Titlebook: Robustness in Econometrics; Vladik Kreinovich,Songsak Sriboonchitta,Van-Nam Hu Book 2017 Springer International Publishing AG 2017 Computa

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Robust Estimation of Heckman Modelnciples can be used to carry out a robustness analysis in [.] model and how to construct robust versions of Heckman’s two-stage estimator. These are central tools for the statistical analysis of data based on non-random samples from a population.

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heterogeneous

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New Estimation Method for Mixture of Normal Distributions obtain initial estimates of parameters; then upgrade the estimates to better estimates recursively. The initial estimates are simply Method of Moments Estimates in this paper. Empirical results show that parameter estimates are more accurate than that with traditional EM and SEM algorithms.

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1860-949X he field.Includes supplementary material: This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focu

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Introduction

Why Cannot We Have a Strongly Consistent Family of Skew Normal (and Higher Order) Distributionsution. However, this selection is not strongly consistent in the above sense. In this paper, we show that this absence of strong consistency is not a fault of a specific selection but a general feature of the problem: for third and higher order moments, no strongly consistent selection is possible.

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