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This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households.

A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding.

Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R² > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects.

This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums.

All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas.

This paper uses primary survey data (collected by the authors) to assess housing affordability for the urban poor of Lucknow city. It makes the results of the study credible and useful for further applications.

Art return indices are usually estimated based only on a few means of artistic expression (mainly paintings and drawings). Other forms of expression (e.g. sculptures and installations) are generally ignored, in part because they are three-dimensional and, hence, more difficult to measure. We analyze the price determinants as well as the return and risk of three artistic expressions (paintings, drawings and sculptures) executed by Fernando Botero, the most expensive living Latin American artist, to analyze the degree to which their risk and return attributes differ throughout a 20-year period.

We analyzed all paintings, drawings and sculptures executed by Botero and sold at Sotheby’s and Christie’s between 2000 and 2020 (a total of 707 artworks). The data and the images of each artwork were obtained from the web pages of these two auction houses. A hedonic regression was run to explain the price of each artwork and use explanatory variables that are standard in the literature. Art price indices for paintings, drawings and sculptures were constructed using the year-dummy variables estimated in the regressions. We performed a similar analysis for another artist, Carlos Cruz-Diez, as a robustness to our results.

The performance of Botero’s sculptures through time differs markedly from that of his paintings and drawings. Our results suggest that it is possible that returns estimated in the literature could suffer from a bias, as they have usually ignored the performance of sculptures and other artistic expressions. Botero’s paintings provided a return that was comparable to those of his sculptures (3.36% and 3.20%, respectively), they were two times as high as those of his drawings (1.68%). On the other hand, whereas paintings and drawings had similar annual standard deviations (26% and 25.22%, respectively), sculptures had a much smaller standard deviation (16.96%).

A limitation of the hedonic regression method lies in the need to have a significant and diverse sample to identify the true effect of each variable on the price of a good. Another limitation is that we were only able to use art prices from auctions, as this is the only comprehensive source of art price data that is publicly available. These two limitations are shared by all the studies that use the hedonic pricing model.

Our results have practical applications for art collectors and investors, as well as for artists, galleries and, in general, for the whole art market ecosystem. The risk and return attributes of the various artistic expressions of an artist can be different, and thus it makes sense to analyze each one of them individually, as well as their correlations with the other artistic expressions and with traditional and other alternative investments.

The art market is part of what is known as the “orange economy” (also known as the Creative Economy). According to the World Bank, the economic value of the creative sector is not well known or appreciated, even though cultural, creative and artistic activities are vital for our sense of well-being.

To the best of our knowledge, this is the first paper that compares the financial performance of paintings, drawings and sculptures for the case of a specific artist. We chose Botero for three reasons. First, he is a Latin American living artist who has achieved the highest levels of international sales. Second, Botero has worked extensively on various artistic expressions (oil paintings, drawings on different materials and sculptures) throughout his life, a characteristic that is essential to be able to carry out our study. Third, there is a long record of auction sales for each of Botero’s artistic expressions.

Los índices de rentabilidad del arte generalmente se estiman basándose únicamente en unos pocos medios de expresión artística (principalmente pinturas y dibujos). Otras formas de expresión artística (por ejemplo, esculturas e instalaciones) generalmente se ignoran, en parte porque son tridimensionales y, por tanto, más difíciles de medir. Analizamos los determinantes del precio, así como el retorno y el riesgo de tres expresiones artísticas (pinturas, dibujos y esculturas) ejecutadas por Fernando Botero, el artista latinoamericano vivo más caro, para analizar en qué medida sus atributos de riesgo y retorno difieren a lo largo del tiempo, en un período de 20 años.

Analizamos todas las pinturas, dibujos y esculturas ejecutadas por Botero y vendidas en Sotheby’s y Christie’s entre 2000 y 2020 (un total de 707 obras de arte). Los datos y las imágenes de cada obra se obtuvieron de las páginas web de estas dos casas de subastas. Se realizó una regresión hedonante para explicar el precio de cada obra de arte y se utilizaron variables explicativas estándar en la literatura. Los índices de precios de arte para pinturas, dibujos y esculturas se construyeron utilizando variables ficticias anuales estimadas en las regresiones. Realizamos un análisis similar para otro artista, Carlos Cruz-Diez, como análisis de robustez de nuestros resultados.

