New Wine in Old Bottles: A Sequential Estimation Technique for the LPM

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10419/20634

Full metadata record

DC Field	Value	Language
dc.creator	Horrace, William C.	-
dc.creator	Oaxaca, Ronald L.	-
dc.date	2003	-
dc.date.accessioned	2013-10-16T07:11:34Z	-
dc.date.available	2013-10-16T07:11:34Z	-
dc.date.issued	2013-10-16	-
dc.identifier	http://hdl.handle.net/10419/20634	-
dc.identifier	ppn:362201730	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/10419/20634	-
dc.description	The conditions under which ordinary least squares (OLS) is an unbiased and consistent estimator of the linear probability model (LPM) are unlikely to hold in many instances. Yet the LPM still may be the correct model or a good approximation to the probability generating process. A sequential least squares (SLS) estimation procedure is introduced that may outperform OLS in terms of finite sample bias and yields a consistent estimator. Monte Carlo simulations reveal that SLS outperforms OLS, probit and logit in terms of mean squared error of the predicted probabilities.	-
dc.language	eng	-
dc.publisher		-
dc.relation	IZA Discussion paper series 703	-
dc.rights	http://www.econstor.eu/dspace/Nutzungsbedingungen	-
dc.subject	C25	-
dc.subject	ddc:330	-
dc.subject	linear probability model	-
dc.subject	sequential least squares	-
dc.subject	consistency	-
dc.subject	Monte Carlo	-
dc.subject	Regression	-
dc.subject	Schätztheorie	-
dc.subject	Theorie	-
dc.subject	Linear Probability Model	-
dc.title	New Wine in Old Bottles: A Sequential Estimation Technique for the LPM	-
dc.type	doc-type:workingPaper	-
Appears in Collections:	EconStor

Files in This Item:

There are no files associated with this item.

DSpace JSPUI