ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Penganggar GMM Arellano-Bond Teguh×Model Kesan Tetap Panel×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19911978
PengasasArellano & Bond (1991); robust inference extensions by Windmeijer (2005)Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021)
JenisDynamic panel GMM estimator with robust inferencePanel regression estimator
Sumber perintisArellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277-297. DOI ↗Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
AliasRobust Difference GMM, AB-GMM with robust standard errors, Robust first-difference GMM, Arellano-Bond robust estimatorwithin estimator, FE model, within-group estimator, LSDV model
Berkaitan65
RingkasanThe Robust Arellano-Bond GMM estimator applies the Arellano-Bond first-difference GMM approach to dynamic panel data while computing heteroscedasticity- and autocorrelation-consistent (robust) standard errors. This combination handles the Nickell bias from lagged dependent variables and simultaneously yields reliable inference when error variances differ across units or periods.The panel fixed effects (FE) model controls for all time-invariant, unit-specific unobserved heterogeneity by absorbing it into individual intercepts. By sweeping out unit means through the within transformation, FE yields unbiased estimates of the effect of time-varying regressors even when omitted unit-level confounders are correlated with those regressors.
ScholarGateSet data
  1. v1
  2. 2 Sumber
  3. PUBLISHED
  1. v1
  2. 2 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: Robust Arellano-Bond GMM · Panel Fixed Effects Model. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare