Description Usage Arguments Details Value Author(s) References See Also Examples
Calculating the excess colocation (XCL) index by Howard, Newman and Tarp for a given number of industries
1 | howard.xcl2(k, industry, region, print.results = TRUE)
|
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 |
print.results |
logical argument that indicates whether the calculated values are printed or not |
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. This function takes a while even for a relatively small number of industries!
A matrix with I rows (one for each industry-industry combination) containing the XCL values
Thomas Wieland
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.
howard.cl
, howard.xcl2
, ellison.c
, ellison.c2
1 2 3 4 5 6 7 8 9 | ## Not run:
# example data from Farhauer/Kroell (2014):
data (FK2014_EGC)
howard.xcl2 (FK2014_EGC$firm, FK2014_EGC$industry,
FK2014_EGC$region)
# this may take a while!
## End(Not run)
|
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