Penalized quadratic inference functions estimation of fixed effects partially linear varying coefficient spatial error model
Jianbao Chen and
Fen Li
Economic Modelling, 2025, vol. 146, issue C
Abstract:
This study introduces a novel fixed effects partially linear varying coefficient spatial error model featuring a correlation structure within individuals. A penalized quadratic inference functions estimation method for unknowns is proposed by employing B-spline to approximate the varying coefficient functions. Under certain regular conditions, the consistency and asymptotic normality of parametric estimators and the optimal convergence rate of nonparametric estimators are derived. Monte Carlo simulation indicates that the estimates perform strongly in finite sample scenarios. Empirical data analysis demonstrates that the model effectively captures the spatial error correlation of CO2 emissions and diverse factors’ linear and nonlinear influences on CO2 emissions. The proposed model and estimation method can be useful for researchers in related disciplines.
Keywords: Partially linear varying coefficient spatial error model; Penalized quadratic inference functions estimation; Correlation within individuals; Asymptotic property; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: C14 C15 C23 C51 R15 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:146:y:2025:i:c:s0264999325000173
DOI: 10.1016/j.econmod.2025.107022
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