When Random Group Effects are Cross-Correlated: An Application to Elderly Migration Flow Models

Author(s)/Creator(s)

Karen S. Conway, University of New Hampshire - Main Campus
Andrew J. Houtenville, University of New Hampshire - Main Campus

Description/Abstract

Incorporating random group effects has proven important to making correct statistical inferences about factors that only vary across groups. We note that it is possible to have more than one random effect in models using cross-sectional data and that these random effects could be correlated, unlike in the typical panel data situation. Extending the standard multiple random effects model in this way is greatly simplified by using the two-step estimator we develop. Our application to an elderly migration flow model provides an intuitive example of cross-correlated random group effects and demonstrates the ease of our estimator, as well as highlighting the empirical importance of controlling for random effects.

Document Type

Working Paper

Date

10-1998

Language

English

Funder(s)

National Institute on Aging

Funding ID

P20-AG12837

Series

Aging Studies Program Paper Series

Disciplines

Economic Policy | Economics | Public Affairs, Public Policy and Public Administration | Public Policy

ISSN

1084-1695

Additional Information

Aging studies program paper no.15

Recommended Citation

Conway, Karen S. and Houtenville, Andrew J., "When Random Group Effects are Cross-Correlated: An Application to Elderly Migration Flow Models" (1998). Center for Policy Research. 432.
https://surface.syr.edu/cpr/432

Source

Local Input

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.