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  2. Generalized method of moments - Wikipedia

    en.wikipedia.org/wiki/Generalized_method_of_moments

    In econometrics and statistics, the generalized method of moments (GMM) is a generic method for estimating parameters in statistical models.Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable.

  3. Method of moments (statistics) - Wikipedia

    en.wikipedia.org/wiki/Method_of_moments_(statistics)

    In statistics, the method of moments is a method of estimation of population parameters.The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of the parameters of interest.

  4. Estimating equations - Wikipedia

    en.wikipedia.org/wiki/Estimating_equations

    In statistics, the method of estimating equations is a way of specifying how the parameters of a statistical model should be estimated.This can be thought of as a generalisation of many classical methods—the method of moments, least squares, and maximum likelihood—as well as some recent methods like M-estimators.

  5. Empirical likelihood - Wikipedia

    en.wikipedia.org/wiki/Empirical_likelihood

    An empirical likelihood ratio function is defined and used to obtain confidence intervals parameter of interest θ similar to parametric likelihood ratio confidence intervals. [7] [8] Let L(F) be the empirical likelihood of function , then the ELR would be: = / (). Consider sets of the form

  6. Arellano–Bond estimator - Wikipedia

    en.wikipedia.org/wiki/Arellano–Bond_estimator

    In econometrics, the Arellano–Bond estimator is a generalized method of moments estimator used to estimate dynamic models of panel data.It was proposed in 1991 by Manuel Arellano and Stephen Bond, [1] based on the earlier work by Alok Bhargava and John Denis Sargan in 1983, for addressing certain endogeneity problems. [2]

  7. Optimal instruments - Wikipedia

    en.wikipedia.org/wiki/Optimal_instruments

    To estimate parameters of a conditional moment model, the statistician can derive an expectation function (defining "moment conditions") and use the generalized method of moments (GMM). However, there are infinitely many moment conditions that can be generated from a single model; optimal instruments provide the most efficient moment conditions.

  8. List of statistics articles - Wikipedia

    en.wikipedia.org/wiki/List_of_statistics_articles

    Accelerated failure time model; ... Empirical likelihood; Empirical measure; Empirical orthogonal functions; ... Generalized method of moments;

  9. Lars Peter Hansen - Wikipedia

    en.wikipedia.org/wiki/Lars_Peter_Hansen

    Hansen is best known for his work on the generalized method of moments, he is also a distinguished macroeconomist, focusing on the linkages between the financial sector and the macroeconomy. His current collaborative research develops and applies methods for pricing the exposure to macroeconomic shocks over alternative investment horizons and ...