Description Usage Arguments Details Value Author(s) References See Also Examples
Analyzing industry-specific regional growth with the dynamic shift-share analysis
1 2 3 4 5 |
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: |
gerfin.shifts |
If |
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.title |
If |
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 |
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 |
components.year |
A |
growth |
A |
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # 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)
shiftid(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
1 2 3 4 5 6
Growth (t1-t) -3.000000 29.00000 -1117.0000 -255.0000 -51.0000 524.0000
National share 6.103502 -9.46377 254.5217 160.0638 561.7436 368.2053
Regional share -9.103502 38.46377 -1371.5217 -415.0638 -612.7436 155.7947
Net total shift -9.103502 38.46377 -1371.5217 -415.0638 -612.7436 155.7947
7 8 9 10 11 12
Growth (t1-t) 470.00000 274.00000 -465.000000 2229.000 1178.0000 268.0000
National share 515.03493 286.32383 6.356612 1821.392 977.9869 167.9118
Regional share -45.03493 -12.32383 -471.356612 407.608 200.0131 100.0882
Net total shift -45.03493 -12.32383 -471.356612 407.608 200.0131 100.0882
13 14 15
Growth (t1-t) 1272.0000 4211.000 363.00000
National share 1138.5383 3556.692 47.50353
Regional share 133.4617 654.308 315.49647
Net total shift 133.4617 654.308 315.49647
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 %)
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