TCI: Compute an index of knowledge complexity of industries using...

In PABalland/EconGeo: Computing Key Indicators of the Spatial Distribution of Economic Activities

Compute an index of knowledge complexity of industries using the eigenvector method

Description

This function computes an index of knowledge complexity of industries using the eigenvector method from regions - industries (incidence) matrices. Technically, the function returns the eigenvector associated with the second largest eigenvalue of the projected industry - industry matrix.

Usage

TCI(mat, RCA = FALSE)

Arguments

mat	An incidence matrix with regions in rows and industries in columns
RCA	Logical; should the index of relative comparative advantage (RCA - also refered to as location quotient) first be computed? Defaults to FALSE (a binary matrix - 0/1 - is expected as an input), but can be set to TRUE if the index of relative comparative advantage first needs to be computed

Author(s)

Pierre-Alexandre Balland [e-mail]

References

Hidalgo, C. and Hausmann, R. (2009) The building blocks of economic complexity, Proceedings of the National Academy of Sciences 106: 10570 - 10575.

Balland, P.A. and Rigby, D. (2017) The Geography of Complex Knowledge, Economic Geography 93 (1): 1-23.

See Also

location.quotient, ubiquity, diversity, MORc, KCI, MORt

Examples

## generate a region - industry matrix with full count
set.seed(31)
mat <- matrix(sample(0:10,20,replace=T), ncol = 4)
rownames(mat) <- c ("R1", "R2", "R3", "R4", "R5")
colnames(mat) <- c ("I1", "I2", "I3", "I4")

## run the function
TCI (mat, RCA = TRUE)

## 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=T), ncol = 4)
rownames(mat) <- c ("R1", "R2", "R3", "R4", "R5")
colnames(mat) <- c ("I1", "I2", "I3", "I4")

## run the function
TCI (mat)

## generate the simple network of Hidalgo and Hausmann (2009) presented p.11 (Fig. S4)
countries <- c("C1", "C1", "C1", "C1", "C2", "C3", "C3", "C4")
products <- c("P1","P2", "P3", "P4", "P2", "P3", "P4", "P4")
data <- data.frame(countries, products)
data$freq <- 1
mat <- get.matrix (data)

## run the function
TCI (mat)

PABalland/EconGeo documentation built on Jan. 5, 2023, 8:40 a.m.