Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity

We consider the estimation and inference of fixed effects (FE) spatial dynamic panel data (SDPD) models under small T and unknown heteroskedasticity by extending the M-estimation strategy for homoskedastic FE-SDPD model of Yang (2018, Journal of Econometrics). Unbiased estimating equations are obtai...

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Main Authors: LI, Liyao, YANG, Zhenlin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2020
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Online Access:https://ink.library.smu.edu.sg/soe_research/2360
https://ink.library.smu.edu.sg/context/soe_research/article/3359/viewcontent/LiYang2020.pdf
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spelling sg-smu-ink.soe_research-33592021-05-31T04:38:42Z Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity LI, Liyao YANG, Zhenlin We consider the estimation and inference of fixed effects (FE) spatial dynamic panel data (SDPD) models under small T and unknown heteroskedasticity by extending the M-estimation strategy for homoskedastic FE-SDPD model of Yang (2018, Journal of Econometrics). Unbiased estimating equations are obtained by adjusting the conditional quasi-score functions given the initial observations, leading to M-estimators that are free from the initial conditions and robust against unknown cross-sectional heteroskedasticity. Consistency and asymptotic normality of the proposed M-estimator are established. The standard errors are obtained by representing the estimating equations as sums of martingale differences. Monte Carlo results show that the proposed M-estimators have good finite sample performance. The practical importance and relevance of allowing for heteroskedasticity in the model is illustrated using data on sovereign risk spillover. 2020-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2360 info:doi/10.1016/j.regsciurbeco.2020.103520 https://ink.library.smu.edu.sg/context/soe_research/article/3359/viewcontent/LiYang2020.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Adjusted quasi score Dynamic panels Fixed effects Initial-condition Martingale difference Short panels Spatial effects Unknown heteroskedasticity Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Adjusted quasi score
Dynamic panels
Fixed effects
Initial-condition
Martingale difference
Short panels
Spatial effects
Unknown heteroskedasticity
Econometrics
spellingShingle Adjusted quasi score
Dynamic panels
Fixed effects
Initial-condition
Martingale difference
Short panels
Spatial effects
Unknown heteroskedasticity
Econometrics
LI, Liyao
YANG, Zhenlin
Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity
description We consider the estimation and inference of fixed effects (FE) spatial dynamic panel data (SDPD) models under small T and unknown heteroskedasticity by extending the M-estimation strategy for homoskedastic FE-SDPD model of Yang (2018, Journal of Econometrics). Unbiased estimating equations are obtained by adjusting the conditional quasi-score functions given the initial observations, leading to M-estimators that are free from the initial conditions and robust against unknown cross-sectional heteroskedasticity. Consistency and asymptotic normality of the proposed M-estimator are established. The standard errors are obtained by representing the estimating equations as sums of martingale differences. Monte Carlo results show that the proposed M-estimators have good finite sample performance. The practical importance and relevance of allowing for heteroskedasticity in the model is illustrated using data on sovereign risk spillover.
format text
author LI, Liyao
YANG, Zhenlin
author_facet LI, Liyao
YANG, Zhenlin
author_sort LI, Liyao
title Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity
title_short Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity
title_full Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity
title_fullStr Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity
title_full_unstemmed Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity
title_sort estimation of fixed effects spatial dynamic panel data models with small t and unknown heteroskedasticity
publisher Institutional Knowledge at Singapore Management University
publishDate 2020
url https://ink.library.smu.edu.sg/soe_research/2360
https://ink.library.smu.edu.sg/context/soe_research/article/3359/viewcontent/LiYang2020.pdf
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