Comparing the asymptotic and empirical (un)conditional distributions of OLS and IV in a linear static simultaneous equation

DOI10.1016/j.csda.2010.07.028zbMath1255.62360OpenAlexW2128723827MaRDI QIDQ1927137

Jerzy Niemczyk, Jan F. Kiviet

Publication date: 30 December 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2010.07.028

zbMATH Keywords

conditioningweak instrumentssimultaneity biasefficiency comparisonsMonte Carlo designinconsistent estimation

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Monte Carlo methods (65C05)

Related Items (3)

SUBSET HYPOTHESES TESTING AND INSTRUMENT EXCLUSION IN THE LINEAR IV REGRESSION ⋮ Testing the impossible: identifying exclusion restrictions ⋮ The unconditional distributions of the OLS, TSLS and LIML estimators in a simple structural equations model

Cites Work

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• Should stochastic or non-stochastic exogenous variables be used in Monte Carlo experiments?
• A NEW ASYMPTOTIC THEORY FOR HETEROSKEDASTICITY-AUTOCORRELATION ROBUST TESTS
• YET MORE ON THE EXACT PROPERTIES OF IV ESTIMATORS
• Specification Tests in Econometrics

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