ScholarGate
Msaidizi

Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Kikokotozi cha Arellano-Bond GMM×Mfumo wa Data wa Paneli Wenye Kigezo Teule×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili19911988–1991
MwanzilishiManuel Arellano and Stephen BondArellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988)
AinaGMM estimator for dynamic panel dataDynamic regression / GMM estimation
Chanzo asiliaArellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277-297. DOI ↗Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297. DOI ↗
Majina mbadalaAB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimatordynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model
Zinazohusiana55
MuhtasariThe Arellano-Bond GMM estimator is the standard approach for dynamic panel data models in which the lagged dependent variable appears as a regressor. By first-differencing to remove fixed effects and using deeper lags as instruments, it yields consistent estimates even when the error is serially correlated and regressors are endogenous.The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy.
ScholarGateSeti ya data
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

Nenda kwenye utafutaji Pakua slaidi

ScholarGateLinganisha mbinu: Arellano-Bond GMM estimator · Dynamic Panel Data Model. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare