REAT (version 3.0.2)

ellison.a: Ellison-Glaeser Agglomeration Index

Description

Calculating the Agglomeration Index by Ellison and Glaeser for a single industry \(i\)

Usage

ellison.a(e_ik, e_j, regions, print.results = TRUE)

Arguments

e_ik

a numeric vector containing the no. of employees of firm \(k\) from industry \(i\)

e_j

a numeric vector containing the no. of employees in the regions \(j\)

regions

a vector containing the IDs/names of the regions \(j\)

print.results

logical argument that indicates whether the function prints the results or not (only for internal use)

Value

A matrix with five columns (\(\gamma_i\), \(G_i\), \(z_{G_i}\), \(K_i\) and \(HHI_i\)).

Details

The Ellison-Glaeser Agglomeration Index is not standardized. A value of \(\gamma_i = 0\) indicates a spatial distribution of firms equal to a dartboard approach. Values below zero indicate spatial dispersion, values greater than zero indicate clustering.

References

Ellison G./Glaeser, E. (1997): “Geographic concentration in u.s. manufacturing industries: A dartboard approach”. In: Journal of Political Economy, 105, 5, p. 889-927.

Farhauer, O./Kroell, A. (2014): “Standorttheorien: Regional- und Stadtoekonomik in Theorie und Praxis”. Wiesbaden : Springer.

Nakamura R./Morrison Paul, C. (2009): “Measuring agglomeration”. In: Capello, R./Nijkamp, P. (eds): Handbook of Regional Growth and Development Theories, p. 305-328.

See Also

gini.conc, gini.spec, locq, locq2, howard.cl, howard.xcl, howard.xcl2, litzenberger, litzenberger2

Examples

# NOT RUN {
# Example from Farhauer/Kroell (2014):
j <- c("Wien", "Wien", "Wien", "Wien", "Wien", "Linz", 
"Linz", "Linz", "Linz", "Graz")
E_ik <- c(200,650,12000,100,50,16000,13000,1500,1500,25000)
E_j <- c(500000,400000,100000)
ellison.a(E_ik, E_j, j)
# 0.05990628
# }