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This paper aims to understand housing demand of urban Indian households in terms of housing and household-level characteristics. Because a house is a bundle of certain characteristics which vary across houses, each characteristic has an implicit price. Finding this implicit price for certain important characteristics is the first objective of this study. The second objective of the paper is to compute the income elasticity and price elasticity of housing demand for these cities.

To achieve comparable estimates, household-level data from India’s National Sample Survey Organisation housing surveys for the years 2002 and 2008-2009 have been used. A hedonic price function is estimated using ordinary least squares (OLS) and Box-Cox functional forms to estimate the implicit prices of housing characteristics. This exercise is attempted for owned and rented houses separately. Demand function required for computing the elasticities, uses the hedonic price index derived from the implicit prices and household characteristics.

The study finds housing demand to be income elastic and price inelastic for the six cities across both the time periods.

Firstly, this study includes housing characteristics such as individual access to drinking water, modern sanitation facility, separate kitchen, condition of the structure, existence of a road with street light and whether the house is in a slum or non-slum area in the hedonic price function. These variables were not used in any of the earlier studies pertaining to India. Secondly, it uses the Box-Cox non-linear form to derive the hedonic price function, a specification not used earlier. Thirdly, this is the first study analysing housing demand across the six largest Indian cities.

This paper aims to scrutinize the value of houses explained by their location in Central Asia’s largest city – Tashkent, the capital of Uzbekistan. The city was completely rebuilt after a devastating earthquake of 1961 and since the country was under the centrally planned regime, houses followed a common standard and style. This allows minimizing the error from omitting possible intrinsic characteristics in a hedonic model, while measuring the impact of location on housing values.

This study uses unique data on housing values and characteristics harvested from classified adverts. This study deliberately focused on data between 2013 and 2016, when Uzbekistan was characterized as hesitant in economic reforms. Therefore, residential buildings constructed during the Former Soviet Union dominated all parts of the city in the analysis period. The results are based on the hedonic pricing model.

The results suggest that locational characteristics are relatively more important than intrinsic characteristics. This study finds that proximity to the city center and access to subway stations significantly increase housing values. The opposite is true for the case of proximity to a wastewater treatment plant. Surprisingly, on the contrary to the authors’ expectations access to a park has no economically significant impact on housing values. The results, therefore, call for an integrated approach for city planning.

The first and most important contribution of this study to the field of housing economics is that it is the first study done for Uzbekistan, the most populated Central Asian country, and it is a case study for other Central Asian countries. The second contribution of the study is that, after a long and meticulous study, the determinants of housing prices were analyzed by taking into account all possible intrinsic and extrinsic properties of houses with the similar characteristics, over a unique data set created from approximately 18,000 observations from classified pages of a major newspaper published every Thursday in Tashkent City. The final contribution of the study is that it offers new perspectives and policy recommendations to the housing market actors in Uzbekistan.

Reviews the development of Irish housing policy from the eighteenth century to the present. Emphasizes the importance of measuring quality in housing, where housing may be described by a vector of measured characteristics. Undertakes a detailed price determination of these various characteristics using a hedonic model. Explains observed house prices in terms of the various housing characteristics using a hedonic model, from which a set of implicit or “hedonic” prices emerges. Reviews the theoretical basis of such an approach and develops a model specifically for aggregated data, as other studies in this area used disaggregated models. Obtains quantitative estimates of the qualitative and quantitative characteristics of the housing bundle before and after a series of model transformations. The results indicate the premium associated with certain housing characteristics. They emphasize, in particular, the importance of floor area and location in determining new Irish estate house prices.

The purpose of this paper is to determine the key characteristics that determine housing prices in the USA. Data analytical models capable of predicting the driving forces of housing prices can be extremely useful in the built environment and real estate decision-making processes.

