an adjusted R2 value of 0.794, indicating that 79.4% of the house price variation is explained by the model. The F value of 996.921, which is statistically significant, indicates that the predictors significantly combine to predict the price of TOD areas in Kuala Lumpur. The coefficient for LnTrainsta is 0.056, indicating that there was a positive relationship between residential house prices and TOD in Kuala Lumpur; this explains that house prices increase by 5.6% for every 100 meter closer to the rail transit station.

Legumes on the Rise: The Impact of Sustainability Attributes on Market Prices

Despite their environmental value and important role in human nutrition and food security, legumes, including lentils, have been underestimated. Nevertheless, nowadays there is a renewed interest in their consumption due to regional specialization, varietal diversity and their role in the transition towards sustainable production and consumptions systems. Recent years have also witnessed a rise in consumer awareness regarding sustainable food, healthier and plant-based diet and regional or local food systems. The aim of this paper is to evaluate the influence of attributes linked to sustainability, such as biodiversity, organic certification, origin indication, and packaging type, on lentils’ market prices in Italy. Based on the Hedonic Price Model, and following a review of scientific literature, eight lentil characteristics are defined. Data were collected on 228 valid observations of dry and precooked lentils across 20 different retail stores. Results indicate that Italian consumers have a positive appreciation for lentils with organic certifications and references to geographic and territorial characteristics. Some lentil varieties hold unique market positions, suggesting opportunities for diverse product offerings. Packaging materials influence consumer valuation, reflecting trends towards healthy and convenient food options. These insights will aid stakeholders in fostering sustainable practices and enhancing market competitiveness in the Italian lentil market.

Ecosystem service values provided by National Parks to residential property owners

This paper focuses on the ecosystem service benefits to homeowners from living in close proximity to three National Parks. Knowing these ecosystem service benefits is of policy and management relevance as expansion of existing Parks and protected areas along ecosystem boundaries often requires acquisition of undeveloped private land or other multiple use public lands, something that local officials may oppose. While the effects on house prices from urban parks, and two other types of U.S. Federal lands have been studied, the effect of lands in the U.S. National Park System on house prices had not been studied at the time of this research. To fill this information gap, hedonic price models were estimated to calculate the effect on residential house prices of proximity to three National Parks (NPs). After controlling for other characteristics of the house, neighborhood, and several other types of open space (e.g., National Forests, County Parks), we estimate house sale prices were on average 9.8% higher for houses within 2 km of National Park boundaries. This house price premium represents the value of the ecosystem services received by homeowners from living in close to these NPs. Quantifiable information on local ecosystem service benefits may ameliorate some concerns by local governments about converting private land or other agencies' multiple use lands in order to expand NPs or protected areas to better reflect ecosystem boundaries rather than historical, and often arbitrary boundaries. In addition, quantifiable information on enhancement of property values may broaden stakeholder groups to include the real estate industry. Thus, our results may support agencies in better achieving their objectives of managing NPs as ecological units.

Investigating the Effect of Transit-Oriented Development (TOD) on Social Equity—Examining the Displacement of Footscray, Melbourne

As Melbourne faces exponential population growth, the necessity for resilient urban planning strategies becomes critical. These strategies include mixed land use, density, diversity, and sustainable transportation through transit-oriented development (TOD). While TOD promises to accommodate growing populations and address environmental concerns, it also raises issues regarding its unintended consequences on poverty and inequality, notably through residential displacement and gentrification. This study investigates the impacts of TOD construction on inequality in Footscray, employing spatial analysis techniques like the hedonic price model (HPM), robust regression analysis, and Pearson correlation analysis. It aims to understand how spatial factors influence housing prices and their correlations. Additionally, the study uses observational spatial analysis via Google Street View (GSV) to examine indices such as housing development type, traffic signage, sanitation facilities, and house beautification. This approach seeks to build an evaluation framework to assess the extent of TOD street reconstruction and its impact on gentrification and displacement. The research adapts existing knowledge to create a tool for reviewing past planning decisions and assessing the fairness of TOD planning implementation. By providing assessment and guidance to mitigate the potential adverse impacts of TOD, this study contributes to the advancement of urban-planning practices, offering insights into mixed land use and effective strategies to balance economic development and social equity, thereby enhancing community resilience. Ultimately, this research deepens our understanding of the impacts of TOD on urban inequality and offers practical tools and insights for more equitable and sustainable urban development.

Hedonic Analysis of Dried Pasta Prices Using E-Commerce Data-An Explorative Study.

