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Time-varying coefficient spatial panel interval-valued models and applications
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DOI：10.1016/j.cnsns.2025.108880.png)
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Abstract
En 中文
Interval-valued data have attracted attention across various applications, prompting an increase in research on spatial models for interval-valued data. The study of the nonlinear characteristics of spatial interval-valued data over time has become essential; however, existing models demonstrate significant limitations in adequately characterizing these dynamics. This paper presents a spatial panel interval-valued model with time-varying coefficient and individual fixed effects, utilizing the parametric method. The local linear generalized method of moments is employed for parameter estimation, and its consistency and asymptotic properties are discussed. Monte Carlo simulations are employed to validate the fitting and predictive performance of the proposed model across various scenarios. Furthermore, the model is used to real-world air quality datasets for forecasting purposes, highlighting the practical utility of the proposed model.
Keywords:
Spatial autoregressive
Time-varying coefficient
Generalized method of moments
Air quality
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