| norm_ubiquity {EconGeo} | R Documentation |
Compute a measure of complexity by normalizing ubiquity of industries
Description
This function computes a measure of complexity by normalizing ubiquity of industries. We divide the share of the total count (employment, number of firms, number of patents, ...) in an industry by its share of ubiquity. Ubiquity is given by the number of regions in which an industry can be found (location quotient > 1) from regions - industries (incidence) matrices
Usage
norm_ubiquity(mat)
Arguments
mat |
An incidence matrix with regions in rows and industries in columns |
Value
A numeric vector representing the measure of complexity obtained by normalizing the ubiquity of industries. Each value in the vector corresponds to the normalized complexity score of an industry.
Author(s)
Pierre-Alexandre Balland p.balland@uu.nl
References
Balland, P.A. and Rigby, D. (2017) The Geography of Complex Knowledge, Economic Geography 93 (1): 1-23.
See Also
diversity, location_quotient, ubiquity, tci, mort
Examples
## generate a region - industry matrix with full count
set.seed(31)
mat <- matrix(sample(0:10, 20, replace = TRUE), ncol = 4)
rownames(mat) <- c("R1", "R2", "R3", "R4", "R5")
colnames(mat) <- c("I1", "I2", "I3", "I4")
## run the function
norm_ubiquity(mat)