CoChat
Sign Up
Cited by 129Migration and Labor DynamicsMigration, Refugees, and IntegrationMigration, Health, Geopolitics, Historical Geography

Bilateral international migration flow estimates for 200 countries

Open access
Abel, Guy J., Cohen, Joel E.·2019·Scientific Data
DOI 10.1038/s41597-019-0089-3PMC PMC6572777
Open this paper in CoChat — free accountOpen PDF

Abstract

Data on stocks and flows of international migration are necessary to understand migrant patterns and trends and to monitor and evaluate migration-relevant international development agendas. Many countries do not publish data on bilateral migration flows. At least six methods have been proposed recently to estimate bilateral migration flows between all origin-destination country pairs based on migrant stock data published by the World Bank and United Nations. We apply each of these methods to the latest available stock data to provide six estimates of five-year bilateral migration flows between 1990 and 2015. To assess the resulting estimates, we correlate estimates of six migration measures from each method with equivalent reported data where possible. Such systematic efforts at validation have largely been neglected thus far. We show that the correlation between the reported data and the estimates varies widely among different migration measures, over space, and over time. We find that the two methods using a closed demographic accounting approach perform consistently better than the four other estimation approaches.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41597-019-0089-3

Cites

21 of 21 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The "demographic account minimization closed" approach provides the highest correlation with immigration rates (0.84) but a substantially lower correlation with outmigration rates (0.30).

    “As a robustness check (see online Appendix: Supplemental Materials), we also produce estimates based on the “demographic account minimization closed” approach by Abel–Cohen. The latter approach provides the highest correlation with immigration rates in their validation exercise (0.84), but a substantially lower correlation with outmigration rates (0.30).”

    From Demography: Fast and Slow (2022) · cites this paper as Abel and Cohen 2019

    The Methods section describes a closed demographic-accounting minimisation approach. Technical Validation > Overall agreement says its immigration-rate correlations are relatively high and that emigration-rate correlations are generally lower. Our copy does not give the claimed 0.84 and 0.30 values or establish that this approach has the single highest immigration-rate correlation. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • The "demographic account pseudo Bayesian closed" method provides the largest correlation coefficient with "ground truth" validation sets for outmigration rates (0.44) and the second-largest correlation coefficient for immigration rates (0.82).

    “For our main results, we select Abel–Cohen estimates based on the “demographic account pseudo Bayesian closed” method, which provides the largest correlation coefficient with “ground truth” validation sets for outmigration rates (0.44), and the second‐largest correlation coefficient for immigration rates (0.82).”

    From Demography: Fast and Slow (2022) · cites this paper as Abel and Cohen 2019

    Technical Validation > Overall agreement reports that closed demographic-accounting estimates, especially the pseudo-Bayesian method, have the highest correlations for most migration measures, and that closed methods have higher immigration-rate correlations. It does not give the claimed 0.44 and 0.82 coefficients or establish that this method ranks first for emigration rates and second for immigration rates; the reference to Fig. 4 in our copy does not supply those values. (LLM, conf=0.81)

    Experimental — accuracy not yet measured

  • At the global level, thanks to Abel and Cohen bilateral migration flow estimates combined with UN birth and death rate estimates, it is possible to estimate national-level turnover rates.

    “At the global level, thanks to new bilateral migration flow estimates provided by Abel and Cohen (2019), combined with UN birth and death rate estimates, it is possible to estimate national‐level turnover rates.”

    From Demography: Fast and Slow (2022) · cites this paper as Abel and Cohen 2019

  • Reliably estimating data on immigration and emigration flows at the country level is difficult.

    “A major challenge in estimating country‐level PTRs is related to data quality and availability: while birth and death rates are widely available over time and space, reliably estimating data on immigration and emigration flows at the country level is difficult (Abel and Cohen 2019; Abel and Sander 2014).”

    From Demography: Fast and Slow (2022) · cites this paper as Abel and Cohen 2019

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

1 of the 22 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Related

Authors
Abel, G. J., & Cohen, J. E.
Affiliations
  • Shanghai University (CN)
  • University of Chicago (US)
Corresponding author
Abel, Guy J.
ORCID
Venue
Scientific Data
Publisher
Springer Science and Business Media LLC
Published
2019-06-17
Volume
6
Issue
1
Pages
82-82
ISSN
2052-4463 (ISSN-L)
DOI
10.1038/s41597-019-0089-3
PMC
PMC6572777
OpenAlex
W2951293227
Cited by
129
References
22
Citations by year
2026: 14 · 2025: 20 · 2024: 25 · 2023: 17 · 2022: 23 · 2021: 18 · 2020: 10 · 2019: 2
Type
data paper
Language
en
Open access
Licence
Locations
  • Scientific Data (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • IIASA PURE (International Institute of Applied Systems Analysis) (acceptedVersion)
  • ePubWU Institutional Repository (Wirtschaftsuniversität Wien) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • China National Funds for Distinguished Young Scientists (41650110483)
  • National Science Foundation (DMS-1225529)
Topics
  • Social Sciences › Sociology and Political Science › Migration and Labor Dynamics
  • Social Sciences › Sociology and Political Science › Migration, Refugees, and Integration
  • Social Sciences › Demography › Migration, Health, Geopolitics, Historical Geography
Keywords
bilateral migration flows, international migration, origin-destination pairs, migration and development
MeSH terms
Data Analysis, Humans, Emigrants and Immigrants, Human Migration

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review