El desempeño de las esculturas de Botero a través del tiempo difiere marcadamente del de sus pinturas y dibujos. Nuestros resultados sugieren que es posible que los retornos estimados en la literatura sufran un sesgo, ya que generalmente han ignorado el desempeño de esculturas y otras expresiones artísticas. Las pinturas de Botero proporcionaron un retorno comparable al de sus esculturas (3.36% y 3.20%, respectivamente), pero fueron dos veces superiores a los de sus dibujos (1.68%). Por otro lado, mientras que las pinturas y los dibujos tuvieron desviaciones estándar anuales similares (26% y 25.22%, respectivamente), las esculturas tuvieron una desviación estándar mucho menor (16.96%).

Una limitación del método de regresión hedónica radica en la necesidad de contar con una muestra significativa y diversa para identificar el verdadero efecto de cada variable sobre el precio de un bien. Otra limitación consiste en que solo pudimos utilizar precios de arte de subastas, ya que esta es la única fuente completa de datos sobre precios de arte que está disponible públicamente. Estas dos limitaciones son compartidas por todos los estudios que utilizan el modelo de precios hedónico.

Nuestros resultados tienen aplicaciones prácticas para coleccionistas e inversores de arte, así como también para artistas, galerías y, en general, para todo el ecosistema del mercado del arte. Los atributos de riesgo y retorno de las diversas expresiones de un artista pueden ser diferentes, por lo que tiene sentido analizar cada una de ellas individualmente, así como sus correlaciones con las otras expresiones artísticas y con las inversiones tradicionales y otras alternativas.

El mercado del arte forma parte de lo que se conoce como “economía naranja” (también conocida como Economía Creativa). Según el Banco Mundial, el valor económico del sector creativo no es bien conocido ni apreciado, a pesar de que las actividades culturales, creativas y artísticas son vitales para nuestra sensación de bienestar.

Hasta donde hemos podido comprobar, este es el primer artículo que compara el desempeño financiero de pinturas, dibujos y esculturas para el caso de un artista específico. Elegimos a Botero por tres razones. En primer lugar, es el artista vivo latinoamericano que ha alcanzado los mayores niveles de ventas internacionales. En segundo lugar, Botero ha trabajado extensamente en diversas expresiones artísticas (óleos, dibujos sobre distintos materiales y esculturas) a lo largo de su vida, característica que resulta fundamental para poder realizar nuestro estudio. En tercer lugar, existe un largo historial de ventas en subasta de cada una de las expresiones artísticas de Botero.

This study aims to examine the determinants that influence housing prices in Dammam metropolitan area (DMA), Saudi Arabia, by using the analytic hierarchy process (AHP) model. The study considers determinants such as building age (BLD AG), building size (BLD SZ), building condition (BLD CN), access to parking (ACC PK), proximity to transport infrastructure (PRX TRS), proximity to green areas (PRX GA) and proximity to amenities (PRX AM).

The AHP decision model was used to assess the determinants of housing prices in DMA, using a pair-wise comparison matrix to determine the influence of the investigated factors on housing prices.

The study’s results revealed that building size (BLD SZ) was the most critical determinant affecting housing prices in DMA, with a weight of 0.32, trailed by proximity to transport infrastructure (PRX TRS), with a weight of 0.24 as the second most influential housing price determinant in DMA. The third most important determinant was proximity to amenities (PRX AM), with a weight of 0.18.

This study addresses a research gap by using the AHP model to assess the spatial determinants of housing prices in DMA, Saudi Arabia. Few studies have used this model in examining housing price factors, particularly in the context of Saudi Arabia. Consequently, the findings of this study provide unique insights for policymakers, housing developers and other stakeholders in understanding the importance of building size, proximity to transport infrastructure and proximity to amenities in influencing housing prices in DMA. By considering these determinants, stakeholders can make informed decisions to improve housing quality and prices in the region.

This paper aims to compare the efficiency of spatial and nonspatial hedonic price models in capturing housing submarkets dynamics for cities in developing countries. This study expects to contribute to a better understanding of the housing price determinants from both nonspatial and spatial perspectives. In addition, this paper fills a gap in the literature on the study of housing prices from a spatial perspective in Latin American cities.

