The effect of environment on housing prices: Evidence from the Google Street View

Wang, Guan‐Yuan

doi:10.1002/for.2907

Cited by 4 publications

(3 citation statements)

References 47 publications

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“…In cases where correlations between variables change over time and over different investment horizons, wavelet analysis allows simultaneous correlation analysis in the time and frequency domains [34][35][36]. It should be noted that methods such as DCC GARCH, enabling us to analyze in the time domain, do not allow for analysis in the frequency domain and therefore only allow the study of the covariance matrix in the time domain [37,38].…”

Section: -Research Methodologymentioning

confidence: 99%

Program-Target Mechanisms to Ensure the Fiscal Balance of the Federal Constituent

Karaev,

Gorlova,

Ponkratov

et al. 2023

Emerg Sci J

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The purpose of this research is to study the possible impact of program costs associated with the development of the real sector of the regional economy on the fiscal balances of the constituent entities of the Russian Federation based on the wavelet analysis method. To achieve this purpose, we conducted a correlation analysis of the time-frequency dependence between the variables of the empirical model: the shares of program costs, the shares of non-repayable receipts, and the share of business taxes in the revenues of the consolidated budgets of constituent entities of the Russian Federation such as the Republic of Mordovia, the Udmurt Republic, Trans-Baikal Territory, and Kaliningrad Region for the period from 2001 to 2021. The research results indicate a significant impact exerted by the program costs of the regional budgets on the development of the real sector to ensure fiscal balance in the Republic of Mordovia, the Udmurt Republic, and the Trans-Baikal Territory on certain time scales. The novelty of this research lies in demonstrating the wavelet analysis effectiveness applied when conducting correlation analysis in cases where the relationships between the analyzed variables follow different patterns at different time horizons, and precisely wavelet analysis makes it possible to reveal the most significant characteristics of the relationship of variables. Earlier studies based on traditional methods ignored the time-frequency dependence between the variables of the empirical model. The practical significance of the research results lies in the fact that they determine the time scale on which the most effective measures and budgetary policy instruments applied within the framework of program-target mechanisms are provided to ensure fiscal balances in the regions. Doi: 10.28991/ESJ-2023-07-05-05 Full Text: PDF

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Section: -Research Methodologymentioning

confidence: 99%

Program-Target Mechanisms to Ensure the Fiscal Balance of the Federal Constituent

Karaev,

Gorlova,

Ponkratov

et al. 2023

Emerg Sci J

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“…In housing research, it is crucial to explore the relationship between socioeconomic environments and human settlement. Bin et al (2020), Chen et al (2020), Fu et al (2019), Kang, Stice-Lawrence, and Wong (2021), Law et al (2019), Li et al (2021), Lyu et al (2022), Wang (2023), Wu et al (2022), Xu et al (2022), Yao et al (2018) and Ye et al (2019) utilised street views to estimate housing prices and proposed a neural networks-based methodology to address the issues that the economists had to manually categorise each view in the past and providing new insights into the assessment of human settlement values. Meanwhile, Johnson et al (2020), Kostic and Jevremovic (2020) and Qiu et al (2022) found that houses with better street or property design come at a price premium, meaning that proposed methods can efficiently describe visible characteristics.…”

Section: Review and Applicationsmentioning

confidence: 99%

Integrating Street Views, Satellite Imageries and Remote Sensing Data Into Economics and the Social Sciences

Wang

2023

Social Science Computer Review

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Street views, satellite imageries and remote sensing data have been integrated into a wide spectrum of topics in the social sciences. Computer vision methods not only help analysts and policymakers make better decisions and produce more effective solutions but they also enable models to achieve more precise predictions and greater interpretability. In this paper, we review the growing literature applying such methods to economic issues and the social sciences, in which social scientists employ deep learning approaches to utilise image data to retrieve additional information. Typically, image data produce better results than traditional approaches and can provide detailed results and helpful insights to improve society and people’s well-being.

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“…The effectiveness of each alternative energy source should be evaluated based on its scalability, or the ability to increase its output to meet future demand [30]. This criterion should consider the technical and economic feasibility of scaling up each system as well as any potential environmental impacts associated with increasing the system capacity [31,32]. Therefore, scalability is considered as the fifth and final criterion in this study.…”

mentioning

confidence: 99%

Multi-Criteria Decision Analysis for Evaluating the Effectiveness of Alternative Energy Sources in China

et al. 2023

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The transition to renewable energy sources is crucial for mitigating the impacts of climate change and achieving sustainable development goals. In China, the rapid industrialization and urbanization have led to an increasing demand for energy, highlighting the urgent need to transition to alternative energy sources. This study aims to evaluate the effectiveness of alternative energy sources in China, considering multiple criteria such as cost, environmental impact, energy output, reliability, and scalability. We employed a Multi-Criteria Decision Analysis (MCDA) approach to compare and rank different energy sources based on these criteria. Our findings indicate that wind energy is the most effective alternative energy source overall due to its relatively low cost, high efficiency, moderate environmental impact, good scalability, and high reliability. However, geothermal energy had the lowest levelized cost of electricity (LCOE), while hydro energy performed well in terms of efficiency and reliability. The environmental impact of wind energy was found to be moderate but still less severe compared to other energy sources. Our study provides important insights into the trade-offs and considerations that policymakers and industry leaders must make when selecting which energy sources to prioritize. The findings highlight the need for a comprehensive and integrated approach to energy policy that balances economic, environmental, and social considerations. In conclusion, this study contributes to the literature by emphasizing the importance of considering multiple criteria when evaluating alternative energy sources. Our findings can inform policy decisions regarding the development of a sustainable and reliable energy mix in China, and have important implications for other countries seeking to transition to renewable energy sources.

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The effect of environment on housing prices: Evidence from the Google Street View

Cited by 4 publications

References 47 publications

Program-Target Mechanisms to Ensure the Fiscal Balance of the Federal Constituent

Program-Target Mechanisms to Ensure the Fiscal Balance of the Federal Constituent

Integrating Street Views, Satellite Imageries and Remote Sensing Data Into Economics and the Social Sciences

Multi-Criteria Decision Analysis for Evaluating the Effectiveness of Alternative Energy Sources in China

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