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Abstract
In this paper, the author estimates a multinomial logit model to analyse the contextual determinants of internal migration in Sri Lanka. The study uses micro-level data from the Consumer Finance and Socio-Economic Survey 2003/2004 of the Central Bank of Sri Lanka, and finds that higher probability for internal migration is correlated with rural areas; districts with larger concentration of labour in agriculture; districts with a larger share of population with ownership of assets; and districts with a larger share of population in 19–34 years. Districts with large labour forces and districts with a more unequal income distribution are correlated with a lower probability for internal migration. Policy recommendations of the findings include, repositioning of the balance in policy focus from receiving areas of internal migrants towards sending areas of internal migration by developing the rural infrastructure to efficiently receive remittances, improve investment of these remittances in agriculture technology to ensure agriculture productivity and focus on demographic composition of those left behind. Rural areas with larger labour forces as well as areas with greater income inequality are ideal candidates to be developed in metro cities as noted by the development policy framework Department of National Planning.
Acknowledgements
The author thanks David Jaeger, Wim Vijverberg, Partha Deb and an unknown referee for valuable comments.
Notes
1. This low percentage is partially attributable to the definition adopted in classifying urban and rural areas.
2. However, literature on internal migration resulting as a result of the ethnic conflict is abundant. The determinants of these conflict-related migration flows are different from development-related ones.
3. The self-selection into internal migration and the observational nature of the data-set used, does not warrant to explore any causal relationship between contextual variables and internal migration.
4. Nonetheless, the richness in data on non-migrants compensates for the absence of a human capital variable for migrants. This will be discussed subsequently.
5. A binary logit model consisting of only internal migrants and stayers was also considered. However, such an outcome variable was not pursued further because it overlooks the remaining option – international migration, and hence fails to depict the true scenario of labour mobility in Sri Lanka.
6. (1) Mason/carpenter/plumber; (2) Driver; (3) Domestic aide; (4) Labourer; (5) Teacher; (6) Technician; (7) Nurse; (8) Doctor; (9) Engineer; (10) Accountant; (11) Administrative & clerical service; (12) Business; (13) Hotel services; (14) Armed forces police service; and (15) Other.
7. Rural sector includes the estate sector.
8. A Gini coefficient of 0 indicates perfect equality and 1 indicates complete inequality.
9. A one-unit increase corresponds to the increase of the labour force by 1000.