An Investigation Of Generalized Rakingin The Synthetic Estimation Ofpopulation Size
The problem of counting a population that is cross-classified with respect to demographic and geographic attributes is considered. A census is conducted in which individuals are “captured” with probabilities that are believed to be relatively constant within demographic categories. The census is followed by a random sample in which individuals are “recaptured” independently of the census. Using the two counts, capture-recapture estimates of the demographic category populations are obtained. A synthetic estimate of population size for a geographic entity is obtained by summing the corresponding adjustment factors (capture-recapture estimates divided by census counts) across all individuals captured by the census in the entity. The use of generalized raking is considered as a method for smoothing adjustment factors. It is found that generalized raking differs little from a class of weighted least squares regression models. This suggests that generalized raking does not offer an improvement over regression for smoothing adjustment factors. The efficiency loss of generalized raking relative to the best regression-based procedures can be substantial.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 11 (2004)
Issue (Month): 1 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/GMPS20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/GMPS20|
When requesting a correction, please mention this item's handle: RePEc:taf:mpopst:v:11:y:2004:i:1:p:29-49. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.