|
EconStor >
The Johns Hopkins University, Baltimore, Md. >
Department of Economics, The Johns Hopkins University >
Working Papers, Department of Economics, The Johns Hopkins University >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/49889
|
| | |
Full metadata record
| DC Field | | Value | | Language |
| dc.contributor.author | | An, Yonghong | | en_US |
| dc.contributor.author | | Hu, Yingyao | | en_US |
| dc.date.accessioned | | 2010-03-19 | | en_US |
| dc.date.accessioned | | 2011-09-27T15:21:21Z | | - |
| dc.date.available | | 2011-09-27T15:21:21Z | | - |
| dc.date.issued | | 2009 | | en_US |
| dc.identifier.uri | | http://hdl.handle.net/10419/49889 | | - |
| dc.description.abstract | | It is widely admitted that the inverse problem of estimating the distribution of a latent variable X* from an observed sample of X, a contaminated measurement of X*, is ill-posed. This paper shows that measurement error models for self-reporting data are well-posed, assuming the probability of reporting truthfully is nonzero, which is an observed property in validation studies. This optimistic result suggests that one should not ignore the point mass at zero in the error distribution when modeling measurement errors in self-reported data. We also illustrate that the classical measurement error models may in fact be conditionally well-posed given prior information on the distribution of the latent variable X*. By both a Monte Carlo study and an empirical application, we show that failing to account for the property can lead to significant bias on estimation of distribution of X*. | | en_US |
| dc.language.iso | | eng | | en_US |
| dc.publisher | | Johns Hopkins Univ., Dep. of Economics Baltimore, Md. | | en_US |
| dc.relation.ispartofseries | | Working papers // the Johns Hopkins University, Department of Economics 556 | | en_US |
| dc.subject.ddc | | 330 | | en_US |
| dc.subject.keyword | | Well-posed | | en_US |
| dc.subject.keyword | | conditionally well-posed | | en_US |
| dc.subject.keyword | | ill-posed | | en_US |
| dc.subject.keyword | | inverse problem | | en_US |
| dc.subject.keyword | | Fredholm integral equation | | en_US |
| dc.subject.keyword | | deconvolution | | en_US |
| dc.subject.keyword | | measurement error model | | en_US |
| dc.subject.keyword | | self-reported data | | en_US |
| dc.subject.keyword | | survey data | | en_US |
| dc.subject.stw | | Schätztheorie | | en_US |
| dc.subject.stw | | Befragung | | en_US |
| dc.subject.stw | | Statistischer Fehler | | en_US |
| dc.subject.stw | | Theorie | | en_US |
| dc.title | | Well-posedness of measurement error models for self-reported data | | en_US |
| dc.type | | Working Paper | | en_US |
| dc.identifier.ppn | | 612116069 | | en_US |
| dc.rights | | http://www.econstor.eu/dspace/Nutzungsbedingungen | | en_US |
| Appears in Collections: | | Working Papers, Department of Economics, The Johns Hopkins University
|
| Files in This Item:
| |
|
| No. of Downloads:
| |
| last Month |
last 3 Month |
total |
|
|
|
|
|
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.
|