| relatedness_density {EconGeo} | R Documentation |
Compute the relatedness density between regions and industries from regions - industries matrices and industries - industries matrices
Description
This function computes the relatedness density between regions and industries from regions - industries (incidence) matrices and industries - industries (adjacency) matrices
Usage
relatedness_density(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 matrix representing the relatedness density between regions and industries. The values in the matrix indicate the share of industries related to each industry in each region, scaled from 0 to 100. Rows represent regions and columns represent industries.
Author(s)
Pierre-Alexandre Balland p.balland@uu.nl
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
Boschma, R., Heimeriks, G. and Balland, P.A. (2014) Scientific Knowledge Dynamics and Relatedness in Bio-Tech Cities, Research Policy 43 (1): 107-114
See Also
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(mat, relatedness)