This study uses a comparative analysis between an ordinary least squares regression and a geographical weighted regression, GWR. The study also assesses the performance of two distinct data sources: the city’s cadastral records and a real estate sales web portal.

The results suggest that compared to the traditional regression model, the spatial regression models are more effective at capturing housing market variations on a fine scale. Moreover, they reveal interesting findings on the spatial varying, sometimes contradictory effects of some housing attributes on housing prices in different areas of the city, suggesting the potential impact from segregation.

The availability of data on housing prices and characteristics in Latin American cities is fragmented and complex. The level of detail, granularity and coverage is not consistent over time. For this reason, this study combines and compares data sets from official and unofficial sources in an effort to close this gap. Likewise, the socioeconomic variables that come from the census must be carefully analyzed, knowing the historical context in which they were constructed, what they represent and their interpretation.

This paper suggests that despite the improvement on the spatial models, the selection of a specific one should always be based on the diagnosis of it as it highly depends on the data used and the objectives of the study.

This study enriches the limited body of literature on spatial hedonic price models of housing in Latin American cities. It also shed light on the importance of spatial approaches to identify complex housing submarkets.

The purpose of this study is to examine the influence of key hotel attributes on the room rates of selected hotels in the Greater Gaborone Region, Botswana.

Using hedonic pricing analysis, the effect of eight attributes collected from 80 standard double rooms on Booking.com in the area was analysed using quantile regression.

The estimated results from quantile regression suggested the importance of the 10th quantile as the best predictor of hotel room price distribution. Overall, the presence of a fitness centre and the availability of meeting and conference facilities were positively significant for the lowest- and premium-priced hotels, respectively.

The study advanced the literature in hedonic pricing models by confirming the applicability of hotel room rate attribute research in unexplored environments.

Hotel managers should be aware of the influence of key attributes, such as meeting and conference space availability and locational factors, on the pricing decisions of room rates in the Greater Gaborone Region. The study also presented opportunities for business-to-business marketing between hotel and tour operators in the region.

The study is one of the few that uses quantile regression in the hedonic pricing analysis of hotel room rates.

The use of statistical methods in the field of real estate appraisals presents a trade-off between the efficiency of the estimates (that would require the use of sophisticate econometric models) and the ease of the economic interpretation of the outcomes (that characterises the hedonic pricing models). This paper shows that multilevel modelling (MLM) can represent a suitable solution to this trade-off.

This paper uses the so-called “multilevel modelling” (henceforth MLM). MLM can represent a further step forward in the use of statistical methods in property appraisals. MLM is easy to implement and the MLM estimates have a clear economic meaning. Furthermore, MLM provides more efficient estimates of hedonic prices (the prices of housing attributes) with respect to standard hedonic pricing models. Finally, MLM is particularly suitable for the housing market analysis, where the feature “location” plays a key role.

For the Italian context, characterised by many “benchmark locations” (small municipalities that share similar geographic, historic, and socioeconomic characteristics), the paper finds that multilevel modelling (MLM) is needed to correctly estimate the hedonic prices also in a micro-area.

MLM allows to further enhance the key role of “location”. Location is indeed used as the “grouping variable” in MLM, instead of being treated as a generic housing attribute in hedonic pricing models. When the benchmark locations are many, therefore, MLM represents a very effective compromise between the estimates’ efficiency and the ease of outcomes’ economic interpretation.

Unlike the related literature that, basically, use MLM to investigate what are the main determinants (levels) of housing prices, this paper uses MLM to make more efficient the estimation of hedonic prices.

The purpose of this study is to examine the buyers’ preferences influencing the purchase of privately developed affordable housing in Kolkata and to determine whether unsold houses result from misalignment with these preferences.

The literature review and user-opinion survey identified 119 independent variables that indicate buyers’ preferences. A questionnaire survey of 383 households in affordable housing units from 32 housing complexes in Kolkata recorded buyers’ preferences and satisfaction against the independent variables grouped under five levels of characteristics. The product weights of variables derived from the rank sum method and percentage satisfaction give the Utility Score. Multivariate regression and univariate linear regressions were conducted to determine the significance of each Level of characteristics and each variable, identifying the significant variables that would affect the sale of affordable houses.

