Spatial dynamic panel data models with correlated random effects

Liyao Li and Zhenlin Yang

Journal of Econometrics, 2021, vol. 221, issue 2, 424-454

Abstract: In this paper, M-estimation and inference methods are developed for spatial dynamic panel data models with correlated random effects, based on short panels. The unobserved individual-specific effects are assumed to be correlated with the observed time-varying regressors linearly or in a linearizable way, giving the so-called correlated random effects model, which allows the estimation of effects of time-invariant regressors. The unbiased estimating functions are obtained by adjusting the conditional quasi-scores given the initial observations, leading to M-estimators that are consistent, asymptotically normal, and free from the initial conditions except the process starting time. By decomposing the estimating functions into sums of terms uncorrelated given idiosyncratic errors, a hybrid method is developed for consistently estimating the variance–covariance matrix of the M-estimators, which again depends only on the process starting time. Monte Carlo results demonstrate that the proposed methods perform well in finite sample. An empirical application on the political competition in China is presented.

Keywords: Adjusted quasi score; Dynamic panels; Correlated random effects; Initial-conditions; Martingale difference; Spatial effects; Short panels (search for similar items in EconPapers)
JEL-codes: C10 C13 C15 C21 C23 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407620302372
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Spatial Dynamic Panel Data Models with Correlated Random Effects (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:221:y:2021:i:2:p:424-454

DOI: 10.1016/j.jeconom.2020.05.016

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().