Literature DB >> 29276429

Prospects for the Comparative Study of International Migration using quasi-longitudinal micro-data.

Mao-Mei Liu1, Mathew J Creighton2, Fernando Riosmena3, Pau Baizán Mun Oz4.   

Abstract

BACKGROUND: Longitudinal micro-level data about international migration behavior are notoriously difficult to collect, but data collection efforts have become more frequent in recent years. Comparative research of the patterns and processes of international migration, however, remains quite rare, especially that which compares across regions.
OBJECTIVE: We highlight the promises and difficulties of comparative international migration research, by offering a detailed comparison of two prominent data collection efforts.
METHODS: We systematically review existing sources of longitudinal and quasi-longitudinal individual-level and household-level data of international migration. We then compare two widely-used data sources: the Mexican Migration Project (MMP) and the Migration between Africa and Europe project (MAFE).
RESULTS: Data collection efforts are increasingly diverse, yet public accessibility of data remains limited. Also, comparability of data collected across settings can be complicated. In our MMP-MAFE analysis, we show some ways in which comparability can be achieved.
CONCLUSIONS: A primary roadblock to international comparative research is that, with some exceptions, the public accessibility of data remains low. Even when data is public and surveys are modeled after one another, comparability is not easy due to necessary trade-offs in adapting surveys to local settings and to developments in the field. CONTRIBUTION: We demonstrate that, despite great strides in collecting quasi-longitudinal data of international migration, data accessibility still hinders the study of migration. With regards to comparability, our article provides important lessons for future data collection and analysis efforts that could improve comparability and thus advance understanding of the complex dynamics of international migration.

Entities:  

Year:  2016        PMID: 29276429      PMCID: PMC5739584          DOI: 10.4054/DemRes.2016.35.26

Source DB:  PubMed          Journal:  Demogr Res


  35 in total

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Journal:  Demography       Date:  1999-08

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Authors:  Sara R Curran; Estela Rivero-Fuentes
Journal:  Demography       Date:  2003-05

3.  The indirect estimation of migration: a critical review.

Authors:  B Zaba
Journal:  Int Migr Rev       Date:  1987

4.  Birds of passage no more: migration decision making among Filipino immigrants in Hawaii.

Authors:  F Arnold
Journal:  Int Migr       Date:  1987-03

5.  The limits to cumulative causation: international migration from Mexican urban areas.

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Journal:  Demography       Date:  2004-02

6.  The healthy migrant effect: new findings from the Mexican Family Life Survey.

Authors:  Luis N Rubalcava; Graciela M Teruel; Duncan Thomas; Noreen Goldman
Journal:  Am J Public Health       Date:  2007-11-29       Impact factor: 9.308

7.  Do conditional cash transfers influence migration? A study using experimental data from the Mexican PROGRESA program.

Authors:  Guy Stecklov; Paul Winters; Marco Stampini; Benjamin Davis
Journal:  Demography       Date:  2005-11

8.  Cumulative causation, market transition, and emigration from China.

Authors:  Zai Liang; Miao David Chunyu; Guotu Zhuang; Wenzhen Ye
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9.  The Geography of Undocumented Mexican Migration.

Authors:  Douglas S Massey; Jacob S Rugh; Karen A Pren
Journal:  Mex Stud       Date:  2010

10.  Undocumented Migration from Latin America in an Era of Rising U.S. Enforcement.

Authors:  Douglas S Massey; Fernando Riosmena
Journal:  Ann Am Acad Pol Soc Sci       Date:  2010-07-01
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  2 in total

1.  The Ethnosurvey Revisited: New Migrations, New Methodologies?

Authors:  Pawel Kaczmarczyk; Douglas S Massey
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2.  Health and well-being of male international migrants and non-migrants in Bangladesh: A cross-sectional follow-up study.

Authors:  Randall Kuhn; Tania Barham; Abdur Razzaque; Patrick Turner
Journal:  PLoS Med       Date:  2020-03-31       Impact factor: 11.069

  2 in total

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