Internal Migration and Education Toward Consistent Data Collection Practices for Comparative Research AUDE BERNARD & MARTIN BELL QUEENSLAND CENTRE FOR POPULATION RESEARCH UNIVERSITY OF QUEENSLAND, AUSTRALIA
Background Significance of internal migration 763 million people worldwide (4 times the # of international migrants) 10-14 times moves over the lifetime Young adults are the most mobile Linked to key life-course transitions, including education Integral to human development Main driver of population change Key features Most volatile component of population change Difficult to measure no international standards Theoretically challenging
New Zealand South Korea USA Australia Fiji Canada Panama Chile Switzerland Senegal France Cameroon Paraguay Israel Japan Mongolia Barbados Bolivia Kyrgyzstan Peru Uruguay Guinea South Africa Morocco Malta Uganda Cambodia Rwanda Greece Brazil Argentina Malaysia Costa Rica Tunisia Ghana Guatemala Dominican Portugal China Vietnam Indonesia El Salvador Mauritius Cuba Honduras Thailand St Lucia Nicaragua Ecuador Haiti Philippines Spain Iraq Nepal Venezuela Mali North Korea Mexico Egypt India % changed address in the last five years Variations in levels of internal migration 60 50 40 30 20 10 0 Bell et al. (2015), IMAGE project https://imageproject.com.au/
Spatial patterns of movement CHINA THAILAND Charles-Edwards et al. (2016)
Education as a reason for moving education employment family Marriage other Level of education-related migration varies significantly between countries Accounts for a small proportion of all moves Few countries collect reasons for moving at their census Sample size from surveys often too small to disaggregate by age Iraq India Cambodia Mexico Egypt Iran Indonesia Colombia Thailand China 1 9 4 33 10 11 13 16 15 8 16 17 21 31 52 14 50 42 40 58 45 29 49 42 32 21 32 6 42 7 25 8 6 11 15 28 3 19 33 2 3 22 18 12 8 12 8 0% 20% 40% 60% 80% 100% Reasons for long-distance migration (15-24 years) Bernard et al. (forthcoming)
Migration Index (no education=1) Educational selectivity of migrants 5 Primary education Secondary education Tertiary education Probability of moving increases sharply with education Holds across all world regions Educational gradient less pronounced in Latin America 4 3 2 1 1.7 2.8 3.7 0 Africa (n=20) Asia (n=17) Europe and North America (n=13) Latin America (n=18) World (n=68) Bernard et al. (forthcoming)
Educational selectivity of migrants Significant variations between countries The impact of tertiary education is what strongly differentiate countries Reasons for this are poorly understood Malaysia Thailand Indonesia China Iran Kyrgyzstan Vietnam Armenia Philippines Fiji Cambodia Jordan Mongolia Turkey India Iraq Nepal Asia 0 2 4 6 8 10 Migration index (no education=1) Bernard et al. (forthcoming)
Impact of migration on children s education Chronic mobility is detrimental to educational performance Need to better understand Type of moves (rural vs. urban) Duration (temporary versus permanent) Frequency of movement Impact of regulatory framework (e.g. China s Hukou system) Impact on both enrolment and performance Rural-to-urban migration & language score in primary school in Beijing Lu and Zhou (2013)
Educational composition of migration flows and their impacts Educational selectivity varies with flow types 70% urban to urban urban to rural rural to urban rural to rural The volume of particular flows affects the redistribution of human capital 60% 50% Limitation of current data sources Few countries collect urban status of previous place of residence Definition of urban areas not consistent Limited geographic detail 40% 30% 20% 10% 0% % of migrants with at least secondary education Bernard et al. (forthcoming)
Economic Returns to Internal Migration Positive effect of migration on earnings increase with education Limited understanding how it varies over time and across countries Need comparable longitudinal datasets or retrospective residential histories Need high spatial and temporal resolution Urban status at both origin and destination
Internal migration data collection practices Most countries collect some form of migration data 179/183 countries since 1995 Different collection instruments Census (88 %) Population register or administrative source (28%) National surveys (61 %) e.g. Demographic and Health Surveys (90 countries since 1980) 6 in 10 countries draw data from multiple sources Bell et al. (2014) IMAGE Repository
Measuring internal migration Different forms of data Transition Event Duration Time interval (2000 UN Census round) 1 year interval (20%) 5 year interval (37%) Undefined (23%) Lifetime (86%) Spatial framework All changes of address # of zones Characteristics of migrants Sex Age Education Bell et al. (2014) IMAGE Repository
Strength of each data source Census - Enumeration of full the population - High spatial resolution - Long historical time series - Large range of covariates, including education - Individual-level migration data for 60 countries available in IPUMS Survey - Can collect detailed migration histories - Can collect reasons for moving - Large range of covariates, including education - Information on place of origin - Representative of whole population or tailored to particular groups (youths, refugees,..) - Ability to modify questions - Detailed temporal coverage (longitudinal data collected annually or retrospective life histories)
