Model-based incomplete data analysis with an application to occupational mobility and migration accounts
Stuart Sweeney
Mathematical Population Studies, 1999, vol. 7, issue 3, 279-305
Abstract:
In many planning and policy research settings available secondary data sources may be incapable of answering pertinent research questions because certain variable combinations are unavailable. One solution to this constraint is to try to construct the desired data using information from multiple data sources and prior information. Current methods for accomplishing this task tend to focus predominantly on updating transaction matrices (input-output tables, transportation flows, or interregional migration accounts) and emphasize an algorithmic approach to the problem. This paper attempts to broaden the applications and generalize the solution by extending the model-based approach to incomplete data analysis advocated by Willekens (1982). The log-linear model is presented here as a flexible platform for incomplete data analysis and a path diagram describes several alternative modeling approaches; different paths are determined by the level of available information. The paper concludes with an application to incomplete occupational migration and mobility tables.
Keywords: Incomplete Data; Log-linear models; Generalized linear models; Occupational Migration and Mobility (search for similar items in EconPapers)
Date: 1999
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/08898489909525460 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:mpopst:v:7:y:1999:i:3:p:279-305
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GMPS20
DOI: 10.1080/08898489909525460
Access Statistics for this article
Mathematical Population Studies is currently edited by Prof. Noel Bonneuil, Annick Lesne, Tomasz Zadlo, Malay Ghosh and Ezio Venturino
More articles in Mathematical Population Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().