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Logarithmic spatial heteroscedasticity model with exogenous variables: Ohio’s housing prices

Bing Su et al.

Spatial Economic Analysis2026https://doi.org/10.1080/17421772.2025.2597824article
AJG 2ABDC B
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0.50

What the paper says

The investigation of the spatial dependence in variance is obtaining increased attention. In this paper, we propose a new generalised logarithmic spatial heteroscedasticity model with exogenous variables. For this model, we provide its estimators and tests for parameter constraints or model checking. Moreover, we establish the asymptotics of all estimators and tests using the tool of spatial near-epoch dependence, and examine their finite-sample performance by simulation. Finally, we give an empirical application for investigating the impact of spatial dependence and house characteristics on both the mean and variance of house prices.

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https://doi.org/https://doi.org/10.1080/17421772.2025.2597824

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@article{bing2026,
  title        = {{Logarithmic spatial heteroscedasticity model with exogenous variables: Ohio’s housing prices}},
  author       = {Bing Su et al.},
  journal      = {Spatial Economic Analysis},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/17421772.2025.2597824},
}

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Logarithmic spatial heteroscedasticity model with exogenous variables: Ohio’s housing prices

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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