Spatial Dynamic Panel Data Models with Correlated Random Effects
Liyao Li () and
Zhenlin Yang ()
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Liyao Li: School of Economics, Singapore Management University
No 15-2018, Economics and Statistics Working Papers from Singapore Management University, School of Economics
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.
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)
Pages: 46 pages
New Economics Papers: this item is included in nep-ecm, nep-geo, nep-ore, nep-sea and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:ris:smuesw:2018_015
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