Italy is the world leader in the production of pasta and the Italian market is characterized by strong price competition among large industrial producers. Thus, recently, many small and medium firms have started to differentiate their products as a way to achieve higher margins and escape from price competition. Using data on the prices and characteristics of dried pasta sold online in the Italian market and a hedonic price model, we estimated the implicit prices associated with several attributes that are currently available for dried pasta. We find that the "artisanal" statement on pasta labeling is associated with the highest price premium. Also, results show that protected geographical indication, Halal and Kosher certifications, and the use of ancient wheat varieties are valuable features of dried pasta sold in the Italian market. Instead, a positive, albeit limited in magnitude, price premium is associated with dried pasta made using 100% Italian durum wheat semolina, the organic method, enriched with additional ingredients. Findings suggest that producers can differentiate their products by mostly emphasizing their small-scale production methods, the territorial connotation, and the cultural and environmental sustainability of production. Otherwise, certifying dried pasta as Halal or Kosher can represent a complementary or alternative strategy to differentiate the product and achieve a higher price.

Two-step model based on XGBoost for predicting artwork prices in auction markets

Art markets globally have grown, making artwork an investment of note. Precise valuation is pivotal for optimal returns. We introduce a two-step model with a two-level regressor, utilizing extreme gradient boosting (XGBoost) for accurate artwork price prediction. The model encompasses a price-class classifier and regressors for individual categories. This captures diverse factor influences, combining predictions to reduce misclassification risks. Visual features further enhance accuracy through the second-step two-level regressor. Experiments on Korean art auction data demonstrate the superiority of our two-step model with the two-level regressor over one-step and two-step alternatives, as well as the hedonic pricing model. While visual features affected one- and two-step models’ training, they boosted performance when integrated into the second-level decision tree, reducing first-level residuals. This emphasizes the two-level regressor’s efficacy in incorporating visual elements for artwork valuation. Our study highlights the potential of our approach in the field of artwork valuation.

Impacts of street tree abundance, greenery, structure and management on residential house prices in New York City

Urban trees have been widely linked to residential house prices. However, most existing studies focus on using tree abundance and greenery measures to evaluate the economic benefits of urban trees, while disregarding the effects of tree structure and tree-related management such as intentional maintenance and stewardship. We hypothesize that tree abundance, greenery, structure, and tree-related management are associated with house prices through offering local benefits that accrue to private homeowners and providing desirable living environments. We take street trees in New York City (NYC) as a case study to test the hypothesis. We first derived street tree canopy cover from high-resolution satellite images, street greenery from Google Street View, and street tree structure (e.g., species diversity, tree size, and tree health) and streetscape management variables (e.g., tree stewardship, tree guards that are a man-made structure to protect trees and enhance tree growth, and sidewalk damages adjacent to street trees) from the 2015–2016 street tree census data in NYC. We then built spatial hedonic price models to examine the associations between the above-mentioned street tree variables and residential house prices, after controlling for a variety of covariates. We found that HPMs that incorporate street tree structure and streetscape management offer stronger explanatory power than the one with only street tree abundance. Among the street tree-related variables we considered, tree canopy cover, green view index, tree stewardship and tree guards are statistically associated with increased house prices, while there are no such relationships for species richness, trees’ health status and streetscape sidewalk damages. More research is needed to understand the potential mechanisms and causal pathways that urban tree abundance, structure, and management affect residential house prices.

Investigating revealed preferences for urban waterway conditions: A hedonic property valuation study

AbstractThis study examines the impact of urban waterway conditions on property market prices. In general, similar revealed preference studies typically focus on identifying the value associated with changes in attributes such as riparian vegetation or water quality. Using an index that classifies waterways based on the vegetation and channel conditions, we analyse both attributes. Our spatial hedonic property price model findings indicate that buyers are willing to pay premiums ranging from 2.7% to 8.5%, depending on vegetation and channel conditions. However, when the proximity to the waterway is accounted for, we found that properties adjacent to the highest‐ranked vegetation and channel conditions attract a higher premium of 12.8%. Overall, the implicit marginal effects for the distance–condition interaction variables indicate that for lower‐ranked waterway conditions, there is a relative aversion to being adjacent to waterways. The results suggest that there are significant gains to be realised from removing concrete‐lined channels and replacing them with stones for banks, or re‐creating unmodified channels, even if there is only limited scope for increasing vegetation.

