کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5097627 | 1478585 | 2006 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Identification and estimation with contaminated data: When do covariate data sharpen inference?
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Contaminated or corrupted data typically require strong assumptions to identify parameters of interest. However, weaker assumptions often identify bounds on these parameters. This paper addresses when covariate data-variables in addition to the one of interest-tighten these bounds. First, we construct the identification region for the distribution of the variable of interest. This region demonstrates that covariate data are useless without knowledge about the distribution of erroneous data conditional on the covariates. Then, we develop bounds both on probabilities and on parameters of this distribution that respect stochastic dominance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 130, Issue 2, February 2006, Pages 253-272
Journal: Journal of Econometrics - Volume 130, Issue 2, February 2006, Pages 253-272
نویسندگان
Charles H. Mullin,