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Bayesian like R- and M- estimators of change points

100%

Antoch J., Husková M.

Discussiones Mathematicae Probability and Statistics

2000

tom 20

nr 1

115-134

The purpose of this paper is to study Bayesian like R- and M-estimators of change point(s). These estimators have smaller variance than the related argmax type estimators. Confidence intervals for the change point based on the exchangeability arguments are constructed. Finally, theoretical results are illustrated on the real data set.

On robust GMM estimation with applications in economics and finance

88%

Steland A.

Discussiones Mathematicae Probability and Statistics

2000

tom 20

nr 1

63-83

Generalized Methods of Moments (GMM) estimators are a popular tool in econometrics since introduced by Hansen (1982), because this approach provides feasible solutions for many problems present in economic data where least squares or maximum likelihood methods fail when naively applied. These problems may arise in errors-in-variable regression, estimation of labor demand curves, and asset pricing in finance, which are discussed here. In this paper we study a GMM estimator for the rank modelingapproach (RMA), which analyzes the ordinal structure of a response variable. Assuming m-dependent data consistency and asymptotic normality of the proposed estimator are shown including the important case that the instruments depend on lagged regressors.Consistent estimators for the asymptotic covariance matrices are proposed. Further, the construction of minimum variance RMA-GMM estimators is discussed. Finite sample properties are studied by a small simulation study.

Ograniczanie wyników

2 Discussiones Mathematicae Probability and Statistics

1 Antoch J.

1 Husková M.

1 Steland A.

2 2000

Wyniki wyszukiwania

Bayesian like R- and M- estimators of change points

On robust GMM estimation with applications in economics and finance