Summary indices of migration connectivity
Usage
index_connectivity(
m = NULL,
gini_orig_all = FALSE,
gini_dest_all = FALSE,
gini_corrected = TRUE,
orig_col = "orig",
dest_col = "dest",
flow_col = "flow",
long = TRUE
)
Source
Bell, M., Blake, M., Boyle, P., Duke-Williams, O., Rees, P. H., Stillwell, J., & Hugo, G. J. (2002). Cross-national comparison of internal migration: issues and measures. Journal of the Royal Statistical Society: Series A (Statistics in Society), 165(3), 435–464. https://doi.org/10.1111/1467-985X.00247
Rogers, A., & Raymer, J. (1998). The Spatial Focus of US Interstate Migration Flows. International Journal of Population Geography, 4(1), 63–80. https://doi.org/10.1002/(SICI)1099-1220(199803)4%3A1<63%3A%3AAID-IJPG87>3.0.CO%3B2-U
Rogers, A., & Sweeney, S. (1998). Measuring the Spatial Focus of Migration Patterns. Professional Geographer, 50(2), 232–242.
Plane, D., & Mulligan, G. F. (1997). Measuring spatial focusing in a migration system. Demography, 34(2), 251–262.
Arguments
- m
A
matrix
or data frame of origin-destination flows. Formatrix
the first and second dimensions correspond to origin and destination respectively. For a data frame ensure the correct column names are passed toorig_col
,dest_col
andflow_col
.- gini_orig_all
Logical to include gini index values for all origin regions. Default
FALSE
.- gini_dest_all
Logical to include gini index values for all destination regions. Default
FALSE
.- gini_corrected
Logical to use corrected denominator in Gini index of Bell (2002) or original of David A. Plane and Mulligan (1997)
- orig_col
Character string of the origin column name (when
m
is a data frame rather than amatrix
)- dest_col
Character string of the destination column name (when
m
is a data frame rather than amatrix
)- flow_col
Character string of the flow column name (when
m
is a data frame rather than amatrix
)- long
Logical to return a long data frame with index values all in one column
Value
A tibble with 12 summary measures:
- connectivity
Migration connectivity index of Bell et. al. (2002) for the share of non-zero flows. A value of 0 means no connections (all zero flows) and 1 shows that all regions are connected by migrants.
- inequality_equal
Migration inequality index of Bell et. al. (2002) based on a distributions of flows compared to equal distributions of expected flows . A value of 0 shows complete equality in flows and 1 shows maximum inequality.
- inequality_sim
Migration inequality index of Bell et. al. (2002) based on a distributions of flows compared to distributions of expected flows from a Poisson regression independence fit
flow ~ orig + dest
. A value of 0 shows complete equality in flows and 1 shows maximum inequality.- gini_total
Overall concentration of migration from Bell (2002), corrected from Plane and Mulligan (1997). A value of 0 means no spatial focusing and 1 shows that all migrants are found in one single flow. Calculated using
migration.indices::migration.gini.total()
- gini_orig_standardized
Relative extent to which the origin selections of out-migrations are spatially focused. A value of 0 means no spatial focusing and 1 shows maximum focusing. Adapted from
migration.indices::migration.gini.row.standardized()
.- gini_dest_standardized
Relative extent to which the destination selections of in-migrations are spatially focused. A value of 0 means no spatial focusing and 1 shows maximum focusing. Adapted from
migration.indices::migration.gini.col.standardized()
.- mwg_orig
Origin spatial focusing, from Bell et. al. (2002). Calculated using
migration.indices::migration.weighted.gini.out()
- mwg_dest
Destination spatial focusing, from Bell et. al. (2002). Calculated using
migration.indices::migration.weighted.gini.in()
- mwg_mean
Mean spatial focusing, from Bell et. al. (2002). Average of the origin and destination migration weighted Gini indices (
mwg_orig
andmwg_dest
). A value of 0 means no spatial focusing and 1 shows that all migrants are found in one region. Calculated usingmigration.indices::migration.weighted.gini.mean()
- cv
Coefficient of variation from Rogers and Raymer (1998).
- acv
Aggregated system-wide coefficient of variation from Rogers and Sweeney (1998), using
migration.indices::migration.acv()
Examples
library(dplyr)
korea_gravity %>%
filter(year == 2020) %>%
select(orig, dest, flow) %>%
index_connectivity()
#> # A tibble: 11 × 2
#> measure value
#> <chr> <dbl>
#> 1 connectivity 1
#> 2 inequality_equal 0.541
#> 3 inequality_sim 0.281
#> 4 gini_total 0.709
#> 5 gini_orig_standardized 0.0493
#> 6 gini_dest_standardized 0.0517
#> 7 mwg_orig 0.0370
#> 8 mwg_dest 0.0389
#> 9 mwg_mean 0.0379
#> 10 cv 17.9
#> 11 acv 3.43