ellison.a: Ellison-Glaeser Agglomeration Index

In REAT: Regional Economic Analysis Toolbox

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)

Details

The Ellison-Glaeser Agglomeration Index is not standardized. A value of γ_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.

Value

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

Author(s)

Thomas Wieland

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

# 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

Example output

[1] 0.05990628

REAT documentation built on Sept. 5, 2021, 5:18 p.m.