Bayesian Endogeneity Bias Modeling ∗ Gabriel Montes - Rojas † Antonio

Instrumental Variables Quantile Regression for Panel Data with Measurement Errors∗

This paper develops an instrumental variables estimator for quantile regression in panel data with fixed effects. Asymptotic properties of the instrumental variables estimator are studied for large N and T when Na/T → 0, for some a > 0. Wald and Kolmogorov-Smirnov type tests for general linear restrictions are developed. The estimator is applied to the problem of measurement errors in variables...

Non-uniform Wealth Distribution in a Simple Spatial Banking Model

MS #2007-0051-2 Inter-city compensating wage differentials and intra-city workplace centralization (Old title: An inter-urban wage test of the monocentric model)

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 ...

Testing linearity against threshold effects: uniform inference in quantile regression

This paper develops a uniform test of linearity against thresholds effects in the quantile regression framework. The test is based on the supremum of the Wald process over the space of quantile and threshold parameters. We establish the asymptotic null distribution of the test statistic for stationary weakly dependent processes, and propose a simulation method to approximate the critical values...