Evaluation of extreme traffic noise as hazardous living environment factor in Saint Petersburg

Lozhkina, Olga; Lozhkin, Vladimir; Vorontsov, Ivan I.; Druzhinin, Petr

doi:10.1016/j.trpro.2020.10.046

Cited by 4 publications

(4 citation statements)

References 38 publications

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“…In a similar account, Wilhelmsson (2000) found that single-family houses located near busy roads in Ängby, a suburb of Stockholm, sell for a significant discount. Relatively similar findings are reported by Guijarro (2019) in Madrid; Lozhkina et al (2020) in Saint Petersburg; and McElveen et al (2020) in Jacksonville, FL. Andersson et al (2010) further argue that proximity to roads has a higher negative impact on house values than proximity to railways, although the study is limited by the non-specification of the type of roads in question.…”

Section: Earlier Studiessupporting

confidence: 85%

“…Logic should guide the researcher in deciding if it is justifiable to ignore the lagged X variables if the SAC model is to be applied. LeSage and Pace (2009) advocate for the spatial Durbin model (SDM), or alternatively, the Spatial Durbin Error Model (SDEM). The SDM model was introduced by Anselin (1988).…”

Section: Theoretical Background 21 the Hedonic Pricing Modelmentioning

confidence: 99%

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The effect of proximity and spatial dependence on the house price index for Dar es Salaam

Nyanda

2023

IJHMA

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Purpose This study aims to examine the effect of proximity and spatial dependence on the house price index for the nascent market Dar es Salaam, Tanzania. Despite the ongoing housing market transactions, there is no single house price index that takes into account proximity and spatial dependence. The proximity considerations in question are proximal to arterial roads, public hospitals, an airport and food markets. Previous studies on sub-Saharan Africa have focused on the ordinary least squares (OLS)-based hedonic model for the index and ignored spatial and proximity considerations. Design/methodology/approach Using the OLS and spatial econometric approach, the paper tests for the significance of the two effects – proximity and spatial dependence in the hedonic price model with year dummy variables from 2010 to 2019. The paper then compares the three indices in the following configurations: without the two effects, with proximity factors only, and with both effects, i.e. proximity and spatial dependence. Findings The inclusion of proximity factors and spatial dependence – spatial autocorrelation – seems to improve the hedonic price model but does not significantly improve the house price index. However, further research should be called for on account of the nascent nature of the market. Originality/value The paper brings new knowledge by demonstrating that it may not be necessary to take into account proximity factors and spatial dependence for the Dar es Salaam house price index.

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Section: Earlier Studiessupporting

confidence: 85%

Section: Theoretical Background 21 the Hedonic Pricing Modelmentioning

confidence: 99%

The effect of proximity and spatial dependence on the house price index for Dar es Salaam

Nyanda

2023

IJHMA

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“…There is also significant impact of noise level on the price of real estate. Lozhkina et al (2020) have shown that the price of the apartment on the heavy trafficked road is 10 % less compared to the apartment in quiet area. They also studied that the traffic noise creates an extreme risk of cardiovascular disease among senior citizens (aged over 65) that live in apartments with high noise in surrounding area [8].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Lozhkina et al (2020) have shown that the price of the apartment on the heavy trafficked road is 10 % less compared to the apartment in quiet area. They also studied that the traffic noise creates an extreme risk of cardiovascular disease among senior citizens (aged over 65) that live in apartments with high noise in surrounding area [8]. For the model development, Rey et al (2020) considered urban variables such as street location, street geometry, urban land use, road traffic control, and public and private transportation.…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting traffic induced noise using artificial neural network and multiple linear regression approach

2022

IJATEE

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Many countries have implemented noise regulations by enacting emission guidelines and regulating building acoustics. Unlike many other environmental issues, noise pollution continues to worsen, accompanied by an increase in the number of complaints from those who are affected. Most people are exposed to a variety of noise sources, with road traffic noise being the most common. Traffic management work is typically carried out by traffic

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Development of a Device to Reduce the Toxicity of Road Transport Emissions

Tunakova,

Mingazetdinov,

Ablyasova

et al. 2024

Lecture Notes in Networks and Systems

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Evaluation of extreme traffic noise as hazardous living environment factor in Saint Petersburg

Cited by 4 publications

References 38 publications

The effect of proximity and spatial dependence on the house price index for Dar es Salaam

The effect of proximity and spatial dependence on the house price index for Dar es Salaam

Predicting traffic induced noise using artificial neural network and multiple linear regression approach

Development of a Device to Reduce the Toxicity of Road Transport Emissions

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