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Arellano–Bond estimator
In econometrics, the Arellano–Bond estimator is a generalized method of moments estimator used to estimate dynamic panel data models. It was first proposed by Manuel Arellano and Stephen Bond in 1991.〔.〕
==Qualitative description==
Unlike static panel data models, dynamic panel data models include lagged levels of the dependent variable as regressors. Since lags of the dependent variable are necessarily correlated with the idiosyncratic error, traditional static panel data model estimators such as the fixed effects and random effects estimators are inconsistent, due to presence of endogenous regressors.
Anderson and Hsaio (1981) first proposed a solution by utilising instrumental variables (IV) estimation.〔.〕 By taking the first difference of the regression equation to eliminate the fixed effect, deeper lags of the dependent variable can be used as instruments for differenced lags of the dependent variable (which are endogenous). Since increasing the number of instruments always increases the asymptotic efficiency of the estimator, it was proposed that all instruments in each time period should be used.
However, the Anderson–Hsiao estimator is asymptotically inefficient, as its asymptotic variance is higher than the Arellano–Bond estimator, which uses the same set of instruments, but constructs moment conditions from them and uses generalized method of moments estimation rather than instrumental variables estimation.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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