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Path selection of spatial econometric model for mass appraisal of real estate: evidence from Yinchuan, China

    Yu Zhao Affiliation
    ; Xuejia Shen Affiliation
    ; Jian Ma Affiliation
    ; Miao Yu Affiliation

Abstract

Urbanization, national economic growth, and China’s changing population structure have elevated the importance of real estate assessment in various contexts, including mortgage financing, secondary housing market transactions, and real estate tax reform. To address this need, this study employs a time-spatial double-fixed spatial cross-section data model as a mass appraisal tool to analyze the transaction price data of 429 ordinary residential houses in Xixia District, Yinchuan, China on April 1, 2022. Specifically, this study analyzes 7 spatial cross-section data models, discerning their interconnections. It devises an assignment technique that merges distance and characteristic variable rank into a unified indicator. The results explore spatial lag effects in real estate transaction price generation and assess the descriptive capabilities of different spatial cross-section data models.

Keyword : mass appraisal of real estate, spatial section data model, SDM, empirical analysis

How to Cite
Zhao, Y., Shen, X., Ma, J., & Yu, M. (2023). Path selection of spatial econometric model for mass appraisal of real estate: evidence from Yinchuan, China. International Journal of Strategic Property Management, 27(5), 304–316. https://doi.org/10.3846/ijspm.2023.20376
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Nov 27, 2023
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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