Generalized method of moments

E1046128

The generalized method of moments is an econometric estimation technique that uses sample moments to infer model parameters without requiring full specification of the underlying probability distribution.

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Statements (49)

Predicate Object
instanceOf econometric estimation method
method of moments estimator
statistical estimation method
abbreviation GMM
allows more moment conditions than parameters
overidentified models
appliedIn finance
industrial organization
labor economics
macroeconomics
associatedTest Hansen J test NERFINISHED
overidentifying restrictions test
assumes central limit theorem for sample moments
law of large numbers
basedOn moment conditions
sample moments
canHandle autocorrelation
heteroskedasticity
coreIdea choose parameters so that sample moments match theoretical moments implied by the model
doesNotRequire full specification of the underlying probability distribution
field econometrics
statistics
generalizes classical method of moments
hasLimitation finite-sample bias
sensitivity to choice of instruments
sensitivity to choice of weighting matrix
hasProperty asymptotic normality of estimators
consistency under correct specification of moment conditions
efficiency when optimal weighting matrix is used
input sample data
theoretical moment conditions
introducedBy Lars Peter Hansen NERFINISHED
introducedInYear 1982
optimizationCriterion quadratic form in sample moment conditions
output estimated covariance matrix of parameters
parameter estimates
publishedIn Econometrica NERFINISHED
relatedTo generalized empirical likelihood
instrumental variables estimation
requires valid instruments when regressors are endogenous
specialCase two-stage least squares
usedFor estimation of Euler equations
estimation of asset pricing models
estimation of dynamic panel data models
uses estimating equations
weighting matrix
variant dynamic panel GMM
linear GMM
nonlinear GMM

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Lars Peter Hansen notableWork Generalized method of moments