Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left
The effect of mismeasured variables in the most straightforward regression analysis with a single regressor variable leads to a least squares estimate that is downward biased in magnitude toward zero. I begin by reviewing classical issues involving mismeasured variables. I then consider three recent developments for mismeasurement econometric models. The first issue involves difficulties in using instrumental variables. A second involves the consistent estimators that have recently been developed for mismeasured nonlinear regression models. Finally, I return to mismeasured left hand side variables, where I will focus on issues in binary choice models and duration models.
Volume (Year): 15 (2001)
Issue (Month): 4 (Fall)
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- Aigner, Dennis J. & Hsiao, Cheng & Kapteyn, Arie & Wansbeek, Tom, 1984. "Latent variable models in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 23, pages 1321-1393 Elsevier.
- Aigner, Dennis J., 1973. "Regression with a binary independent variable subject to errors of observation," Journal of Econometrics, Elsevier, vol. 1(1), pages 49-59, March.
- David Card, 2000.
"Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems,"
NBER Working Papers
7769, National Bureau of Economic Research, Inc.
- Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-60, September.
- Amemiya, Yasuo, 1985. "Instrumental variable estimator for the nonlinear errors-in-variables model," Journal of Econometrics, Elsevier, vol. 28(3), pages 273-289, June.
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