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Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects

Yiguo Sun and Emir Malikov ()

Journal of Econometrics, 2018, vol. 203, issue 2, 359-378

Abstract: This paper develops an innovative way of estimating a functional-coefficient spatial autoregressive panel data model with unobserved individual effects which can accommodate (multiple) time-invariant regressors with a large number of cross-sectional units and a finite time periods. Our proposed methodology removes unobserved fixed effects from the model by transforming the latter into a semiparametric additive model, however avoids using backfitting technique. We derive the limiting results for the proposed estimators and construct a consistent nonparametric test to test for spatial endogeneity. A small Monte Carlo study shows that our proposed estimators and test statistic exhibit good finite-sample performance.

Keywords: First difference; Fixed effects; Hypothesis testing; Local linear regression; Nonparametric GMM; Sieve estimator; Spatial autoregressive; Varying coefficient (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C23 (search for similar items in EconPapers)
Date: 2018
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Working Paper: Estimation and Inference in Functional-Coefficient Spatial Autoregressive Panel Data Models with Fixed Effects (2017) Downloads
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