RGCCA (version 2.0)

Russett: Russett data

Description

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": GINI = Inequality of land distribution, FARM = % farmers that own half of the land (> 50), RENT = % farmers that rent all their land. The second block X2 = [GNPR, LABO] describes "Industrial Development": GNPR = Gross national product per capita ($1955), LABO = % of labor force employed in agriculture. The third one X3 = [INST, ECKS, DEAT] measures "Political Instability": INST = Instability of executive (45-61), ECKS = Number of violent internal war incidents (46-61), DEAT = Number of people killed as a result of civic group violence (50-62). 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.

Usage

data(Russett)

Format

A data frame with 47 observations on the following 12 variables.

PAYS

a character vector

gini

a numeric vector

farm

a numeric vector

rent

a numeric vector

gnpr

a numeric vector

labo

a numeric vector

inst

a numeric vector

ecks

a numeric vector

death

a numeric vector

demostab

a numeric vector

demoinst

a numeric vector

dictatur

a numeric vector

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", "dictatur")])
A = list(X_agric, X_ind, X_polit)