Electoral Disproportionality

Electoral Disproportionality: Rae (1971), Loosemore and Hanby (1971), Lijphart (1986), Lijphart (1994), Gallagher (1991) and Cox and Shugart (1991).

dispro(tidy_data, method, scale = 1)

Arguments

tidy_data	data.frame that contains the following variables with these names: election: year of election. unit: the unit of analysis (province, department ...) party: name of the political parties that obtain votes. votes: votes obtained by each party. seats: . If the data is not structured in this way you can order it with: convert_esaps.
method	Method to calculate electoral volatility: method = "Rae" or method = 1. method = "Loosemore and Hanby" or method = 2. method = "Lijphart_1" or method = 3. method = "Lijphart_2" or method = 4. method = "Gallagher" or method = 5. method = "Cox and Shugart" or method = 6.
scale	By default it is 100, the indices will vary between 0 and 100. If scale = 1 the variation will be between 0 and 1.

Value

data.frame.

Author

Nicolas Schmidt nschmidt@cienciassociales.edu.uy

Examples

votes <- data.frame(election = rep(c(2000, 2005), each = 4),
                   unit  = rep(c("ARG", "URY"), each = 4),
                   party = c("party_A", "party_B","party_C","party_D"),
                   votes = c(20, 30, 40, 10, 30, 35, 25, 10),
                   seats = c(25, 20, 40, 15, 35, 30, 30, 5)
                   )

dispro(votes, 1:6, 1)
#>   election unit  Rae  LH Lijphart_1 Lijphart_2 Gallagher Cox_Shugart
#> 1     2000  ARG 0.05 0.1       0.10       0.06      0.32        1.00
#> 2     2005  URY 0.05 0.1       0.05       0.06      0.32        0.73
dispro(votes, 3)
#>   election unit Lijphart_1
#> 1     2000  ARG       0.10
#> 2     2005  URY       0.05
dispro(tidy_data = votes, method = 3:5)
#>   election unit Lijphart_1 Lijphart_2 Gallagher
#> 1     2000  ARG       0.10       0.06      0.32
#> 2     2005  URY       0.05       0.06      0.32
dispro(tidy_data = votes, method = c(1,3,6))
#>   election unit  Rae Lijphart_1 Cox_Shugart
#> 1     2000  ARG 0.05       0.10        1.00
#> 2     2005  URY 0.05       0.05        0.73
dispro(tidy_data = votes, method = c("Rae", "Gallagher"))
#>   election unit  Rae Gallagher
#> 1     2000  ARG 0.05      0.32
#> 2     2005  URY 0.05      0.32