Do People Value Environmental Goods? Evidence From the Dutch Housing Market

This article studies the relationship between environmental goods and housing prices in the Netherlands. Applying a hedonic pricing model, we estimate simultaneous correlations between housing prices and air quality, noise pollution, green scenery, and water scenery, demonstrating the importance of including related sets of environmental goods to avoid omitted variable bias. We find that households particularly value noise pollution and green and water amenities in close proximity to their house. Air quality does not appear to substantially impact housing prices, neither do green spaces located more than 200 meters away. These results suggests that households mainly value those environmental goods that are directly experienced. A comparison of our hedonic price results to existing monetary estimates of the health effects of environmental goods indicates that people only partially internalize these health effects.

Willingness to pay for flood risk mitigation among residents living near river’s confluence in Yogyakarta, Indonesia

Both property buyers and owners are concerned about the impact of flooding on residential property price. Although several studies have investigated the possibility of property devaluation in flood-prone areas, there are still few that have looked into the effects of flooding on residential properties in Sriharjo, Imogiri, Indonesia. This study aims to examined housing characteristics such as structure, neighborhood, and environment on residential property value. We also created an interaction variable between flood and structural attributes to see whether the impact of flood inundation on property value varies depending on the age of the building, the size of the building area, and the number of bedrooms. Using the hedonic pricing model, we found that flooding reduces the market value of residential property value. The characteristics of property like land square, building square, building age, and number of rooms have influence on property price. The characteristics of neighborhoods are also influence to property price such as distance to city, distance to main road, distance to school and distance to the river. Only one environmental characteristic which influence to property price is height of flood inundation. We discovered that, on average, a rise in the amount of flood inundation decreased property prices in the research region by.015% by using a two-stage estimating approach to evaluate these associations. We calculated IDR 698,500 as the marginal implicit cost of reducing flood inundation. According to subsequent estimates, homeowners would be ready to pay an extra 0.685 percent for a decrease in flood inundation. The study’s findings will help property owners better understand the elements that contribute to property depreciation due to floods. This paper also suggests flood insurance plans since flooding is a significant issue for real estate owners.

개발 호재가 아파트 분양 프리미엄에 미치는 영향

1. CONTENTS
 (1) RESEARCH OBJECTIVES
 The purpose of this study is to examine how significant the construction of Samsung Electronics' Pyeongtaek Campus and the SRT Pyeongtaek-Jije Station, which are favorable developments in the Pyeongtaek area, affect the premium of apartment sales rights.
 (2) RESEARCH METHOD
 Hedonic price model was used for the factors affecting the actual transaction price, and multiple regression analysis was applied to find out the factors affecting the premium of the actual transaction right.
 (3) RESEARCH FINDINGS
 Model 1 (related to SRT Pyeongtaek Jije Station) empirical analysis showed that variables such as the number of floors, 2021 contract rankings, household parking, interest rates, exchange rates, and Pyeongtaek apartment sales price index had a positive (+) effect. The distance from the SRT Pyeongtaekji Station, a characteristic of favorable development, was found to have the second-largest influence on the dependent variable among the variables.
 Model 2 (related to Samsung Electronics' Pyeongtaek Campus) empirical analysis showed that the number of floors, 2021 contract ranking, exclusive area, number of parking lots by generation, interest rate, exchange rate, Pyeongtaek apartment sales price index had a positive (+) effect. Whether it was completed in 2018, the distance to Samsung Electronics' Pyeongtaek campus, the distance to the school, distance to commercial facilities, and the overall stock index were significant and had a negative (-) effect. The distance from Samsung Electronics' Pyeongtaek campus, a characteristic of favorable development, was found to have the greatest influence on the dependent variable among the variables.
 2. RESULTS
 The results of the study provide basic data that can be used to predict the real estate market when developing station areas around high-speed railway stations by grasping the impact of the opening of SRT Pyeongtaek Jije Station on the premium of the apartments around the area. This is expected to be useful data in grasping the degree of change in the value of local real estate assets and analyzing the development effect when constructing additional transportation facilities in the future

머신러닝과 통계 모형을 이용한 미술품 가격 예측

The art market is comprised of complex cultural, economic, and social characteristics and has recently received a lot of attention. Art transactions are carried out in a variety of ways, of which art auctions account for a large portion. We collected auction data on Post-War and Contemporary Art artists born after 1920 from Artnet and implemented an art price prediction model. In addition to the hedonic price model commonly used in existing studies, price prediction performance was compared using various machine learning models such as regression model, random effects model, regularization model, tree-based model, and SVM. To compare various machine learning models, RMSE and MAE were compared using two cross-validation methods. As a result, the nonlinear random effects model using author information showed the good performance. The impact of explanatory variables on price was analyzed using the optimal model. In addition, we were able to obtain price curves of various patterns according to the passage of time for each author. Among machine learning models that do not use author information, Bagging showed the best performance. As a result of measuring the importance of variables through Bagging, it was found that the size of the work had the most influence in predicting the price, followed by the artist's year of birth, the method of painting, the material with which the painting was painted, and the year of production.

