Template-Type: ReDIF-Paper 1.0
Author-Name: Tue Gørgens
Author-X-Name-First: Tue
Author-X-Name-Last: Gørgens
Author-Email: tue.gorgens@anu.edu.au
Author-Workplace-Name: Australian National University
Author-Name: Dean Hyslop
Author-X-Name-First: Dean
Author-X-Name-Last: Hyslop
Author-Email: dean.hyslop@motu.org.nz 
Author-Workplace-Name: Motu Economic and Public Policy Research
Title: The specification of dynamic discrete-time two-state panel data models
Abstract: This paper examines dynamic binary response and multi-spell duration model approaches to analyzing longitudinal discrete-time binary outcomes. Prototypical dynamic binary response models specify low-order Markovian state dependence and restrict the effects of observed and unobserved heterogeneity on the probability of transitioning into and out of a state to have the same magnitude and opposite signs. In contrast, multi-spell duration models typically allow for state-specific duration dependence, and allow the probability of entry into and exit from a state to vary flexibly. We show that both of these approaches are special cases within a general framework. We compare specific dynamic binary response and multi-spell duration models empirically using a case study of poverty transitions. In this example, both the specification of state dependence and the restrictions on the state-specific transition probabilities imposed by the simpler dynamic binary response models are severely rejected against the more flexible multi-spell duration models. Consistent with recent literature, we conclude that the standard dynamic binary response model is unacceptably restrictive in this context.
Length: 61 pages
Creation-Date:  2016-02
File-URL: https://motu-www.motu.org.nz/wpapers/16_01.pdf
Number: 16_01
Classification-JEL: C33, C35, C41, C51
Keywords: Panel data, transition data, binary response, duration analysis, event history analysis, initial conditions, random effects.
Handle: RePEc:mtu:wpaper:16_01