index_impact: Summary indices of migration impact
In migest: Methods for the Indirect Estimation of Bilateral Migration

index_impact

R Documentation

Summary indices of migration impact

Description

Summary indices of migration impact

Usage

index_impact(
  m,
  p,
  pop_col = "pop",
  reg_col = "region",
  orig_col = "orig",
  dest_col = "dest",
  flow_col = "flow",
  long = TRUE
)

Arguments

`m`	A `matrix` or data frame of origin-destination flows. For `matrix` the first and second dimensions correspond to origin and destination respectively. For a data frame ensure the correct column names are passed to `orig_col`, `dest_col` and `flow_col`.
`p`	A data frame or named vector for the total population. When data frame, column of populations labelled using `pop_col` and region names labelled `reg_col`.
`pop_col`	Character string of the population column name
`reg_col`	Character string of the region column name. Must match dimension names or values in origin and destination columns of `m`.
`orig_col`	Character string of the origin column name (when `m` is a data frame rather than a `matrix`)
`dest_col`	Character string of the destination column name (when `m` is a data frame rather than a `matrix`)
`flow_col`	Character string of the flow column name (when `m` is a data frame rather than a `matrix`)
`long`	Logical to return a long data frame with index values all in one column

Value

A tibble with 4 summary measures where

`effectivness`	Migration effectiveness index (MEI) from Shryock et al. (1975). Values range between 0 and 100. High values indicate migration is an efficient mechanism of population redistribution, generating a large net migration. Conversely, low values denote that migration is closely balanced, leading to comparatively little redistribution.
`anmr`	Aggregate net migration rate from Bell et. al. (2002). The population weighted version of `mei`.
`perference`	Index of preference, given in UN DESA (1983). From Bachi (1957) and Shryock et al. (1975) - measures size of migration compared to expected flows based on unifrom migration. Can go from 0 to infinity
`velocity`	Index of velocity, given in UN DESA (1983). From Bogue, Shryock, Jr. & Hoermann (1957) - measures size of migration compared to expected flows based on population size alone. Can go from 0 to infinity

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

Shryock, H. S., & Siegel, J. S. (1976). The Methods and Materials of Demography. (E. G. Stockwell (ed.); Condensed). Academic Press.

United Nations Department of Economic and Social Affairs Population Division. (1970). Methods of measuring internal migration. United Nations Department of Economic and Social Affairs Population Division - 1970 - Methods of measuring internal migration https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/files/documents/2020/Jan/manual_vi_methods_of_measuring_internal_migration.pdf

Examples

# single year
library(dplyr)
m <- korea_gravity %>%
  filter(year == 2020,
         orig != dest) %>%
  select(orig, dest, flow)
m
p <- korea_gravity %>%
  filter(year == 2020) %>%
  distinct(dest, dest_pop)
p
index_impact(m = m, p = p, pop_col = "dest_pop", reg_col = "dest")

# multiple years
library(tidyr)
library(purrr) 

korea_gravity %>%
  select(year, orig, dest, flow, dest_pop) %>%
  group_nest(year) %>%
  mutate(m = map(.x = data, .f = ~select(.x, orig, dest, flow)),
         p = map(.x = data, .f = ~distinct(.x, dest, dest_pop)),
         i = map2(.x = m, .y = p,
                  .f = ~index_impact(
                    m = .x, p = .y, pop_col = "dest_pop", reg_col = "dest", long = FALSE
                  ))) %>%
  select(-data, -m, -p) %>%
  unnest(i)

migest documentation built on Nov. 18, 2023, 9:06 a.m.