shift {REAT}

Shift-share analysis

Description

Analyzing regional growth with the shift-share analysis

Usage

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

Arguments

e_ij1

a numeric vector with i values containing the employment in i industries in region j at time 1

e_ij2

a numeric vector with i values containing the employment in i industries in region j at time 2

e_i1

a numeric vector with i values containing the total employment in i industries at time 1

e_i2

a numeric vector with i values containing the total employment in i industries at time 2

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", "Esteban", "Gerfin") (default: shift.method = "Dunn")

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)

Details

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), the dynamic shift-share analysis (Barff/Knight 1988) or the extension by Esteban-Marquillas (1972).

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 shift-share analysis for two years.

Value

A list containing the following objects:

components

A matrix containing the shift-share components related to the chosen method

growth

A matrix containing the industry-specific growth values

method

The chosen method, e.g. "Dunn"

Author(s)

Thomas Wieland

References

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.

See Also

portfolio, shiftd, shifti, , shift.growth

Examples

# Example from Farhauer/Kroell (2013):
region_A_t <- c(90,20,10,60)
region_A_t1 <- c(100,40,10,55)
# 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)
# data for the national economy (time t and t+1)
resultsA <- shift(region_A_t, region_A_t1, nation_X_t, nation_X_t1)
# results for region A
region_B_t <- c(60,30,30,40)
region_B_t1 <- c(85,55,40,35)
# data for region B (time t and t+1)
resultsB <- shift(region_B_t, region_B_t1, nation_X_t, nation_X_t1)
# results for region B
region_C_t <- c(250,100,110,300)
region_C_t1 <- c(255,115,85,390)
# data for region C (time t and t+1)
resultsC <- shift(region_C_t, region_C_t1, nation_X_t, nation_X_t1)
# results for region C

# Example Freiburg dataset
data(Freiburg)
# Loads the data
shift(Freiburg$e_Freiburg2008, Freiburg$e_Freiburg2014, Freiburg$e_Germany2008, 
Freiburg$e_Germany2014)
# results for Freiburg and Germany (2008 vs. 2014)