| unionDensity | R Documentation |
Cross-national data on relative size of the trade unions and predictors, in 20 countries. Two of the predictors are highly collinear, and are the source of a debate between Stephens and Wallerstein (1991), later reviewed by Western and Jackman (1994).
data(unionDensity)
unionnumeric, percentage of the total number of wage
and salary earners plus the unemployed who are union members,
measured between 1975 and 1980, with most of the data drawn from 1979
leftnumeric, an index tapping the extent to which
parties of the left have controlled governments since 1919, due to
Wilensky (1981).
sizenumeric, log of labor force size, defined as the
number of wage and salary earners, plus the unemployed
concennumeric, percentage of employment, shipments, or
production accounted for by the four largest enterprises in a
particular industry, averaged over industries (with weights
proportional to the size of the industry) and the resulting measure
is normalized such that the United States scores a 1.0, and is due
to Pryor (1973). Some of the scores on this variable are imputed
using procedures described in Stephens and Wallerstein (1991, 945).
Pryor, Frederic. 1973. Property and Industrial Organization in Communist and Capitalist Countries. Bloomington: Indiana University Press.
Stephens, John and Michael Wallerstein. 1991. Industrial Concentration, Country Size and Trade Union Membership. American Political Science Review 85:941-953.
Western, Bruce and Simon Jackman. 1994. Bayesian Inference for Comparative Research. American Political Science Review 88:412-423.
Wilensky, Harold L. 1981. Leftism, Catholicism, Democratic Corporatism: The Role of Political Parties in Recemt Welfare State Development. In The Development of Welfare States in Europe and America, ed. Peter Flora and Arnold J. Heidenheimer. New Brunswick: Transaction Books.
Jackman, Simon. 2009. Bayesian Analysis for the Social Sciences. Wiley: Hoboken, New Jersey.
data(unionDensity)
summary(unionDensity)
pairs(unionDensity,
labels=c("Union\nDensity",
"Left\nGovernment",
"log Size of\nLabor Force",
"Economic\nConcentration"),
lower.panel=function(x,y,digits=2){
r <- cor(x,y)
par(usr=c(0,1,0,1))
text(.5,.5,
format(c(r,0.123456789),digits=digits)[1],
cex=1.5)
}
)
ols <- lm(union ~ left + size + concen,
data=unionDensity)
summary(ols)