Bias from Classical and Other Forms of Measurement Error
AbstractWe consider the implications of an alternative to the classical measurement-error model, in which the observed, mismeasured data are optimal predictions of the true values, given some information set. In this model, any measurement error is uncorrelated with the reported value and, by necessity, correlated with the true value of interest. In a regression model, such measurement error in the regressor does not lead to bias, whereas measurement error in the dependent variable leads to bias toward 0. In general, the measurement-error model, together with the information set, is critical for determining the bias in econometric estimates.
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 19 (2001)
Issue (Month): 4 (October)
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Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main
Other versions of this item:
- Dean R. Hyslop & Guido W. Imbens, 2000. "Bias from Classical and Other Forms of Measurement Error," NBER Technical Working Papers 0257, National Bureau of Economic Research, Inc.
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- David Card & Dean Hyslop, 1997.
"Does Inflation “Grease the Wheels of the Labor Market”?,"
in: Reducing Inflation: Motivation and Strategy, pages 71-122
National Bureau of Economic Research, Inc.
- David Card & Dean Hyslop, 1996. "Does Inflation "Grease the Wheels of the Labor Market"?," NBER Working Papers 5538, National Bureau of Economic Research, Inc.
- David Card & Dean Hyslop, 1995. "Does Inflation 'Grease the Wheels of the Labor Market'?," Working Papers 735, Princeton University, Department of Economics, Industrial Relations Section..
- Orley Ashenfelter & Alan Krueger, 1992.
"Estimates of the Economic Return to Schooling from a New Sample of Twins,"
683, Princeton University, Department of Economics, Industrial Relations Section..
- Ashenfelter, Orley & Krueger, Alan B, 1994. "Estimates of the Economic Returns to Schooling from a New Sample of Twins," American Economic Review, American Economic Association, vol. 84(5), pages 1157-73, December.
- Alan Krueger & Orley Ashenfelter, 1992. "Estimates of the Economic Return to Schooling from a New Sample of Twins," NBER Working Papers 4143, National Bureau of Economic Research, Inc.
- Bound, John & Krueger, Alan B, 1991.
"The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?,"
Journal of Labor Economics,
University of Chicago Press, vol. 9(1), pages 1-24, January.
- John Bound & Alan B. Krueger, 1989. "The Extent of Measurement Error In Longitudinal Earnings Data: Do Two Wrongs Make A Right?," NBER Working Papers 2885, National Bureau of Economic Research, Inc.
- Joshua Angrist & Alan Krueger, 1998.
"Empirical Strategies in Labor Economics,"
98-7, Massachusetts Institute of Technology (MIT), Department of Economics.
- Das, J.W.M. & Dominitz, J. & Soest, A.H.O. van, 1998.
"Comparing predictions and outcomes: theory and application to income changes,"
Open Access publications from Tilburg University
urn:nbn:nl:ui:12-121742, Tilburg University.
- Das, J.W.M. & Dominitz, J. & Soest, A.H.O. van, 1997. "Comparing Predictions and Outcomes: Theory and Application to Income Changes," Discussion Paper 1997-45, Tilburg University, Center for Economic Research.
- Edward Leamer, 1906.
"Errors in Variables in Linear Systems,"
UCLA Economics Working Papers
406, UCLA Department of Economics.
- N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
- repec:att:wimass:8905 is not listed on IDEAS
- Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
- Pischke, J.S., 1994.
"Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study,"
94-01, Massachusetts Institute of Technology (MIT), Department of Economics.
- Pischke, Jorn-Steffen, 1995. "Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 305-14, July.
- Klepper, Steven & Leamer, Edward E, 1984. "Consistent Sets of Estimates for Regressions with Errors in All Variables," Econometrica, Econometric Society, vol. 52(1), pages 163-83, January.
- Card, David, 1996. "The Effect of Unions on the Structure of Wages: A Longitudinal Analysis," Econometrica, Econometric Society, vol. 64(4), pages 957-79, July.
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