Abstract
We study measurement error in the simplest dynamic panel data model without covariates. We start by investigating the first-order effects, on the most commonly used estimator, of the presence of measurement error. As was to be expected, measurement error renders this estimator inconsistent. However, with a slight adaptation, the estimator can be made consistent. This approach to consistent estimation is ad hoc and we next develop a systematic approach to consistent estimation. We show how to obtain the most efficient estimator from this class of consistent estimators. We illustrate our findings through an empirical example.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ahn, S.C., Schmidt, P.: Efficient estimation of models for dynamic panel data. J. Econom. 68, 5–27 (1995)
Aigner, D.J., Hsiao, C., Kapteyn, A., Wansbeek, T.: Latent variable models in econometrics. In: Griliches, Z., Intriligator, M.D. (eds.) Handbook of Econometrics, vol. 2, pp. 1321–1393. North-Holland, Amsterdam (1984)
Altonji, J.G., Siow, A.: Testing the response of consumption to income changes with (noisy) panel data. Q. J. Econ. 101, 293–328 (1987)
Anderson, T.W., Hsiao, C.: Estimation of dynamic models with error components. J. Am. Stat. Assoc. 77, 598–606 (1981)
Anderson, T.W., Hsiao, C.: Formulation and estimation of dynamic models using panel data. J. Econom. 18, 47–82 (1982)
Antman, F., McKenzie, D.: Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity. J. Dev. Stud. 43, 1057–1083 (2007)
Arellano, M., Bond, S.: Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58, 277–297 (1991)
Arellano, M., Bover, O.: Another look at the instrumental variable estimation of error-components models. J. Econom. 68, 29–51 (1995)
Biørn, E.: The measurement error problem in dynamic panel data analysis: modeling and GMM estimation, Working paper, University of Oslo, 2012
Blundell, R., Bond, S.: Initial conditions and moment restrictions in dynamic panel data models. J. Econom. 87, 115–143 (1998)
Bond, S., Hoeffler, A., Temple, J.: GMM estimation of empirical growth models, CEPR Working Paper 3048, 2001
Buonaccorsi, J.: Measurement Error, Models, Methods, and Applications. Chapman & Hall, Boca Raton (2010)
Chen, J., Ni, S., Podgursky, M.: Estimating dynamic panel data models with measurement errors with an application to school evaluation based on student test scores. In: Proceedings of the 2008 Meeting of the American Statistical Association, pp. 951–957 (2008)
Fan, Z., Sutradhar, B.C., Rao, R.P.: Bias corrected generalized method of moments and generalized quasi-likelihood inferences in linear models for panel data with measurement error. Sankhyā B. 74, 126–148 (2012)
Griliches, Z., Hausman, J.A.: Errors in variables in panel data. J. Econom. 31, 93–118 (1986)
Harris, M.N., Mátyás, L.: Performance of the operational Wansbeek-Bekker estimator for dynamic panel data models. Appl. Econ. Lett. 7, 149–153 (2000)
Juster, F.T., Suzman, R.: An overview of the Health and Retirement Study. J. Hum. Resour. 30, S7–S56 (1995)
Komunjer, I., Ng, S.: Measurement errors in dynamic models, Working paper, 2011
Magnus, J.R., Neudecker, H.: Symmetry, 0–1 matrices and Jacobians: A review. Econom. Theory 2, 157–190 (1986)
Meijer, E., Wansbeek, T.J.: Measurement error in a single regressor. Econ. Lett. 69, 277–284 (2000)
Meijer, E., Spierdijk, L., Wansbeek, T.J.: Point and set identification in linear panel data models with measurement error. Working Paper WR-941, RAND Corporation, Santa Monica, 2012
St. Clair, P., et al.: RAND HRS Data Documentation, Version L. RAND Corporation, Santa Monica (2011)
Wansbeek, T.J., Bekker, P.A.: On IV, GMM and ML in a dynamic panel data model. Econ. Lett. 51, 145–152 (1996)
Wansbeek, T.J., Kapteyn, A.: Simple estimators for dynamic panel data models with errors in the variables. In: Bewley, R., Van Hoa, T. (eds.) Contributions to Consumer Demand and Econometrics. McMillan, London (1992)
Wansbeek, T.J., Meijer, E.: Measurement Error and Latent Variables in Econometrics. North-Holland, Amsterdam (2000)
Acknowledgments
We would like to thank the symposium organizer, Brajendra Sutradhar, and an anonymous reviewer of an earlier version of this paper for their useful comments and suggestions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this paper
Cite this paper
Meijer, E., Spierdijk, L., Wansbeek, T. (2013). Measurement Error in the Linear Dynamic Panel Data Model. In: Sutradhar, B. (eds) ISS-2012 Proceedings Volume On Longitudinal Data Analysis Subject to Measurement Errors, Missing Values, and/or Outliers. Lecture Notes in Statistics(), vol 211. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6871-4_4
Download citation
DOI: https://doi.org/10.1007/978-1-4614-6871-4_4
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6870-7
Online ISBN: 978-1-4614-6871-4
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)