A data set of 13,771 houses is extracted from the 2013 American Housing Survey (AHS) data and used to develop a Hedonic Pricing Method (HPM). Besides, a data set of 22 houses in the city of San Francisco, CA is extracted from Redfin real estate brokerage database and used to test and validate the model. A correlation analysis is performed and a stepwise regression model is developed. Also, the best subsets regression model is selected to be used in HPM and a semi-log HPM is proposed to reduce the problem of heteroscedasticity.

Results show that the main driving force for housing transaction price in the USA is the square footage of the unit, followed by its location, and its number of bathrooms and bedrooms. The results also show that the impact of neighborhood characteristics (such as distance to open spaces and business centers) on the housing prices is not as strong as the impact of housing unit characteristics and location characteristics.

An important limitation of this study is the lack of detailed housing attribute variables in the AHS data set. The accuracy of the prediction model could be increased by having a greater number of information regarding neighborhood and regional characteristics. Also, considering the macro business environment such as the inflation rate, the interest rates, the supply and demand for housing, and the unemployment rates, among others could increase the accuracy of the model. The authors hope that the presented study spurs additional research into this topic for further investigation.

The developed framework which is capable of predicting the driving forces of housing prices and predict the market values based on those factors could be useful in the built environment and real estate decision-making processes. Researchers can also build upon the developed framework to develop more sophisticated predictive models that benefit from a more diverse set of factors.

Finally, predictive models of housing price can help develop user-friendly interfaces and mobile applications for home buyers to better evaluate their purchase choices.

Identification of the key driving forces that determine housing prices on real-world data from the 2013 AHS, and development of a prediction model for housing prices based on the studied data have made the presented research original and unique.

In Ghana, the practice of landlords demanding that renters pay rent advance (RA) of between six months and five years is well noted. Surprisingly, renters appear divided into the benefits and drawbacks of the rent advance payment. Ahead of the 2020 general elections, the two leading political parties in Ghana promised to establish a rent assistance scheme to help renters working in the formal and informal sectors and earning regular incomes to pay their RA. This paper aims to scrutinize the differences in the demographic, employment and housing characteristics between the critics and non-critics of the RA payment in Ghana and the factors that predict the likelihood of being a critic of the RA system.

The study is exploratory and draws empirical data from surveys administered to 327 graduate renters from 13 regions in Ghana. It uses non-parametric and parametric tests, namely, Chi-square goodness-of-fit and T-test to explore these differences between both critics and non-critics of the RA.

There are statistically significant differences between critics and non-critics in terms of the association between their educational attainment on the one hand and their marital status, employment status and employment sector on the other hand. The research also reveals that monthly expenditures, number of bedrooms and RA period significantly predict the likelihood of being a critic of the RA payment or otherwise.

The study provides evidence which policymakers can draw upon to inform housing policy.

The study is the first to study the housing characteristics of graduate renters and to quantitatively distinguish between critics and non-critics of RA payment in Ghana.

The purpose of this paper is to discuss the relation between dissatisfaction with housing conditions and considering moving among residents of Finnish rental multifamily buildings. The paper examines physical attributes, socioeconomic factors, and subjective opinions related to housing conditions and satisfaction with housing.

Logistic regression analysis is used to examine survey data to analyse which factors contribute to dissatisfaction with the housing unit and the apartment building and whether dissatisfaction is related to consideration of moving.

The findings indicate that dissatisfaction with the building and individual housing unit are associated with greater probability of considering moving. Satisfaction with kitchen, living room, storage, and building age are the most important indicators of satisfaction with the housing unit, and satisfaction with living room, bathroom, storage, and building age are associated with satisfaction with the apartment building. These are the areas in which landlords could invest in renovations to increase satisfaction in an attempt to reduce turnover.

The study is conducted with Finnish data only. The sample is not a representative sample of the Finnish population. A longitudinal study would be needed to determine whether dissatisfied residents indending to move actually change residence.

This study is the first of its kind in the Finnish housing market. It tests a general model that has been suggested to be customized to local conditions. In addition, much of the research on this topic is more than 20 years old. Examination of the model under current housing and socioeconomic conditions is necessary to determine if relationships have changed over time.

