shiftd: Dynamic shift-share analysis
In REAT: Regional Economic Analysis Toolbox

Description Usage Arguments Details Value Author(s) References See Also Examples

Analyzing regional growth with the dynamic shift-share analysis

shiftd(e_ij1, e_ij2, e_i1, e_i2, time1, time2, 
industry.names = NULL, shift.method = "Dunn", 
gerfin.shifts = "mean", print.results = TRUE, 
plot.results = FALSE, plot.colours = NULL, plot.title = NULL, 
plot.portfolio = FALSE, ...)

`e_ij1`	a numeric vector with i values containing the employment in i industries in region j at time 1
`e_ij2`	a numeric data frame or matrix with i rows containing the employment in i industries in region j and t columns, representing t (t > 1) years
`e_i1`	a numeric vector with i values containing the total employment in i industries at time 1
`e_i2`	a numeric data frame or matrix with i rows containing the total employment in i industries and t columns, representing t (t > 1) years
`time1`	Initial year
`time2`	Final year
`industry.names`	Industry names (e.g. from the relevant statistical classification of economic activities)
`shift.method`	Method of shift-share-analysis to be used ("Dunn", "Gerfin") (default: `shift.method = "Dunn"`)
`gerfin.shifts`	If `shift.method = "Gerfin"`: Logical argument that indicates if the shifts are calculated as sums or as means (default: `gerfin = "mean"`)
`print.results`	Logical argument that indicates if the function shows the results or not
`plot.results`	Logical argument that indicates if the results have to be plotted
`plot.colours`	If `plot.results = TRUE`: Plot colours
`plot.title`	If `plot.results = TRUE`: Plot title
`plot.portfolio`	Logical argument that indicates if the results have to be plotted in a portfolio matrix additionally
`...`	Additional arguments for the portfolio plot (see the function `portfolio`)

The shift-share analysis (Dunn 1960) adresses the regional growth (or decline) regarding the over-all development in the national economy. The aim of this analysis model is to identify which parts of the regional economic development can be traced back to national trends, effects of the regional industry structure and (positive) regional factors. The growth (or decline) of regional employment consists of three factors: l_{t+1}-l_t = nps + nds + nts, where l is the employment in the region at time t and t+1, respectively, and nps is the net proportionality shift, nds is the net differential shift and nts is the net total shift. Other variants are e.g. the shift-share method by Gerfin (Index method) and the dynamic shift-share analysis (Barff/Knight 1988).

As there is more than one way to calculate a Dunn-type shift-share analysis and the terms are not used consequently in the regional economic literature, this function and the documentation use the formulae and terms given in Farhauer/Kroell (2013). If shift.method = "Dunn", this function calculates the net proportionality shift (nps), the net differential shift (nds) and the net total shift (nts) where the last one represents the residuum of (positive) regional factors.

This function calculates a dynamic shift-share analysis for at least two years.

A list containing the following objects:

`components`	A `matrix` containing the shift-share components related to the chosen method
`components.year`	A `matrix` containing the shift-share components for each year
`growth`	A `matrix` containing the industry-specific growth values
`method`	The chosen method, e.g. "Dunn"

Thomas Wieland

Arcelus, F. J. (1984): “An Extension of Shift-Share Analysis”. In: In: Growth and Change, 15, 1, p. 3-8.

Barff, R. A./Knight, P. L. (1988): “Dynamic Shift-Share Analysis”. In: Growth and Change, 19, 2, p. 1-10.

Casler, S. D. (1989): “A Theoretical Context for Shift and Share Analysis”. In: Regional Studies, 23, 1, p. 43-48.

Dunn, E. S. Jr. (1960): “A statistical and analytical technique for regional analysis”. In: Papers and Proceedings of the Regional Science Association, 6, p. 97-112.

Esteban-Marquillas, J. M. (1972): “Shift- and share analysis revisited”. In: Regional and Urban Economics, 2, 3, p. 249-261.

Farhauer, O./Kroell, A. (2013): “Standorttheorien: Regional- und Stadtoekonomik in Theorie und Praxis”. Wiesbaden : Springer.

Gerfin, H. (1964): “Gesamtwirtschaftliches Wachstum und regionale Entwicklung”. In: Kyklos, 17, 4, p. 565-593.

Schoenebeck, C. (1996): “Wirtschaftsstruktur und Regionalentwicklung: Theoretische und empirische Befunde fuer die Bundesrepublik Deutschland”. Dortmunder Beitraege zur Raumplanung, 75. Dortmund.

portfolio, shift, shifti, shift.growth

# Example from Farhauer/Kroell (2013), extended:
region_A_t <- c(90,20,10,60)
region_A_t1 <- c(100,40,10,55)
region_A_t2 <- c(105,45,15,60)
# data for region A (time t and t+1)
nation_X_t <- c(400,150,150,400)
nation_X_t1 <- c(440,210,135,480)
nation_X_t2 <- c(460,230,155,500)
# data for the national economy (time t and t+1)
shiftd(region_A_t, data.frame(region_A_t1, region_A_t2), nation_X_t, 
data.frame(nation_X_t1, nation_X_t2), time1 = 2000, time2 = 2002,
plot.results = TRUE, plot.portfolio = TRUE, psize = region_A_t1)

data(Goettingen)
shiftd(Goettingen$Goettingen2008[2:16], Goettingen[2:16,3:11], 
Goettingen$BRD2008[2:16], Goettingen[2:16,13:21],
time1 = 2008, time2 = 2017, industry.names = Goettingen$WA_WZ2008[2:16], 
shift.method = "Dunn")

Dynamic Shift-Share Analysis 
Method: Dunn 

Shift-share components 
                Components
Growth (t1-t)   45.0000000
National share  39.9644269
Industrial mix   0.1636996
Regional share   4.8718735
Net total shift  5.0355731

Calculation for 4 industries 
Regional employment at time t: 180, at time t+1: 225 (45 / 0.25 %)
National employment at time t: 1100, at time t+1: 1345 (245 / 0.2227273 %)


Dynamic Shift-Share Analysis 
Method: Dunn 

Shift-share components 
                Components
Growth (t1-t)    8927.0000
National share   7967.7771
Industrial mix   1891.1368
Regional share   -931.9140
Net total shift   959.2229

Calculation for 15 industries 
Regional employment at time t: 56872, at time t+1: 65799 (8927 / 0.1569665 %)
National employment at time t: 27695398, at time t+1: 31443318 (3747920 / 0.1353265 %)