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Abstract This paper proposes a semi-functional partial linear spatial autoregressive (SAR) model, in which we allow one of the explanatory variables to be a functional variable, while the dependent variable… Click to show full abstract
Abstract This paper proposes a semi-functional partial linear spatial autoregressive (SAR) model, in which we allow one of the explanatory variables to be a functional variable, while the dependent variable is scalar. We aim to enable the spatial econometric models to be applied to various areas where data types can be functional data. Based on quasi-maximum likelihood estimation (QMLE) method and local linear regression method, we construct a two-stage estimator to estimate the parameters and nonparametric component. The convergence rate of the estimator of nonparametric component is given. Furthermore, Monte Carlo simulations are performed to investigate our two-stage estimator’s finite sample performance.
Journal Title: Communications in Statistics - Theory and Methods
Year Published: 2020
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