Compara mètodes

	Migration Flow Estimation from Stocks	Bilateral Migration Flow Imputation
Camp	Migration Studies	Migration Studies
Família	Process / pipeline	Process / pipeline
Any d'origen	2013	2019
Autor original	Guy J. Abel; Guy J. Abel & Joel E. Cohen	Guy J. Abel & Joel E. Cohen; Guy J. Abel
Tipus	Demographic-accounting pipeline for deriving migration flows from stocks	Imputation pipeline for completing origin-destination migration matrices
Font seminal	Abel, G. J. (2013). Estimating Global Migration Flow Tables Using Place of Birth Data. Demographic Research, 28, 505-546.	Abel, G. J., & Cohen, J. E. (2019). Bilateral international migration flow estimates for 200 countries. Scientific Data, 6, 82.
Àlies	Stock-to-Flow Migration Estimation, Demographic Accounting of Migrant Stocks, Flow-from-Stock Method, Abel Stock-Differencing Method	Origin-Destination Flow Imputation, Country-Pair Migration Matrix Completion, Harmonized Bilateral Flow Estimation, Migration Matrix Imputation
Relacionats	3	3
Resum	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.	Bilateral migration flow imputation fills in the complete origin-destination matrix of how many people moved between every pair of countries when the directly reported data cover only a fraction of those pairs and are defined inconsistently from one reporter to the next. The reporting problem is severe: some countries count migrants by intended duration of stay, others by change of registration, others not at all, and a flow reported by the sending country rarely matches the same flow reported by the receiving country. Abel and Cohen's 2019 work, building on Abel's 2013 stock-based estimation, treats this as a matrix-completion problem: harmonize whatever fragments exist, derive consistent row and column totals — often from migrant-stock change — and then fill the empty and unreliable cells so the finished matrix matches those totals. The cells are filled with iterative proportional fitting and a pseudo-Bayesian estimator that blends sparse counts toward a structured prior, and the resulting flows can be refined into sex- and age-specific tables. The output is a single, internally consistent, fully populated bilateral flow table for all country pairs.