relatedness_density_ext_avg {EconGeo}

Compute the average relatedness density of regions to industries that are not part of the regional portfolio from regions - industries matrices and industries - industries matrices

Description

This function computes the average relatedness density of regions to industries that are not part of the regional portfolio from regions - industries (incidence) matrices and industries - industries (adjacency) matrices. This is the technological flexibility indicator proposed by Balland et al. (2015).

Usage

relatedness_density_ext_avg(mat, relatedness)

Arguments

mat

An incidence matrix with regions in rows and industries in columns

relatedness

An adjacency industry - industry matrix indicating the degree of relatedness between industries

Value

A vector representing the average relatedness density of regions to industries that are not part of the regional portfolio. The values in the vector indicate the average relatedness density for each region, rounded to the nearest integer.

Author(s)

Pierre-Alexandre Balland [e-mail]

References

Boschma, R., Balland, P.A. and Kogler, D. (2015) Relatedness and Technological Change in Cities: The rise and fall of technological knowledge in U.S. metropolitan areas from 1981 to 2010, Industrial and Corporate Change 24 (1): 223-250

Balland P.A., Rigby, D., and Boschma, R. (2015) The Technological Resilience of U.S. Cities, Cambridge Journal of Regions, Economy and Society, 8 (2): 167-184

See Also

relatedness, relatedness_density, relatedness_density_ext, relatedness_density_int, relatedness_density_int_avg, relatedness_density_ext_avg

Examples

## generate a region - industry matrix in which cells represent the presence/absence
## of a RCA
set.seed(31)
mat <- matrix(sample(0:1, 20, replace = TRUE), ncol = 4)
rownames(mat) <- c("R1", "R2", "R3", "R4", "R5")
colnames(mat) <- c("I1", "I2", "I3", "I4")

## generate an industry - industry matrix in which cells indicate if two industries are
## related (1) or not (0)
relatedness <- matrix(sample(0:1, 16, replace = TRUE), ncol = 4)
relatedness[lower.tri(relatedness, diag = TRUE)] <- t(relatedness)[lower.tri(t(relatedness),
  diag = TRUE
)]
rownames(relatedness) <- c("I1", "I2", "I3", "I4")
colnames(relatedness) <- c("I1", "I2", "I3", "I4")

## run the function
relatedness_density_ext_avg(mat, relatedness)