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MEASUREMENT ERRORS AND CENSORED STRUCTURAL LATENT VARIABLES MODELS

Published online by Cambridge University Press:  25 November 2011

Songnian Chen ,
Cheng Hsiao  and
Liqun Wang
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Abstract

We consider censored structural latent variables models where some exogenous variables are subject to additive measurement errors. We demonstrate that overidentification conditions can be exploited to provide natural instruments for the variables measured with errors, and we propose a two-stage estimation procedure. The first stage involves substituting available instruments in lieu of the variables that are measured with errors and estimating the resulting reduced form parameters using consistent censored regression methods. The second stage obtains structural form parameters using the conventional linear simultaneous equations model estimators.

Type
Brief Report
Information
Econometric Theory , Volume 28 , Issue 3 , June 2012 , pp. 696 - 703
Copyright
Copyright © Cambridge University Press 2011

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Footnotes

We are deeply appreciative of the very helpful comments of a co-editor and two referees. We also thank T. Amemiya for helpful comments. This research is partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC). Part of this work was carried out while the first author was at the National University of Singapore.

References

REFERENCES

Aigner, D.J., Hsiao, C., Kapteyn, A., & Wansbeek, T. (1984) Latent variable models in econometrics. In Griliches, Z. & Intriligator, M.D. (eds.), Handbook of Econometrics, vol. II, pp. 1321–1393. North-Holland.CrossRefGoogle Scholar
Amemiya, T. (1973) Regression analysis when the dependent variable is truncated normal. Econometrica 41, 997–1016.CrossRefGoogle Scholar
Amemiya, T. (1974) Multivariate regression and simultaneous equation models when the dependent variables are truncated normal. Econometrica 42, 999–1012.CrossRefGoogle Scholar
Amemiya, T. (1979) The estimation of a simultaneous equation Tobit model. International Economic Review 20, 169–181.CrossRefGoogle Scholar
Carroll, R.J., Ruppert, D., Stefanski, L.A., & Crainiceanu, C. (2006) Measurement Error in Nonlinear Models: A Modern Perspective, 2nd ed. Chapman and Hall.CrossRefGoogle Scholar
Fang, K.T. & Zhang, Y.T. (1990) Generalized Multivariate Analysis. Springer-Verlag.Google Scholar
Fisher, F.M. (1966) The Identification Problem in Econometrics. McGraw-Hill.Google Scholar
Geraci, V.J. (1976) Identification of simultaneous equation models with measurement error. Journal of Econometrics 4, 263–283.CrossRefGoogle Scholar
Hsiao, C. (1976) Identification and estimation of simultaneous equation models with measurement error. International Economic Review 17, 319–339.CrossRefGoogle Scholar
Hsiao, C. (1977) Identification for a linear dynamic simultaneous error-shock model. International Economic Review 18, 181–194.CrossRefGoogle Scholar
Hsiao, C. (1979) Measurement error in a dynamic simultaneous equations model with stationary disturbances. Econometrica 47, 475–494.CrossRefGoogle Scholar
Hsiao, C. (1983) Identification. In Griliches, Z. & Intriligator, M.D. (eds.), Handbook of Econometrics, vol. I, pp. 223–284. North-Holland.CrossRefGoogle Scholar
Koopmans, T.C. & Hood, W. (1953) The estimation of simultaneous linear economic relationships. In Hood, W.C. & Koopmans, T.C. (eds.), Studies in Econometric Methods, pp. 112–199. Wiley.Google Scholar
Maddala, G.S. (1983) Limited-Dependent and Qualitative Variables Economics. Cambridge University Press.CrossRefGoogle Scholar
Powell, J.L. (1984) Least absolute deviations estimation of the censored regression models. Journal of Econometrics 25, 303–325.CrossRefGoogle Scholar
Powell, J.L. (1986) Symmetrically trimmed least squares estimation of Tobit models. Econometrica 54, 1435–1460.CrossRefGoogle Scholar
Wang, L. & Hsiao, C. (2011) Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models. Journal of Econometrics; doi:10.1016/j.jeconom.2011.05.004.CrossRefGoogle Scholar