REAT (version 3.0.3)

ellison.c: Ellison-Glaeser Coagglomeration Index

Description

Calculating the Coagglomeration Index by Ellison and Glaeser for one set of $U$ industries

Usage

ellison.c(e_ik, industry, region, e_j = NULL, c.industries = NULL)

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 $j$

e_j

a numeric vector containing the total employment of the regions $j$

c.industries

optional: a vector containing the regarded $U$ industries (where $U\le I$)

Value

A single value of ${\gamma }_c$

Details

The Ellison-Glaeser Coagglomeration Index is not standardized. A value of ${\gamma }_c=0$ 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

ellison.a, ellison.a2, ellison.c2, gini.conc, gini.spec, locq, locq2, howard.cl, howard.xcl, howard.xcl2, litzenberger, litzenberger2

Examples

# NOT RUN {
# Example from Farhauer/Kroell (2014):
data(FK2014_EGC)

ellison.c(FK2014_EGC$emp_firm, FK2014_EGC$industry, 
FK2014_EGC$region, FK2014_EGC$emp_region)
# }