Compare methods

	Intention-to-Migrate Prediction	Discrete-Time Hazard of Migration
Field	Migration Studies	Migration Studies
Family	Regression model	Survival analysis
Year of origin	2002	1982
Originator	Jorgen Carling; Hein de Haas	Paul D. Allison
Type	Predictive regression model of migration behavior from stated intentions	Discrete-time hazard model of migration timing
Seminal source	Carling, J. (2002). Migration in the Age of Involuntary Immobility: Theoretical Reflections and Cape Verdean Experiences. Journal of Ethnic and Migration Studies, 28(1), 5-42.	Allison, P. D. (1982). Discrete-Time Methods for the Analysis of Event Histories. Sociological Methodology, 13, 61-98.
Aliases	Migration Intention Modeling, Stated-Intention Migration Prediction, Intention-Behavior Gap Analysis, Migration Plan Predictive Modeling	Person-Period Logit Migration Model, Allison Discrete-Time Event-History Model, Annual-Data Hazard of Moving, Complementary Log-Log Migration Model
Related	3	3
Summary	Intention-to-migrate prediction models stated plans to migrate as a forecast of actual migration behavior, taking seriously that what people say they will do is informative but imperfect. Migration surveys routinely ask whether respondents intend or plan to move, and these stated intentions are among the strongest available predictors of who later migrates; yet the link is far from one-to-one, because intentions are frustrated by constraints and some moves happen without prior plans. Jorgen Carling's 2002 work on involuntary immobility highlighted exactly this slippage between wanting or planning to migrate and being able to, and Hein de Haas's 2021 aspirations-capabilities framework formalized why intentions translate into behavior only when capability is present. The method estimates the probability of intending to migrate from individual and contextual covariates, relates intention to subsequent observed moves, and explicitly measures the intention-behavior gap. It then calibrates and validates its predictions against later migration, and refines them by conditioning on capability. The aim is honest, validated prediction rather than treating stated intention as destiny.	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.