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Censored Regressors and Expansion Bias

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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


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