The multivariate regression analysis has indicated that 68.56% of the variation in the percentage of unsold houses was explained by the five utility scores, which affirms that misalignment with buyers’ preferences significantly affects the sale of privately developed affordable houses. Furthermore, building and neighbourhood-level utility show the highest significance as predictors, while city-level and miscellaneous utility have moderate significance, but housing complex-level utility lacks statistical significance.

This study addresses a research gap in privately developed affordable housing in Kolkata, enhancing understanding of buyer preferences in this segment.

With revolutions in the telecommunication sector having led to wide unprecedented consequences in all facets of human life, this paper aims to examine the relationship between cell phone tower base stations (CPTBSs) and residential property prices within the City of Johannesburg (CoJ), South Africa.

The authors align their work with global literature and assess how the impact of CPTBSs influences residential property values in South Africa. The authors use a semi-log hedonic pricing model to test the hypothesis that proximity of CPTBSs to residential properties does not account for any variation in residential property prices.

The results show a significant impact that proximity of CPTBS has on residential property sale prices. However, the impact of CTPBSs’ proximity on residential property prices depends on their distance from the residential properties. The closer a residential property is to the CTPBS, the greater the impact that the CTPBS will have on the selling price of the residential property.

With international studies offering mixed findings on the impact of CPTBSs on residential property values, there is limited research on their impact in South Africa. The findings of this study offer crucial insights for the real estate practitioners, property owners, telecommunications companies and the public, providing a nuanced understanding of the relationship between CPTBSs and property values. This research helps property owners understand the effects of CPTBSs on their properties, and it assists property valuers in gauging the impact of CPTBSs on property values.

This paper aims to investigate the effects of school quality (SQ) on residential property prices in Johannesburg, South Africa. Previous studies have empirically examined the quality of private and public schools without a standard proxy that is accepted in the literature. As a result, this paper extends the literature to the global south by the effect that SQ has on residential property price changes in the local markets of the City of Johannesburg.

The research adopts the hedonic pricing model to evaluate and quantify the impact that the structural attributes such as erf size; number of bedrooms and bathrooms; and SQ measured by pass rates, sport rankings and quality of facilities have on house prices. A total of 2,763 property transactions covering the Kensington and Observatory areas of the City of Johannesburg over the period 2010 and 2020 were obtained from the deeds registry and used for the empirical analysis.

The study finds that SQ has a positive impact on house prices. When the average pass rate of the model school increases by 1%, all other things being equal, house prices also increase by 1.8%. This suggests that people who live closer to the model school are willing to pay more when the school performance improves. The 1.8% premium this study attributes to a 1% increase in school performance is however generally low when compared to some findings in the literature suggesting that there may be some other important factors that households consider when purchasing their home.

The main contribution is uncovering the relationship between the SQ and residential property prices in the local markets, using Kensington and Observatory in Johannesburg as sampled areas. Due to the presence of reliable and quality of data sets, such studies are not many in the global south and a study of this nature in South Africa is notably not existing in the literature.

This study aims to examine whether or not residential properties closer to landfill sites have lower offer values by the developers. That is, by analyzing real estate data and landfill site locations, the study seeks to provide insights into whether properties situated closer to landfill sites tend to have a lower offer values than those located farther away.

The study is exploratory in nature, and a case study approach is applied. A landfill site named “Uruli Devachi” is selected in the region of Pune district, and data is collected from 102 developers selling residential projects within a radius of 15 km (about 9.32 mi). The gathered data is analyzed by using basic descriptive statistics, one-way ANOVA and ordinary least squares (OLS) regression. The OLS regression helps to determine whether there is a relationship between the distance of a residential property from a landfill site and its offer value.

The findings suggest that landfill sites have a detrimental impact on residential property offer values, with the negative impact increasing with proximity to a landfill site. The negative effect seems to vanish after over 10 km (about 6.21 mi). The developers provide extra facilities including a clubhouse, a children’s play area, a gym and a swimming pool in an effort to mitigate the negative effects of the landfill site on residential properties.

The findings of this study could have implications for property developers, real estate professionals and policymakers in understanding how landfill proximity might impact property offer values.

This study presents many novelties for the Indian housing market: the landfill sites do have a negative effect on the offer value of residential property; the closer the residential property to a landfill site, the higher the negative effect. Further, the developers try and mitigate the negative effect of landfill sites on residential properties by providing additional amenities such as a clubhouse, children’s play park, gym and swimming pool.