Finite-sample generalized confidence distributions and sign-based robust estimators in median regressions with heterogeneous dependent errors

Robust Sign-Based and Hodges-Lehmann Estimators in Linear Median Regressions with Heterogenous Serially Dependent Errors

We propose estimators for the parameters of a linear median regression without any assumption on the shape of the error distribution – including no condition on the existence of moments – allowing for heterogeneity (or heteroskedasticity) of unknown form, noncontinuous distributions, and very general serial dependence (linear or nonlinear) including GARCH-type and stochastic volatility of unkno...

Confidence Intervals Based on Robust Estimators

Finite-sample Exact Tests for Linear Regressions with Bounded Dependent Variables

We introduce tests for finite-sample linear regressions with heteroskedastic errors. The tests are exact, i.e., they have guaranteed type I error probabilities when bounds are known on the range of the dependent variable, without any assumptions about the noise structure. We provide upper bounds on probability of type II errors, and apply the tests to empirical data.

Bayesian Generalized Errors in Variables (geiv) Models for Censored Regressions

Errors in variables models in linear regression are an old and important theoretical topic, but rather neglected in applied statistics. This is especially true for Bayesian statistics where the numerical diiculties for the estimation of the models are even greater. Using a Bayesian approach and modern numerical integration techniques (the Gibbs sampler) we derive the necessary full conditional ...

Residual-Based Finite-Sample Misspecification Tests in Multivariate Regressions with Applications to Asset Pricing Models

In Multivariate Linear Regression (MLR) models, multi-equation diagnostic tests pose some problems not encountered in the analysis of univariate models. In particular, test size distortions grow quickly as the number of cross-equation correlations increases. Despite the widespread recognition of this problem, finite sample multivariate specification tests are rare. In this paper, we propose a g...