Censored Regressors and Expansion Bias

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5054

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DC Field	Value	Language
dc.creator	Rigobon, Roberto	-
dc.creator	Stoker, Thomas M.	-
dc.date	2004-03-12T19:51:06Z	-
dc.date	2004-03-12T19:51:06Z	-
dc.date	2004-03-12T19:51:06Z	-
dc.date.accessioned	2013-10-09T02:37:26Z	-
dc.date.available	2013-10-09T02:37:26Z	-
dc.date.issued	2013-10-09	-
dc.identifier	http://hdl.handle.net/1721.1/5054	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	We show how using censored regressors leads to expansion bias, or estimated effects that are proportionally too large. We show the necessity of this effect in bivariate regression and illustrate the bias using results for normal regressors. We study the bias when there is a censored regressor among many regressors, and we note how censoring can work to undo errors-in-variables bias. We discuss several approaches to correcting expansion bias. We illustrate the concepts by considering how censored regressors can arise in the analysis of wealth effects on consumption, and on peer effects in productivity.	-
dc.format	1193476 bytes	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	MIT Sloan School of Management Working Paper;4451-03	-
dc.subject	Censored Regressors	-
dc.subject	Expansion Bias	-
dc.title	Censored Regressors and Expansion Bias	-
dc.type	Working Paper	-
Appears in Collections:	MIT Items

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