Estimation of bilateral migrant flows from bilateral migrant stocks using stock differencing approaches

Estimates migrant transitions flows between two sequential migrant stock tables using differencing approaches commonly used by economists.

ffs_diff(m1, m2, decrease = "return", include_native_born = FALSE)

Arguments

m1

Matrix of migrant stock totals at time t. Rows in the matrix correspond to place of birth and columns to place of residence at time t

m2

Matrix of migrant stock totals at time t+1. Rows in the matrix correspond to place of birth and columns to place of residence at time t+1.

decrease

How to treat decreases in bilateral stocks over the t to t+1 period (so as to avoid a negative bilateral flow estimates). See details for possible options. Default is return

include_native_born

Logical value to indicate whether to include diagonal elements of m1 and m2. Default of FALSE - not include.

Value

Estimates migrant transitions flows between two sequential migrant stock tables.

When decrease = "zero" all decreases in migrant stocks over there period are set to zero, following the approach of Bertoli and Fernandez-Huertas Moraga (2015)

When decrease = "return" all decreases in migrant stocks are assumed to correspond to return flows back to their place of birth, following the approach of Beine and Parsons (2015)

References

Beine, Michel, Simone Bertoli, and Jesús Fernández-Huertas Moraga. (2016). A Practitioners’ Guide to Gravity Models of International Migration. The World Economy 39(4):496–512.

See also

ffs_demo, ffs_rates

Author

Guy J. Abel

Examples

s1 <- matrix(data = c(100, 10, 10, 0, 20, 55, 25, 10, 10, 40, 140, 65, 20, 25, 20, 200),
             nrow = 4, ncol = 4, byrow = TRUE)
s2 <- matrix(data = c(75, 25, 5, 15, 20, 45, 30, 15, 30, 40, 150, 35, 10, 50, 5, 200),
             nrow = 4, ncol = 4, byrow = TRUE)
r <- LETTERS[1:4]
dimnames(s1) <- dimnames(s2) <- list(pob = r, por = r)
s1; s2
#>    por
#> pob   A  B   C   D
#>   A 100 10  10   0
#>   B  20 55  25  10
#>   C  10 40 140  65
#>   D  20 25  20 200
#>    por
#> pob  A  B   C   D
#>   A 75 25   5  15
#>   B 20 45  30  15
#>   C 30 40 150  35
#>   D 10 50   5 200

ffs_diff(m1 = s1, m2 = s2, decrease = "zero")
#>     dest
#> orig  A  B C  D
#>    A  0 15 0 15
#>    B  0  0 5  5
#>    C 20  0 0  0
#>    D  0 25 0  0
ffs_diff(m1 = s1, m2 = s2, decrease = "return")
#>     dest
#> orig  A  B  C  D
#>    A  0 15  0 25
#>    B  0  0  5  5
#>    C 25  0  0 15
#>    D  0 25 30  0