# TCI: Compute an index of knowledge complexity of industries using... In PABalland/EconGeo: Computing Key Indicators of the Spatial Distribution of Economic Activities

## 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

 `1` ```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 p.balland@uu.nl

## 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.

`location.quotient`, `ubiquity`, `diversity`, `MORc`, `KCI`, `MORt`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27``` ```## 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) ```