# NOT RUN {
# 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)
# }
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