Compare methods

	Discrete-Time Hazard of Migration	Life-Course Event History of Migration
Field	Migration Studies	Migration Studies
Family	Survival analysis	Survival analysis
Year of origin	1982	1990
Originator	Paul D. Allison	Daniel Courgeau; Hill Kulu & Nadja Milewski
Type	Discrete-time hazard model of migration timing	Multi-state, multi-episode event-history model of interdependent life-course processes
Seminal source	Allison, P. D. (1982). Discrete-Time Methods for the Analysis of Event Histories. Sociological Methodology, 13, 61-98.	Kulu, H., & Milewski, N. (2007). Family Change and Migration in the Life Course: An Introduction. Demographic Research, 17, 567-590.
Aliases	Person-Period Logit Migration Model, Allison Discrete-Time Event-History Model, Annual-Data Hazard of Moving, Complementary Log-Log Migration Model	Multi-State Migration Event History, Interdependent Processes Migration Model, Parallel-Careers Hazard Analysis, Simultaneous-Equations Event History of Migration
Related	3	3
Summary	The discrete-time hazard model analyzes the timing of migration when the data arrive in chunks of time — usually person-years — rather than as exact dates. Paul Allison's 1982 formulation showed that an event history measured in discrete periods can be analyzed by a remarkably simple device: expand each person into one record per period they are at risk, mark whether the move happened in that period, and fit an ordinary binary regression (logit or complementary log-log) for the conditional probability of moving. The baseline period enters as a set of terms capturing duration dependence — how the risk of moving rises or falls with time elapsed — and covariates can change from period to period. Because annual migration data are the norm in panels and registers, this person-period approach has become the standard event-history tool in migration research, sitting alongside the continuous-time Cox model and extending naturally to competing destinations and repeat moves. Its great practical virtue is that the entire apparatus reduces to a logistic regression any analyst can run.	Life-course event-history analysis treats migration not as an isolated event but as one thread in a web of parallel biographies — partnership, childbearing, education, and employment — that unfold together and influence one another over a lifetime. Building on Daniel Courgeau's program of analyzing migration alongside family and career and on Kulu and Milewski's synthesis of family change and migration, the approach models several multi-state, multi-episode processes at once and asks how transitions in one career trigger or delay moves in another. Methodologically it generalizes the single-event hazard model in three ways: it allows repeated episodes (people move more than once and pass through many states), it lets the current states of parallel processes enter as time-varying causes of migration, and, in its most demanding form, it estimates the processes jointly as a simultaneous-equations system with correlated unobserved heterogeneity to separate genuine causal interdependence from shared selection. The payoff is a model of migration that respects its embeddedness in the rest of the life course.