ellison.a2: Ellison-Glaeser Agglomeration Index

In REAT: Regional Economic Analysis Toolbox

Description

Calculating the Agglomeration Index by Ellison and Glaeser for a given number of I industries

Usage

ellison.a2(e_ik, industry, region, print.results = TRUE)

Arguments

e_ik	a numeric vector containing the no. of employees of firm k from industry i
industry	a vector containing the IDs/names of the industries i
region	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) and I rows (one for each industry).

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

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

Examples

# Example data from Farhauer/Kroell (2014):
data(FK2014_EGC)

ellison.a2 (FK2014_EGC$emp_firm, FK2014_EGC$industry, 
FK2014_EGC$region)

Example output

Ellison-Glaeser Agglomeration Index 
K = 42 firms, I = 4 industries, J = 3 regions 

                    Gamma i
Clothing trade  -0.09379384
Forestry         0.16838003
Textiles dyeing -0.08012539
Textiles trade  -0.13040134

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