# location.quotient: Compute location quotients from regions - industries matrices In PABalland/EconGeo: Computing Key Indicators of the Spatial Distribution of Economic Activities

## Description

This function computes location quotients from (incidence) regions - industries matrices. The numerator is the share of a given industry in a given region. The denominator is the share of a this industry in a larger economy (overall country for instance). This index is also refered to as the index of Revealed Comparative Advantage (RCA) following Ballasa (1965), or the Hoover-Balassa index.

## Usage

 `1` ```location.quotient(mat, binary = FALSE) ```

## Arguments

 `mat` An incidence matrix with regions in rows and industries in columns `binary` Logical; shall the returned output be a dichotomized version (0/1) of the location quotient? Defaults to FALSE (the full values of the location quotient will be returned), but can be set to TRUE (location quotient values above 1 will be set to 1 & location quotient values below 1 will be set to 0)

## Author(s)

Pierre-Alexandre Balland p.balland@uu.nl

## References

Balassa, B. (1965) Trade Liberalization and Revealed Comparative Advantage, The Manchester School 33: 99-123.

`RCA`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```## generate a region - industry matrix mat = matrix ( c (100, 0, 0, 0, 0, 0, 15, 5, 70, 10, 0, 20, 10, 20, 50, 0, 25, 30, 5, 40, 0, 40, 55, 5, 0), ncol = 5, byrow = T) rownames(mat) <- c ("R1", "R2", "R3", "R4", "R5") colnames(mat) <- c ("I1", "I2", "I3", "I4", "I5") ## run the function location.quotient (mat) location.quotient (mat, binary = TRUE) ```