Time to Demystify Endogeneity Bias

Investigating Endogeneity Bias in Conjoint Models

The use of adaptive designs in conjoint analysis has been shown to lead to an endogeneity bias in part-worth estimates using sampling experiments. In this paper, we re-examine the endogeneity issue in light of the likelihood principle. The likelihood principle asserts that all relevant information in the data about model parameters is contained in the likelihood function. We show that adhering ...

Bayesian Endogeneity Bias Modeling ∗ Gabriel Montes - Rojas † Antonio

We propose to model endogeneity bias using prior distributions of moment conditions. The estimator can be obtained both as a method-of-moments estimator and in a Ridge penalized regression framework. We show the estimator’s relation to a Bayesian estimator.

Demystify statistical significance--time to move on from the p value to bayesian analysis.

Attempting to demystify law reports for the non-lawyer.

To a non-lawyer, references to law reports can appear confusing and complicated. This brief article attempts to explain how to decode such references and thus get to the reports. Those wishing to pursue the matter further are referred to more detailed explanations. This article deals primarily with English case law and is up to date as of December 1987.

Supplement to “ Endogeneity in High Dimensions ”

This supplementary material contains the proof of Theorem 7.1 in the main paper. The following lemma is useful. Lemma 0.1. For a general loss function Ln, suppose it is twice differentiable in a neighborhood of β0. Assume max l / ∈S ∣∣∣∣∂Ln(β0) ∂βl ∣∣∣∣ = op(P ′ n(0)), (0.1) and there is a neighborhood U ⊂ R of β0S such that sup βS∈U max l / ∈S,j∈S ∣∣∣∣∂2Ln(βS, 0) ∂βl∂βj ∣∣∣∣ = op(P ′ n(0) skn ...