Rental housing is an important form of accommodation; evaluating its quality will improve the quality of designs, standard living of renters, new dimension to policy guiding rental housing and enhance the values of rental houses. This study aims to examine the factors influencing rental housing quality in Ile-Ife, Nigeria.

Multi-stage sampling procedure was used to select tenants for the study. Residential areas were stratified into three densities: high, medium and low. Out of the 18 residential areas identified, six, eight and four were in the high, medium and low densities, respectively. Five residential areas were selected based on high concentrations of rental housing. The selected areas are Mokuro and Iloro (high density), Ife City and Eleyele (medium density) and Aladanla (low density). Systematic sampling technique was used to select 550 buildings where an adult tenant was selected per building for questionnaire administration.

The results of the principal component analysis established that four factors were generated for the high-density, nine factors for the medium-density and five factors for low-density areas as the major factors influencing rental housing quality. The variation in the number of factors generated and the percentage variance explained by the factors could be associated to the peculiarities across the densities in terms of the socioeconomic characteristics and housing characteristics of the renters.

This study examined the factors influencing housing quality for renters in Ile-Ife, Nigeria. It provides information on the three residential densities in terms of the variation in their housing morphology. The study went further to establish the relationship among the three musketeers such as socioeconomic characteristic of renters, housing characteristics and housing quality, under three dimensions environmental, internal building and external Building. Therefore, the contribution of this study strengthens the position that a minimum standard and schedule of upgrade and maintenance should be meted out for landlords to carry out repairs at interval, so as to make the housing unit and environment habitable for tenants.

Traditionally, in Palestine, outdoor spaces played a crucial role in organizing and improving the living quality of the living units, while this important role in modern housing design is lost by a stark separation between internal and private external spaces (balconies, verandas and yards). This separation is disconnecting private inside and outside spaces whereas in the traditional courtyard houses there was a continuity between the inside and the outside. This paper investigates the socio-environmental criteria and characteristics of private outdoor spaces that could play an improving role in the living quality of future housing design. So, a comparative study between contemporary and traditional outdoor spaces characteristics was carried out in two different cities in two different climatic zones of Palestine. The contemporary housing was evaluated by conducting a survey over 300 dwellings of different housing typologies (detached houses/apartment flats), while the characteristics of traditional design were analyzed from the old historical part of these cities. The results of this paper demonstrate that the private outdoor space is a major contributor to enhance housing sustainability. It presents the distinctive qualities of courtyard concept, which ought to be reintroduced consciously into the design of future housing in order to improve the living quality. The paper also identifies the most important factors that ensure those qualities and forms the basis for further research.

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.

The purpose of this paper is to describe the principles of a conceptual model to help developers and housing users achieve their expectations regarding quality, affordability and reasonable profits. Based on the identification of housing user’s preferences extracted from the survey, data are incorporated into model simulations considering budget restrictions for developers as well as for housing users.

The models’ development was based on fieldwork in Guayaquil, Ecuador, using a method that includes housing users’ preferences. Developed through a “methodological pluralism”, this study identifies people-oriented variables and assumptions. Thus, a more integrated approach is proposed, crossing and covering the fields of different disciplines.

The study concludes with findings regarding the identification of the most preferred attributes of housing users and the proposal of an alternative method to incorporate quality into model simulations for estimating housing market prices. Through optimizations, it is found that the optimal number of housing units per housing types in urban projects, which translates into more reasonable profits for the developers and the provision of better and more affordable houses for the users.

A more complete assessment of the principles described in this paper will require a larger timeframe and location of application.

The identification of the most preferred attributes of housing users and the inclusion in a conceptual simulation model would help private and public developers to provide better and more affordable houses for users as well as to attain reasonable profits. Further, housing national policy could also be influenced by model’s results.

The consideration of housing user’s preferences will entail an improvement of quality of life for social housing projects.

The study’s main original and novel contribution is the development of an approach for the inclusion of housing preferences into model simulations by using quality points and housing demand curves.