Internal migration around the world: comparing distance travelled and its frictional effect

Abstract

This paper examines how internal migration distance and its frictional effect vary between countries. Such comparisons are hampered by differences in the number and configuration MAUP W use the flexible aggregation routines embedded in the IMAGE Studio, a bespoke software platform which incorporates a spatial interaction model, to elucidate these scale and pattern effects in a set of countries for which finely grained origin-destination matrices are available.We identify an exponential relationship between mean migration distance and mean area size but show that the frictional effect of distance remains remarkably stable across spatial scale, except where zones have small populations and are poorly connected. This stability allows robust comparisons between countries even though zonal systems differ. We find that mean migration distances vary widely, being highest in large, low density countries and positively associated with urbanisation, HDI and GDP per capita. This suggests a positive link between development and migration distance, paralleling that between development and migration intensity. We find less variation in the beta parameter that measures distance friction but identify clear spatial divisions between more developed countries, with lower friction in larger, less dense countries undergoing rapid population growth. IntroductionMigration can be defined as changing residence from one geographical location to another.Whether this involves a permanent or a temporary relocation, travel occurs over a specific distance. As with many other forms of spatial interaction, migration conforms with the axiom following from ' proposition in the nineteenth century that (Ravenstein, 1885, p. 198). Implicit in this statement is that fewer migrants travel longer distances and that distance therefore exerts a frictional effect on migration behaviour. 3Bell et al. (2002) identified distance, along with intensity, connectivity and impact as the dimensions of internal migration that are important to consider when making crossnational comparisons. M residence, measured in the form of a rate or probability, whilst connectivity refers to the extent to which regions are linked by migration flows and can be measured using a simple index such as the proportion of the total flows between regions that are non-zero. Migration impact, on the other hand, indicates the extent to which migration transforms the pattern of population settlement and can be measured using a number of indicators such as migration effectiveness or aggregate net migration. Elsewhere we have examined the data available for making such comparisons (Bell et al., 2014b), developed software to compute comparative indicators and address key methodological issues (Stillwell et al., 2014), and assessed how countries differ with respect to overall migration intensities (Bell et al., 2015). In this paper, we turn to the distance dimension in order to examine how far people move and the frictional effect of distance on internal migration in countries around th...

Spatial Aggregation Methods for Investigating the MAUP Effects in Migration Analysis

“…Moreover, the configuration of ASRs appears to have a relatively low effect on the decay parameter until around 50 ASRs, when the range of values from alternative zonations gets wider. The stability of the beta parameter across scales has been reported for other countries in Stillwell et al (2016).…”

“…Further research is required using countries where data are available on migration at different spatial scales to compare published rates with estimated means derived using the IMAGE Studio from configurations based on lower level spatial units. Whilst the results of the IMAGE project have reported the use of the Studio for comparative analysis of internal migration in different countries around the world (Bell et al 2015b;Rees et al 2016;Stillwell et al 2016) where zone systems are very different, there is also the potential in using the Studio to explore how scale and zonation effects might vary by demographic (age, sex, ethnicity) or socio-economic (occupation, tenure, health status) group in any single country (see Stillwell et al 2018, for an initial study of variations by age group in the UK). A further avenue of investigation might be to explore the relationship between migration indicators and explanatory variables at different spatial scales using correlation analysis of the type that was employed to investigate the MAUP effects in earlier studies of stock variables.…”

Explaining geographic patterns of small group internal migration

“…Nevertheless, there are few studies that have focused on quantifying the deterrence effect; see, for example, Makower, Marschak, and Robinson (1938); Schwartz (1973);and Yang, Cai, Qi, Liu, and Deng (2015) in a British, American, and Chinese context, respectively. Stillwell et al (2016) suggest that this is because of the absence of suitable datasets that provide origin and destination location with sufficient accuracy (see also Niedomysl, Ernstson, & Fransson, 2015). Stillwell and colleagues' major study compares the frictional impact of distance on internal migration patterns across a large number of countries.…”

Spatial demography: A unifying core and agenda for further research

“…Spatial interaction models may be applied to any flow process that involves two or more locations, however, for the purposes of this paper, we focus on the migration process. As part of one of the most ambitious studies of internal migration ever taken, Stillwell et al () fitted spatial interaction models to a series of migration flow tables representing 105 countries to study the effect of distance while controlling for modifiable area unit problem. In another ambitious study, Cohen, Roig, Reuman, and GoGwilt () fitted a gravity model, specified as a generalised linear model, to estimate flows of international migration amongst all countries in the world.…”