Determinants of housing prices in Baku: empirical analyses

Abstract

Purpose This paper aims to reveal major factors affecting housing prices (flats and houses) in Baku, the capital of Azerbaijan Republic. Design/methodology/approach Based on cross-sectional data set of 497 flats and 443 houses, polynomial regression models are estimated for flats and houses separately. Regression models are estimated by using ordinary least squares. Findings Location, largeness, repair level and existence of bill of sale are major price determinants for flats. For houses, number of rooms also matters. Findings reveals that houses are land intensive (more floors, less land area) toward city center, and vice versa. Price difference due to existence of bill of sale diminishes significantly toward the surrounding areas. Research limitations/implications The data set represents view of sellers and does not take into consideration price bargaining in time of sale; probability of information asymmetries exists which not could accounted for, and urgency of sale is not considered. Practical implications Estimation results can be used for housing valuation by real estate market participants and investors. Social implications Research findings reveal importance of bill of sale as a major price determinant and expected to attract policymakers’ attention to solve such a big social problem. Additionally, models can be based for price estimations in Baku housing market. Originality/value The study contributes to the literature by empirically analyzing housing market in Baku, Azerbaijan. Research produces new practically valuable findings.

Comparing predictive performance of general regression neural network (GRNN) and hedonic regression model for factors affecting housing prices in “Pune-India”

“…These findings are consistent with the existing literature. Most of the studies that use location-based hedonic factors to determine the housing prices have come to similar conclusions (Aliyev et al , 2019; Ajide and Alabi, 2010; Akinjare et al , 2011; Babawale et al , 2012; Benson et al , 1998; Bello, 2005, 2007, 2009; Bello and Bello, 2008; Chin and Chau, 2002; Crompton, 2005; Frew and Jud, 2003; lePage, 2003; Owusu et al , 2014; Pozo, 2009; Rodriguez and Sirmans, 1994; Soderberg and Janssen, 2001; Sirmans et al , 2005; Wong et al , 2002; Zou, 2015; Zhang and Dong, 2018). Therefore, these results offer nothing new or substantial with respect the locational hedonic factors except for the use of a location factor “fort.” Authors did not come across any study in the past that have used proximity to a famous fort in the city as a locational hedonic factor.…”

“…However, unlike financial assets, where standard valuation models exist such as income-based, market-based and asset-based or hybrid models (Tiwari and Singla, 2015); when it comes to assets such as real estate, arriving at the right valuation is a difficult task. It is because of the non-availability of a standard framework, as, unlike financial assets, the prices in real estate market are determined by not only the forces of supply and demand (Aliyev et al , 2019) but they are also driven by other significant factors, which define the prices in the housing market.…”

The Effect of the Principal Component Index for Housing Quality Satisfaction on Housing Price: Urban vs. Rural Analysis

“…2014), such as floor area (Guttery, 2002;Sirmans et al, 2005;Wang & Chen, 2018) and total number of floors (Colwell et al, 1998;Dermisi & McDonald, 2010), but building area squared has a negative relationship with housing prices (Fisher et al, 2006). Wang and Chen (2018) apply data mining to determine housing prices, and find that the factors affecting housing prices include the area of the house, house age, number of floors, and number of rooms (Aliyev et al, 2019;Keskin, 2008;Chang et al, 2018).…”

A housing price index with the improvement-value adjusted repeated sales (IVARS) method

“…However, we contend that the collinearity issue is not a problem when we have the data of actual appreciation or depreciation of the house structures. There are limited studies of the quality enhancement effect on house prices (Chau et al , 2003; Aliyev et al , 2019). One major challenge to examining the impact of quality enhancement is the unavailability of individual house quality measures.…”