Russett data

The Russett data set (Russett, 1964) are studied in Gifi (1990). Three blocks of variables have been defined for 47 countries. The first block X1 = [GINI, FARM, RENT] is related to "Agricultural Inequality". The second block X2 = [GNPR, LABO] describes "Industrial Development". The third one X3 = [INST, ECKS, DEAT] measures "Political Instability". An additional variable DEMO describes the political regime: stable democracy, unstable democracy or dictatorship. Russett collected this data to study relationships between Agricultural Inequality, Industrial Development and Political Instability. Russett's hypotheses can be formulated as follows: It is difficult for a country to escape dictatorship when its agricultural inequality is above-average and its industrial development below-average.

data(Russett)

Format

A data frame with 47 observations on the following 11 numeric variables.

gini

Inequality of land distribution

farm

% farmers that own half of the land

rent

% farmers that rent all their land

gnpr

Gross national product per capita ($1955)

labo

% of labor force employed in agriculture

inst

Instability of executive (45-61)

ecks

Number of violent internal war incidents (46-61)

death

Number of people killed as a result of civic group violence (50-62)

demostab

binary variable equal to 1 for stable democraty and 0 otherwise

demoinst

binary variable equal to 1 for unstable democraty and 0 otherwise

dictator

binary variable equal to 1 for dictatorship and 0 otherwise

References

Russett B.M. (1964), Inequality and Instability: The Relation of Land Tenure to Politics, World Politics 16:3, 442-454.

Gifi, A. (1990), Nonlinear multivariate analysis, Chichester: Wiley.

Examples

#Loading of the Russett dataset
data(Russett)
#Russett is partitioned into three blocks (X_agric, X_ind, X_polit)
X_agric =as.matrix(Russett[,c("gini","farm","rent")])
X_ind = as.matrix(Russett[,c("gnpr","labo")])
X_polit = as.matrix(Russett[ , c("inst", "ecks", "death", "demostab", 
                                 "demoinst", "dictator")])
A = list(X_agric, X_ind, X_polit)
lapply(A, dim)
#> [[1]]
#> [1] 47  3
#> 
#> [[2]]
#> [1] 47  2
#> 
#> [[3]]
#> [1] 47  6
#>