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Errors in variables in panel data

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  • Griliches, Zvi
  • Hausman, Jerry A.

Abstract

Panel data based on various longitudinal surveys have become ubiquitous in economics in recent years. Estimation using the analysis of covariance approach allows for control of various "individual effects" by estimation of the relevant relationships from the "within" dimension of the data. Quite often, however, the "within" results are unsatisfactory, "too low" and insignificant. Errors of measurement in the independent variables whose relative importance gets magnified in the within dimension are often blamed for this outcome. However, the standard errors-in-variables model has not been applied widely, partly because in the usual micro data context it requires extraneous information to identify the parameters of interest. In the panel data context a variety of errors-in-variables models may be identifiable and estimable without the use of external instruments. We develop this idea and illustrate its application in a relatively simple but not uninteresting case: the estimation of "labor demand" relationships, also known as the "short run increasing returns to scale" puzzle.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 31 (1986)
Issue (Month): 1 (February)
Pages: 93-118

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Handle: RePEc:eee:econom:v:31:y:1986:i:1:p:93-118

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Web page: http://www.elsevier.com/locate/jeconom

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References

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  1. Hausman, Jerry A, 1978. "Specification Tests in Econometrics," Econometrica, Econometric Society, vol. 46(6), pages 1251-71, November.
  2. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-98, November.
  3. Griliches, Zvi, 1979. "Sibling Models and Data in Economics: Beginnings of a Survey," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages S37-64, October.
  4. Chamberlain, Gary & Griliches, Zvi, 1975. "Unobservables with a Variance-Components Structure: Ability, Schooling, and the Economic Success of Brothers," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 16(2), pages 422-49, June.
  5. Bronwyn H. Hall & Clint Cumminq & Elizabeth S. Laderman & Joy Mundy, 1988. "The R&D Master File Documentation," NBER Technical Working Papers 0072, National Bureau of Economic Research, Inc.
  6. White, Halbert, 1982. "Instrumental Variables Regression with Independent Observations," Econometrica, Econometric Society, vol. 50(2), pages 483-99, March.
  7. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
  8. Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-58, March.
  9. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  10. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
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