Limitations of each data source Census - Covariates measured at the end observation of period - Do not pick up return or multiple moves - Coarse temporal coverage (most censuses are decennial) - Cross-sectional data - Limited information on place of origin - Some countries do not disseminate data Survey - Spatial detail often coarse - Variability in format limits comparability of migration - Ongoing national surveys rare in developing countries - Longitudinal data collected over many years - Small sample size limits disaggregation by age or region - Sampling error - Recall error - Panel attrition
Utility of each data source Migrant selectivity Census - Large range of covariates, including education but measured at the end of observation period Survey - Large range of covariates, including education - Analysis of causal relationships Spatial analysis & redistribution of human capital Trend analysis Cross-national comparisons - High spatial resolution - Enumeration of the full population permits spatial disaggregation - Limited information on place origin - Historical trends but infrequent observations and data is cross-sectional - Individual-level migration data for 60 countries available in IPUMS - Limited spatial resolution - Sample size restricts spatial disaggregation - Information on place of origin - Recent trends with annual observations - Variability in format limits comparability of migration
Recommendations for cross-national comparisons Migration data should be collected in a comparable format Internal migration best measured as an event or over a fixed interval (ideally 1 or 5 years) Changes of address should be collected Place of residence, past and present, should be coded to the smallest geographical units feasible Usual residence should be defined using a threshold criterion of 6 months. Longitudinal surveys long-term investment & problem of attrition Retrospective residential histories Cost-effective and immediate results (collected in one wave as part of on-going survey) Collect full residential histories (All domestic and international moves since birth, address, date, reasons for moving) Collect histories in other life domains (education, employment, family) Increasingly common Europe (SHARE, ELSA ), China (CHARLS ) and US (HRS ) Comparable questionnaires Life-history grids improve recall
Annotated reference list Bell, M, Blake, M, Boyle, P, Duke-Williams, O, Rees, P, Stillwell, J & Hugo, G 2002, 'Cross-national comparison of internal migration: issues and measures', Journal of the Royal Statistical Society: Series A (Statistics in Society), vol. 165, no. 3, pp. 435-64. This paper reviews key issues in comparing internal migration between countries and proposes a set of summary measures for the cross-national comparison of migration Bell, M, Charles-Edwards, E, Kupiszewska, D, Kupiszewski, M, Stillwell, J & Zhu, Y 2015, 'Internal Migration Data Around the World: Assessing Contemporary Practice', Population, Space and Place, vol. 21, no. 1, pp. 1-17. This paper reviews contemporary migration data collection practices around the world and provides a set of recommendations to enhance the utility and comparability of internal migration data. Bell, M, Charles-Edwards, E, Kupiszewska, D, Kupiszewski, M, Stillwell, J & Zhu, Y 2015, 'Internal migration and development: comparing migration intensities around the world', Population and Development Review, vol. 41, no. 1, pp. 33-58. This paper proposes a robust method to compare levels of internal migration between countries and assembles a league table of 96 countries. Bernard A., Bell, M, & Cooper J. (Forthcoming) Internal migration and education: A cross-national comparison Background paper prepared for the 2018 Global Education Monitoring Report, UNESCO, Paris This paper examines the links between education and internal migration in 58 countries from around the world. Bernard, A 2017, 'Cohort Measures of Internal Migration: Understanding Long-Term Trends', Demography, vol. 54, no. 6, pp. 2201-21. This paper proposes a set of cohort measures of internal migration to can be applied to retrospective survey data to analyses migration trends and patterns between successive cohorts and countries. It demonstrates the utility of a cohort approach by applying the proposed measures to retrospective residential histories collected in England. Bernard, A 2017, 'Levels and patterns of internal migration in Europe: A cohort perspective', Population Studies, vol. 71, no. 3, pp. 293-311. This paper uses retrospective survey data from 14 European countries to explore cross-national variations in the level and patterns of internal migration. It reveals the demographic mechanism underpinning enduring regional variations in migration level. Lu, Yao, and Hao Zhou. "Academic achievement and loneliness of migrant children in China: School segregation and segmented assimilation." Comparative education review 57.1 (2012): 85-116. This paper compares the academic achievement of children from migrant and non-migrant families by type of school in Beijing. Vidal, Sergi, and Janeen Baxter. For the sake of the children? A longitudinal analysis of residential relocations and academic performance of Australian children. Life-Course Centre Working Paper Series No. 2016-14, Brisbane, Australia This paper assesses the effect of residential relocation on the academic performance of children in Australian and found a very limited impact.