Using Heteroscedasticity to Identify and
Estimate Mismeasured and Endogenous
Regressor Models
Arthur LEWBEL
Department of Economics, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467
(lewbel@bc.edu)
This article proposes a new method of obtaining identification inmismeasured regressormodels, triangular
systems, and simultaneous equation systems. The method may be used in applications where other sources
of identification, such as instrumental variables or repeated measurements, are not available. Associated
estimators take the form of two-stage least squares or generalized method of moments. Identification comes
from a heteroscedastic covariance restriction that is shown to be a feature of many models of endogeneity
or mismeasurement. Identification is also obtained for semiparametric partly linear models, and associated
estimators are provided. Set identification bounds are derived for cases where point-identifying assumptions
fail to hold. An empirical application estimating Engel curves is provided.
KEY WORDS: Endogeneity; Heteroscedastic errors; Identification; Measurement error; Partly linear
model; Simultaneous system.


https://bbs.pinggu.org/thread-7366896-1-1.html
https://bbs.pinggu.org/thread-8019112-1-1.html
https://econpapers.repec.org/article/tsjstataj/
http://www.360doc.com/content/20/0526/21/45289182_914727486.shtml