Hedonic housing prices and environmental quality in Lebanon

Abstract

Purpose This study aims to examine the impact of local air pollution on housing prices in Lebanon. Design/methodology/approach The authors apply a hedonic pricing approach using a unique data set from Lebanon. To account for non-linearities in pricing, the authors use three different functional regression forms for the hedonic model approach. The authors also deal with potential omitted variable bias by estimating a hedonic frontier specification. Findings The authors find that, in all specifications, air pollution negatively and significantly affects housing prices. The estimated marginal willingness to pay for a one microgram per cubic meter change in particulate matter (PM10) concentration ranges between 2.88% and 3.18% of mean housing prices. The authors also provide evidence of a negative pricing gradient away from the city center, landing support for the monocentric urban development hypothesis. Research limitations/implications Given the lack of a data set linking household socioeconomic characteristics with housing data, the authors only consider the first-stage hedonic model. Practical implications The proposed hedonic pricing regression approximates a housing pricing equation that can be used by policymakers. Social implications The findings suggest that pollution is a significant factor in household behavior in Lebanon. Originality/value This paper adds to the scant literature studying the effects of air pollution on housing prices in developing countries. To the best of the authors’ knowledge, this is the first paper to study the impact of pollution on housing prices in a country in the Middle East and North Africa Region.

Central air conditioning, air pollution and housing location: evidence from Lebanon

“…Moreover, the distance to the Jieh and Zouk power plants is measured in kilometers. Lastly, the distance between the dwelling and the Costa-Brava, Hammoud and Naameh landfills is also measured (Marrouch and Sayour, 2021) [2].…”

“…We use a recent cross-sectional data set collected from Lebanon. This unique data set is collected by Marrouch and Sayour (2021) and it includes local air pollution concentrations, dwellings characteristics and their prices, in addition to information about the location of the dwelling. The dwellings' characteristics are retrieved from "Property Finder Lebanon" in 2018.…”

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Purpose -This study aims to examine the impact of local air pollution on the presence of central air conditioners in apartments in Lebanon.Design/methodology/approach -This study applies a Probit model in a unique data set on apartments' listings for sale in Lebanon collected by Marrouch and Sayour (2021). The data set includes information about air pollution concentrations, dwellings' characteristics, geographic features and location characteristics.Findings -This study finds that local air pollution positively and significantly affects the presence of central air conditioning in dwellings.

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“…Design/methodology/approach -This study applies a Probit model in a unique data set on apartments' listings for sale in Lebanon collected by Marrouch and Sayour (2021). The data set includes information about air pollution concentrations, dwellings' characteristics, geographic features and location characteristics.…”

Provision of urban environmental amenities

“…This finding is supported by those from a study on two coastal cities in Alabama, United States, in which a 1% increase in the distance to water bodies was found to decrease house prices by 0.03-0.04% (Dahal et al, 2019[66]). Furthermore, a 1% increase in proximity to wetlands was found to increase house prices by 0.04% in Portland Oregon (Mahan, Polasky and Adams, 2000 [67]). However, several papers found that proximity to water bodies, such as rivers and streams, had no clear effect on house prices (Cohen, Cromley and Banach, 2015 [68]; Van Der Kruk, 2001 [69]; Mei, Sohngen and Babb, 2018 [70]; Sylla, Lasota and Szewrański, 2019 [71])…”