Calibrating longitudinal models of residential mobility and migration An assessment of a non-parametric marginal likelihood approach

This paper discusses the problems of controlling for omitted variables in estimating the structural parameters of longitudinal models and focuses upon an assessment of a nonparametric marginal maximum likelihood approach suggested by the results of Laird (1978). The approach is shown to be statistic...

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Bibliographic Details
Published in:Regional science and urban economics 1984-05, Vol.14 (2), p.231-247
Main Authors: Davies, Richard B., Crouchley, Robert
Format: Article
Language:English
Subjects:
Americas
Beta
Demography
Developed Countries
Developing Countries
Economic models
Economic theory
Emigration and Immigration
Geography
Longitudinal Studies
Migration
Mobility
Models, Theoretical
North America
Population
Population Dynamics
Probability
Residence Characteristics
Residence/Residences/Residential/ Resident/ Residents
Statistical analysis
Statistical methods
Statistics/Statistical/ Statistically
United States
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Summary:This paper discusses the problems of controlling for omitted variables in estimating the structural parameters of longitudinal models and focuses upon an assessment of a nonparametric marginal maximum likelihood approach suggested by the results of Laird (1978). The approach is shown to be statistically valid for a plausible discrete-time model of the incidence of residential or migration moves, at least for data in which no household moves in every time period. Empirical evaluation with two large datasets on residential mobility indicates that the approach is also computationally feasible and provides a promising alternative to more conventional methods for controlling for omitted variables.
ISSN:0166-0462
1879-2308
DOI:10.1016/0166-0462(84)90025-5