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Identification-robust inference for endogeneity parameters in linear structural models

Doko Tchatoka, Firmin; Dufour, Jean-Marie - In: The econometrics journal 17 (2014) 1, pp. 165-187

Persistent link: https://www.econbiz.de/10010498748

Identification-Robust Inference for Endogeneity Parameters in Linear Structural Models

Doko Tchatoka, Firmin - 2014

dependence between possibly endogenous explanatory variables and disturbances in a linear structural equation (endogeneity … parameters). We focus on second-order dependence and stress the distinction between regression and covariance endogeneity … with least-square methods). We observe that endogeneity parameters may not be identifiable and we give the relevant …

Persistent link: https://www.econbiz.de/10013057771

Simulation-based finite-sample linearity test against smooth transition models

González, Andrés (contributor); … - 2005

In this paper we use Monte Carlo testing techniques for testing linearity against the smooth transition models. The Monte Carlo approach allows us to introduce a new test that differs from the tests existing in the literature in two respects. First, the test is exact in the sense that the...

Persistent link: https://www.econbiz.de/10003073820

Risk Premium Estimation with Multicollinear and Invariant Betas by the Two-Pass Cross-Sectional Regressions

Ahn, Seung C. - 2011

This paper analyzes the finite-sample performance of the two-pass (TP) estimators of factor risk prices when betas have high cross-sectional correlations (Multicollinear) and when betas have small cross-sectional variations (Invariant). Our Monte Carlo simulations, calibrated using actual...

Persistent link: https://www.econbiz.de/10013133797

Two-Pass Cross-Sectional Regression of Factor Pricing Models : A Minimum Distance Approach

Ahn, Seung C. - 2011

This paper examines the asymptotic and finite sample properties of the two-pass cross-sectional regressions estimators, when the factors and the asset returns are conditionally heteroskedastic and/or autocorrelated. Using a minimum distance approach, we derive heteroskedasticity- and/or...

Persistent link: https://www.econbiz.de/10013134108

A Simple Test for Linearity Against Exponential Smooth Transition Models with Endogenous Variables

Massacci, Daniele - 2017

This paper proposes a test for linearity against exponential smooth transition models with endogenous right-hand-side variables: to the very best of our knowledge, this class of models is new to the literature. By Monte Carlo analysis the test is shown to have good finite sample properties

Persistent link: https://www.econbiz.de/10014176554

The Phantom Menace of Omitted Variables – a Comment

Ritter, Nolan; Vance, Colin - 2011

This note demonstrates that in applied regression analysis, the variance of a coefficient of interest may decrease from the inclusion of a control variable, contrasting with Clarke’s assertion (2005, 2009) that the variance can only increase or stay the same. Practitioners may thus be...

Persistent link: https://www.econbiz.de/10014177659

New Solution to Time Series Inference in Spurious Regression Problems

Vinod, Hrishikesh D. - 2010

Phillips (1986) provides asymptotic theory for regressions that relate nonstationary time series including those integrated of order 1, I(1). A practical implication of related literature on spurious regression is that one cannot trust the usual confidence intervals. Therefore it is recommended...

Persistent link: https://www.econbiz.de/10014197508

Finite-Sample Generalized Confidence Distributions and Sign-Based Robust Estimators In Median Regressions with Heterogeneous Dependent Errors

Coudin, Elise - 2017

We study the problem of estimating 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,...

Persistent link: https://www.econbiz.de/10012962776

Testing Identifying Assumptions in Regression Discontinuity Designs

Hsu, Yu‐Chin - 2016

We propose a test for the key identification and estimation conditions in Regression Discontinuity (RD) designs. We characterize the set of sharp testable implications of the RD assumptions, for which the proposed test is uniformly valid under a class of distributions, is consistent against all...

Persistent link: https://www.econbiz.de/10012987628