Returns to Lying? Identifying the Effects of Misreporting When the Truth is Unobserved
Consider an observed binary regressor D and an unobserved binary variable D*, both of which affect some other variable Y. This paper considers nonparametric identification and estimation of the effect of D on Y, conditioning on D*=0. For example, suppose Y is a person's wage, the unobserved D* indicates if the person has been to college, and the observed D indicates whether the individual claims to have been to college. This paper then identifies and estimates the difference in average wages between those who falsely claim college experience versus those who tell the truth about not having college. We estimate this average effect of lying to be about 6% to 20%. Nonparametric identification without observing D* is obtained either by observing a variable V that is roughly analogous to an instrument for ordinary measurement error, or by imposing restrictions on model error moments.
|Date of creation:||28 Nov 2007|
|Date of revision:||16 Jun 2009|
|Note:||previously titled "Identifying the Returns to Lying When the Truth is Unobserved"|
|Contact details of provider:|| Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA|
Web page: http://fmwww.bc.edu/EC/
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- Chen, Xiaohong & Hu, Yingyao & Lewbel, Arthur, 2008.
"Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments,"
Elsevier, vol. 100(3), pages 381-384, September.
- Xiaohong Chen & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric Identification of Regression Models Containing a Misclassified Dichotomous Regressor Without Instruments," Boston College Working Papers in Economics 675, Boston College Department of Economics.
- Xiaohong Chen & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments," CeMMAP working papers CWP17/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Richard W. Blundell & James L. Powell, 2004. "Endogeneity in Semiparametric Binary Response Models," Review of Economic Studies, Oxford University Press, vol. 71(3), pages 655-679.
- Richard Blundell & James L. Powell, 2001. "Endogeneity in semiparametric binary response models," CeMMAP working papers CWP05/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Chunrong Ai & Xiaohong Chen, 2003. "Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions," Econometrica, Econometric Society, vol. 71(6), pages 1795-1843, November. Full references (including those not matched with items on IDEAS)
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