Endogeneity bias and two-stage least squares: a simulation study
"In disciplines such as economics, social science, and epidemiology, estimating regression models using ordinary least squares can lead to biased estimates due to one or more of the independent variables being correlated with the error term. When such correlation is not ruled out, the covariate under suspicion is called endogeneous, and the ordinary least squares estimate of the covariate effect is typically biased and yields inconsistent estimates of the causal parameter...This thesis is a simulation study of the bias due to endogeneity, and how much of this bias is removed is determined by resorting to the 2SLS technique. The simulation study was carried out to investigate the bias under several different model assumptions, and the results are compared"--Abstract, leaf iii.
Samaranayake, V. A.
Le, Vy Khoi
Mathematics and Statistics
M.S. in Mathematics and Statistics
University of Missouri--Rolla
viii, 55 leaves
© 2006 Xujun Wang, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
Equations, Simultaneous -- Numerical solutions
Instrumental variables (Statistics)
Print OCLC #
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b5771849~S5
Wang, Xujun, "Endogeneity bias and two-stage least squares: a simulation study" (2006). Masters Theses. 3859.
This document is currently not available here.