Titlebook: Econometrics in Theory and Practice; Festschrift for Hans Robert Galata,Helmut Küchenhoff Book 1998 Physica-Verlag Heidelberg 1998 Entschei

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Nonparameteric Regression Splines for Generalized Linear Measurement Error Modelstimate the bias, and remove it. The second method is a structural approach, where one hypothesizes a distribution for the independent variable which depends on estimable parameters. For both methods, two different knot selection methods are developed.

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Using First Differences as a Device against Multicollinearity in the original model. Moreover, we shall demonstrate that related estimation procedures also cannot be expected to provide a substantial improvement over the OLS-method. For this analysis the tools from the theory of oblique and orthogonal projectors will turn out to be extremely helpful.

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Nonparameteric Regression Splines for Generalized Linear Measurement Error Modelsonparametric regression techniques are no longer valid. This is further complicated when one instead wants to fit a generalized linear model to the collected data. We consider two different estimation techniques. The first method is the SIMEX (SIMulation Extrapolation) algorithm which attempts to es

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Different Nonlinear Regression Models with Incorrectly Observed Covariatesorder to derive models for the observed data the conditional mean and variance functions of the regression models are only expressed through functions of the observable covariates. The latent covariable is treated as a random variable that follows a normal distribution. Furthermore it is assumed tha