The Analysis of Residence Histories and Other Longitudinal Panel Data: A Semi-Markov Model Incorporating Time Varying Exogenous Variables

Northwestern University, Evanston, IL 60201, USA
Regional Science and Urban Economics (Impact Factor: 1.01). 05/1983; 13(2):271-285. DOI: 10.1016/0166-0462(83)90017-0


The analysis of residence histories and other longitudinal panel data is fraught with methodological problems. Much recent progress has been made in methods of analysis within discrete time. This paper extends the development of empirically tractable mixed continuous time stochastic models. Analysis of a sample of intra-urban residential histories identifies the effect of tenure type, age of household head, size of household and duration of stay on movement probabilities. Surprisingly, no further variation, as represented by a gamma mixing distribution over a hazard rate parameter, may be identified.

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    • "For a first-order Markov model, it would be necessary to condition upon the first outcome and only outcomes for t 2 2 would be modeled. For a renewal process, it would be necessary to condition either upon the duration of stay prior to t = 1 or upon the outcome sequences up to and including the first recorded event, although commencing analysis from the beginning of the process enables us to avoid conditioning (Pickles 1983). In any application, the actual conditioning adopted will thus depend upon the type of feedback included in the model and the data that are available or feasible to collect. "

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