Exploring the Impact of Multimodal Access on Property and Land Economies in Shanghai’s Inner Ring Districts: Leveraging Advanced Spatial Analysis Techniques

This study explores the impact of accessibility on property pricing and land economies by advanced spatial analysis techniques, focusing on Shanghai as a representative metropolis. Despite the impact of metro systems on residential property values, which has been frequently assessed, a research gap exists in understanding this phenomenon in Asian, particularly Chinese, urban contexts. Addressing this gap is crucial for shaping effective urban land use policy and improving the land economy rationally in China and similar settings facing urban challenges. To assess the impact of metro station accessibility on property prices in Shanghai, with extensive rail transit, and to deeply explore the overall impact of land value varieties driven by metro on urban development, we conducted a comprehensive analysis, with discussion about future aspirations for land planning and management along with landscape and facility design, and measures to improve land economy. The procedures involved creating neighborhood centroids to represent accessibility and using the Euclidean distance analysis to determine the shortest paths to metro stations. Our evaluation incorporated a hedonic pricing model, considering variables like neighborhood characteristics, housing attributes, and socio-economic factors. Advanced spatial analysis encompassing Ordinary Least Squares (OLS) regression and XGBoost analysis were employed to explore spatial effects, and Geographically Weighted Regression (GWR) helped examine spatial patterns and address autocorrelation challenges. Results revealed a negative association between distance to metro station and property prices, indicating a non-linear and spatially clustered relationship and heterogeneous spatial pattern. We dissected the non-linear results in detail, which complemented the conclusion in existing research. This study provides valuable insights into the dynamic interplay between metro accessibility and housing market behaviors in a significant Asian urban context, offering targeted suggestions for urban planners and governors to decide on more reasonable land use planning and management strategies, along with landscape and infrastructure design, to promote not only the healthy growth of the real estate market but also the sustainable urban development in China and similar regions.

Do people value farmers markets: A spatial hedonic pricing model approach

Abstract Farmers markets can generate positive externalities by improving food access and negative externalities through pollution. The presence of both may influence people’s willingness to pay (WTP) for living nearby. This study employs spatial hedonic pricing models to estimate the WTP for living near farmers markets in Edmonton, Canada. We find an inverted U-shaped relationship between proximity to a farmers market and property values. Our results suggest that local governments might consider the economic impact of building new or relocating existing farmers markets on residential housing values, alongside the benefits of improved access to high-quality food sources.

Urban Disparities in Energy Performance Premium Prices: Towards an Unjust Transition?

In recent years, numerous studies have explored how energy and environmental performance impact property values. Superior energy efficiency is the basis for value disparities in real estate markets. However, measurements of these variations vary significantly. This research aims to investigate the relationship between market size and vitality and market value differences. This has significant implications for the nature of the energy transition, potentially determining fairness or inequality. The study considers the real estate market in six Italian cities: three metropolitan (Milan, Turin, and Florence) and three medium-sized cities (Padua, Mestre, and Bergamo). The sample includes 2935 properties. In metropolitan cities, hedonic pricing models confirm the relevance of energy performance in market value formation, highlighting a potential depreciation in property values by up to 30% between properties belonging to the highest energy class (A) compared to the lowest (G), and 14% between class D and G. Such premium gaps are halved in medium-sized cities. Conclusions foresee a scenario of socially and economically unjust transition that must be considered in policies aimed at improving the energy efficiency of existing buildings, with a specific concern for the nature and characteristics of the real estate markets involved.

The hedonic price model for the wine market: A systematic and comparative review of the literature

AbstractThis paper carries out a thorough review of the literature on the estimation of hedonic price functions in the wine market, compiling and carefully documenting all research work on the subject. The review analyses the main methodological decisions taken by the different authors, as well as the typology of the available databases: identification of the relevant market, specification of the price function, sources and types of prices, econometric methodology, and type of publication. The variance decomposition analysis of the Adjusted‐R‐squared values from the estimated hedonic price functions suggests that attribute selection, the definition of the product market, the characteristics of information sources, and the implemented econometric procedures are the most relevant factors in explaining the models’ explanatory power.