Modeling approaches to the indirect estimation of migration flows: From entropy to EM
The paper presents probability models to recover information on migration flows from incomplete data. Models are used to predict migration and to combine data from different sources. The parameters of the model are estimated from the data by the maximum likelihood method. If data are incomplete, an extension of the maximum likelihood method, the EM algorithm, may be applied. Two models are considered: the binomial (multinomial) model, which underlies the logit model and the logistic regression, and the Poisson model, which underlies the loglinear model, the log-rate model and the Poisson regression. The binomial model is viewed in relation to the Poisson model. By way of illustration, the probabilistic approach and the EM algorithm are applied to two different missing data problems. The first problem is the prediction of migration flows using spatial interaction models. The probabilistic approach is compared to conventional methods, such as the gravity model and entropy maximization. In fact, spatial interaction models are particular variants of log-linear models. The second problem is one of unobserved heterogeneity. A mixture model is applied to determine the relative sizes of different migrant categories.
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): 7 (1999)
Issue (Month): 3 ()
|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:7:y:1999:i:3:p:239-278. 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.