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Article
Publication date: 17 August 2021

Evgeniy M. Ozhegov and Alina Ozhegova

A common approach to predicting the price of residential properties uses the hedonic price model and its spatial extensions. Within the hedonic approach, real estate prices are…

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Abstract

Purpose

A common approach to predicting the price of residential properties uses the hedonic price model and its spatial extensions. Within the hedonic approach, real estate prices are decomposed into internal characteristics of an apartment, apartment characteristics and external characteristics. To account for the unobserved quality of the surrounding environment, price models include spatial price correlation factors, where the distance is usually measured as the distance in geographic space. In determining the price, a seller focuses not only on the observed and unobserved factors of the apartment and its environment but also on the prices of similar marketed objects that can be selected both by geographic proximity and by characteristics similarity. The purpose of this study is to show the latter point empirically.

Design/methodology/approach

This study uses an ensemble clustering approach to measure objects' proximity and test whether the proximity of objects in the property characteristics space along with spatial correlation explain the significant variation in prices.

Findings

In this paper, the pricing behaviour of sellers in a reselling market in Perm, Russia is studied. This study shows that the price transmission mechanism includes both geographic and characteristics spaces.

Practical implications

After testing on market data, the proposed framework for the distance construct could be used to obtain higher predictive power for price predictive models and construction of automated valuation services.

Originality/value

This study tests the higher explanatory power of the model that includes both the distance measured in geographic and property characteristics spaces.

Details

International Journal of Housing Markets and Analysis, vol. 15 no. 5
Type: Research Article
ISSN: 1753-8270

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Article
Publication date: 2 May 2017

Evgeniy M. Ozhegov

This paper aims to examine the heterogeneity of preferences of mortgage borrowers of Russian state-owned suppliers of residential housing mortgages.

170

Abstract

Purpose

This paper aims to examine the heterogeneity of preferences of mortgage borrowers of Russian state-owned suppliers of residential housing mortgages.

Design/methodology/approach

Analysis takes into account the underwriting process and the choice of contract terms of all loans originated from 2008 to 2012. The data set contains demographic and financial characteristics for all applications, loan terms and the performance information for all issued loans by one regional bank which operates government mortgage programs. The paper uses a multistep semiparametric approach to estimate the determinants of bank and borrower choice controlling for possible heterogeneity of preferences, sample selection and endogeneity of contract terms.

Findings

The study found that the demand of low-income households who are unable to afford to improve the housing conditions by other instruments than government mortgage is less elastic according to the change both in interest rate and maturity compared with higher-income households.

Social implications

Given lower elasticities of the demand, the low-income group of borrowers has higher potential cost of loan and is usually rejected by commercial banks. The presence of the Agency of Housing Mortgage Lending special programs with subsidized interest rate for special constrained categories (young families, teachers, researchers etc.) widens the access for housing conditions’ improvements as a part of housing affordability government program.

Originality/value

The main contribution to the literature is modeling choice of contract terms as interdependent by the structural system of simultaneous equations with heterogeneous marginal effects.

Details

Journal of European Real Estate Research, vol. 10 no. 1
Type: Research Article
ISSN: 1753-9269

Keywords

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