Global Perspective on Internal Migration

22.12.17
Written by Richard Hokenson 

In many parts of the world, migration has replaced fertility and mortality as the leading agent of demographic change. The movement of populations is increasingly the primary process shaping patterns of residence within and between countries. While there has been considerable attention devoted to movements between countries (international migration), comprehensive analysis of population movements involving changes of residence within countries (internal migration) had been largely absent until a recent paper by Bell et al. (2017).

Two principal types of internal migration data can be identified: events and transitions. Event data, usually associated with population registers, are the most common form of internal migration data available in many European countries. Transition data, which measures migration by comparing place of residence at two points in time, is the form of data most commonly derived from censuses. The authors adopt a measure of the Aggregate Crude Migration Rate (ACMI) computed as:

ACMI = 100 M / P

Where M is the total number of internal migrants (transition/last move data) or migrations (event data) in a given time period and is expressed as a percent of P, which is the national population. Charts 1, 2 and 3 display the five-year migration results through 2010 for 61 countries.

Migration intensities varied from highs exceeding 50% in New Zealand and South Korea to lows of less than 6% in Egypt and India. Mapping the results reveals distinctive patterns between and within regions. As noted in the article,

North America and Australasia emerged as giant poles of high mobility while low migration intensities were common across most of Asia with the exceptions of Japan and South Korea. Europe and Latin America displayed more variation but with clear spatial gradients: from high mobility in Northern and Western Europe falling steadily to the south and east and from a spine of high mobility in the Andes declining rapidly to the east and north of the continent into Central America. Evidence for Africa was fragmented but suggested nodes of high mobility in the east, west and south of the continent.

The authors then attempt to account for the differences in migration intensity. Part of the variation could be a function of age-composition effects, but that was rejected as age standardization had little effect on the international rankings. Using a number of economic, social and demographic variables, they found moderate to strong correlations with the level of urbanization and per capita income. Mobile phone subscriptions also showed a strong association with migration. Most notable was the finding that migration intensities appear to be reduced by later departures from the parental home. There is also a close link with international migration: net international migration gains appear to increase internal mobility while net losses substitute for internal movements. This latter development may occur because the inflow of remittances reduces the need for migration.

Investment Conclusion

Birth rates for many countries are low and falling. In conjunction with growing resistance to international migration, the growth outlook for countries will increasingly be determined within borders. The results above will be invaluable in providing insights into what is feasible. Although the United States ranks very high in the international rankings, we (Hokenson & Company) also know that mobility has been declining for quite a few years. Mobility or the lack thereof is a very important issue in assessing the state of the labor market, e.g. are there enough workers where the work is? We will soon be publishing on that topic.

References
Bell, Martin, Elin Charles-Edwards, Philipp Ueffing, John Stillwell, Marek Kupiszewiski and Dorota Kupiszewska, 2017. “Internal Migration and Development: Comparing Migration Intensities Around the World”, Population and Development Review 41(1): 33-58.

 
 

This update was researched and written by Richard Hokenson. Data is as of 22 December 2017

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