Compare methods

	Migration Flow Estimation from Stocks	Place-to-Place Migration Model
Field	Migration Studies	Migration Studies
Family	Process / pipeline	Regression model
Year of origin	2013	1966
Originator	Guy J. Abel; Guy J. Abel & Joel E. Cohen	Ira S. Lowry; (gravity antecedent: George K. Zipf)
Type	Demographic-accounting pipeline for deriving migration flows from stocks	Econometric origin-destination flow model
Seminal source	Abel, G. J. (2013). Estimating Global Migration Flow Tables Using Place of Birth Data. Demographic Research, 28, 505-546.	Lowry, I. S. (1966). Migration and Metropolitan Growth: Two Analytical Models. Chandler Publishing, San Francisco. ISBN: 9780810200135
Aliases	Stock-to-Flow Migration Estimation, Demographic Accounting of Migrant Stocks, Flow-from-Stock Method, Abel Stock-Differencing Method	Origin-Destination Migration Model, Lowry Migration Model, Econometric Gross-Flow Model, Modified Gravity Migration Model
Related	3	3
Summary	Migration flow estimation from stocks reconstructs the unobserved movement of people between countries from something that is observed: how many foreign-born residents each country holds, broken down by country of birth, at two points in time. Most countries report migrant stocks — the number of people living abroad by where they were born — far more reliably than they report flows, the year-by-year counts of who moved where. Guy Abel's 2013 method, refined in the Abel and Cohen 2019 release covering 200 countries, treats the change in these bilateral stock tables between two censuses as the net result of migration plus births and deaths, and solves for the smallest set of origin-to-destination flows that could have produced the observed change. The approach rests on demographic accounting: a stock at the end of a period equals the stock at the start, plus births into the group, minus deaths, plus arrivals, minus departures. By fixing the demographic margins and minimizing flows, it turns a fragmentary stock record into a complete, comparable flow table. This has become the standard way to build globally consistent five-year migration flow estimates where direct flow data simply do not exist.	The place-to-place migration model explains and predicts the gross number of people moving from each origin region to each destination region as a function of conditions at both ends and the distance between them. It descends from the gravity analogy popularized by George Zipf in 1946, in which movement between two cities rises with the product of their populations and falls with the distance separating them, but it adds behavioral economic content. Ira Lowry's 1966 formulation is the canonical example: he modeled interregional migration as driven by relative labor-market conditions — wages, unemployment, and the size of the labor force at origin and destination — modified by distance, and estimated the relationship econometrically from observed flows. Cast in log-linear or, in modern practice, Poisson form, the model recovers interpretable elasticities showing how flows respond to a wage gap or an unemployment differential, and it can reproduce or forecast the entire origin-destination matrix. It bridges the descriptive gravity tradition and explicit regression-based migration econometrics, and remains a workhorse for analyzing why people move where they do.