Minimum distance estimation of the errors-in-variables model using linear cumulant equations

DOI10.1016/j.jeconom.2014.05.011zbMath1312.62086OpenAlexW3123423818MaRDI QIDQ473243

Timothy Erickson, Toni M. Whited, Colin Huan Jiang

Publication date: 24 November 2014

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2014.05.011

zbMATH Keywords

errors-in-variablesinvestmentleveragehigher cumulants

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (6)

Simulated minimum distance estimation of dynamic models with errors-in-variables ⋮ EIV regression with bounded errors in data: total `least squares' with Chebyshev norm ⋮ Dynamic deconvolution and identification of independent autoregressive sources ⋮ IDENTIFICATION OF LINEAR REGRESSIONS WITH ERRORS IN ALL VARIABLES ⋮ Measurement error in multiple equations: Tobin's \(q\) and corporate investment, saving, and debt ⋮ Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Consistent moment estimators of regression coefficients in the presence of errors in variables
• On estimating the slope of a straight line when both variables are subject to error
• Higher moment estimators for linear regression models with errors in the variables
• Consistent Sets of Estimates for Regressions with Errors in All Variables
• Regression with errors in variables: estimators based on third order moments
• The Fitting of Straight Lines When both Variables are Subject to Error
• The Estimation of Economic Relationships using Instrumental Variables
• Identification in the Linear Errors in Variables Model
• Comment on Identification in the Linear Errors in Variables Model
• Wald Tests and Systems of Stochastic Equations
• On the Asymptotic Bias of Wald-Type Estimators of a Straight Line when Both Variables are Subject to Error
• Constructing Instruments for Regressions With Measurement Error When no Additional Data are Available, with An Application to Patents and R&D
• TWO-STEP GMM ESTIMATION OF THE ERRORS-IN-VARIABLES MODEL USING HIGH-ORDER MOMENTS
• Panel Data Econometrics
• A separability result for gmm estimation, with applications to gls prediction and conditional moment tests
• Nonparametric Identification and Semiparametric Estimation of Classical Measurement Error Models Without Side Information
• Consumption-Based Asset Pricing with Higher Cumulants
• GMM ESTIMATION FOR DYNAMIC PANELS WITH FIXED EFFECTS AND STRONG INSTRUMENTS AT UNITY
• Identifiability of a Linear Relation between Variables Which Are Subject to Error
• Confluence Analysis by Means of Lag Moments and Other Methods of Confluence Analysis

This page was built for publication: Minimum distance estimation of the errors-in-variables model using linear cumulant equations