Yöntem Karşılaştırma

	Multiplicity Sampling of Migrant Stock	Migrant Stock Estimation
Alan	Migration Studies	Migration Studies
Aile	Process / pipeline	Process / pipeline
Köken yılı	1970	1983
Köken	Monroe G. Sirken	United Nations Population Division (standard measurement conventions)
Tür	Network-based survey design and weighting estimator for rare populations	Cross-source pipeline for counting the resident migrant population
Seminal kaynak	Sirken, M. G. (1970). Household Surveys with Multiplicity. Journal of the American Statistical Association, 65(329), 257-266.	United Nations (1983). Manual on Methods of Estimating Internal Migration (Manual VI). Population Studies No. 47. New York: United Nations.
Diğer adlar	Network Sampling of Migrants, Multiplicity Survey of Emigrants, Sirken Multiplicity Estimator, Relative-Report Migrant Sampling	Foreign-Born Stock Estimation, International Migrant Stock, Migrant Population Counting, Stock-Based Migration Measurement
İlişkili	3	3
Özet	Multiplicity sampling, introduced by Monroe Sirken in 1970, is a survey design for counting rare and hard-to-reach populations by letting respondents report not only about themselves but about eligible relatives living elsewhere. For migration research the appeal is direct: emigrants and dispersed migrants are, by definition, absent from the sampling frame of the place that wants to count them, so an ordinary household survey misses them. Under multiplicity sampling a sampled household reports its migrant relatives — say, children or siblings who have moved abroad — according to an explicit counting rule, which dramatically raises the effective coverage of the rare group because many households can each contribute reports. The price of this expanded reach is that the same migrant may be reportable by several households, so each reported migrant must be weighted by the inverse of the number of households eligible to report them, the migrant's 'multiplicity.' Sirken showed that this multiplicity-weighted estimator is unbiased and that, by enlarging the set of reporters, it can sharply reduce the sampling variance for rare populations compared with conventional surveys.	Migrant stock estimation answers a deceptively basic question: how many migrants are living in a place at a given moment? Unlike migration flows, which count moves over an interval, a stock is a cross-sectional count of people whose origin differs from their place of residence — most commonly the foreign-born, but sometimes the foreign-national or those who have lived abroad. The United Nations measurement conventions, set out in its migration manuals, fix the core definitions (place of birth versus citizenship, duration thresholds, usual residence) and the at-risk concepts that make stocks comparable. In practice the analyst rarely has one clean source: censuses give place-of-birth tables but miss recent or irregular arrivals, population registers give continuous citizenship-based counts but vary in how they handle departures, and surveys give detail but suffer sampling error. Migrant stock estimation is therefore a pipeline that compiles these sources, harmonizes their differing definitions and geographies, and adjusts for undercount, overstay, and double counting, drawing on the same comparability concerns Bell and colleagues raised for internal migration. The output — a coherent count of migrants by origin, age, and sex — underpins integration policy, flow estimation, and the denominators of countless migration indicators.