Testing Endogeneity of Spatial Weights Matrices in Spatial Dynamic Panel Data Models

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https://hdl.handle.net/2142/114458

Title: Testing Endogeneity of Spatial Weights Matrices in Spatial Dynamic Panel Data Models
Author(s): Lee, Jieun
Issue Date: 2022-09-02
Keyword(s): Endogenous spatial weights matrices, Economic distance, Spatial dynamic panel data (SDPD), two-way fixed effects panel, maximum likelihood estimation (MLE), robust Rao’s score (RS) test, robust LM test, local parametric misspecification.
Abstract: I propose Robust Rao’s Score (RS) test statistic to determine endogeneity of spatial weights matrices in a spatial dynamic panel data (SDPD) model (Qu, Lee, and Yu, 2017). I firstly introduce the bias-corrected score function since the score function is not centered around zero due to the two-way fixed effects. I further adjust score functions to rectify the over-rejection of the null hypothesis under a presence of local misspecification in contemporaneous dependence over space, dependence over time, or spatial time dependence. I then derive the explicit forms of our test statistic. A Monte Carlo simulation supports the analytics and shows nice finite sample properties. Finally, an empirical illustration is provided using data from Penn World Table version 6.1.
Type of Resource: Paper
Handle URL: https://hdl.handle.net/2142/114458