howard.xcl: Howard-Newman-Tarp excess colocation (XCL) index

In REAT: Regional Economic Analysis Toolbox

Description

Calculating the excess colocation (XCL) index by Howard, Newman and Tarp for two industries

Usage

howard.xcl(k, industry, region, industry1, industry2, no.samples = 50, e_k = NULL)

Arguments

k	a vector containing the IDs/names of firms k
industry	a vector containing the IDs/names of the industries i
region	a vector containing the IDs/names of the regions j
industry1	Regarded industry 1 (out of the industry vector)
industry2	Regarded industry 2 (out of the industry vector)
no.samples	Number of samples for the counterfactual firm allocation via bootstrapping
e_k	Employment of firm k

Details

The Howard-Newman-Tarp excess colocation index (XCL) is standardized (-1 ≤ CL ≤ 1). The rationale behind is that the CL index (see howard.cl) is compared to a counterfactual (random) location pattern which is constructed via bootstrapping. Processing time depends on the number of firms and the number of samples.

Value

A single value of XCL

Author(s)

Thomas Wieland

References

Howard, E./Newman, C./Tarp, F. (2016): “Measuring industry coagglomeration and identifying the driving forces”. In: Journal of Economic Geography, 16, 5, p. 1055-1078.

See Also

howard.cl, howard.xcl2, ellison.c, ellison.c2

Examples

# example from Howard et al. (2016):
firms <- 1:6
industries <- c("A", "B", "A", "B", "A", "B")
locations <- c("X", "X", "X", "Y", "Y", "X")

howard.xcl(firms, industries, locations, industry1 = "A", 
industry2 = "B")

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