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Mapping the Policy Preferences of Romanian Political Parties
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39
As it can be seen, the first factor contains mainly issues that could be
categorized as "cultural", although, some of them (like welcome for foreign capital,
income redistribution among counties etc) have a very powerful component. The
second factor is composed by economic issues: privatization, combating inflation or
unemployment, income taxation, contributions to the health insurance public system.
The only issue that is marginal in this respect is the fighting the rural-urban
differences, but even here it may be quite probable that experts had in mind the
economic backward of rural areas compared with the urban zones. This result seems
to confirm our initial hypothesis that the most important body of issues remains the
cultural ones, although individually, they received lower scores on saliency for party
competition.
We go now to the second method of data reduction, the cluster analysis. We
have used, in this case, the hierarchical cluster analysis, with between-group linkage
and squared Euclidean distance in order to group our variables. Below, table 23
presents the agglomeration schedule of clusters and the dendrogram the combination
of the variables.
Table 23: Agglomeration Schedule
8
9
4,805
0
0
8
3
5
7,465
0
0
5
11
12
9,077
0
0
4
4
11
26,513
0
3
7
2
3
40,206
0
2
8
6
7
45,923
0
0
10
4
13
46,189
4
0
9
2
8
48,464
5
1
11
1
4
78,622
0
7
12
6
10
81,318
6
0
11
2
6
134,404
8
10
12
1
2
376,279
9
11
0
Stage
1
23
45
678
910
1112
Cluster 1 Cluster 2
Cluster Combined
Coefficients Cluster 1 Cluster 2
Stage Cluster First
Appears
Next Stage
The computer identified two clusters (although the first one is not entirely
consistent), suggesting, again, that political space of party competition is bi-
dimensional. However, the components of the clusters are different than in the case of
factor analysis, mainly because of different methods of combination. What makes us
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39
As it can be seen, the first factor contains mainly issues that could be
categorized as "cultural", although, some of them (like welcome for foreign capital,
income redistribution among counties etc) have a very powerful component. The
second factor is composed by economic issues: privatization, combating inflation or
unemployment, income taxation, contributions to the health insurance public system.
The only issue that is marginal in this respect is the fighting the rural-urban
differences, but even here it may be quite probable that experts had in mind the
economic backward of rural areas compared with the urban zones. This result seems
to confirm our initial hypothesis that the most important body of issues remains the
cultural ones, although individually, they received lower scores on saliency for party
competition.
We go now to the second method of data reduction, the cluster analysis. We
have used, in this case, the hierarchical cluster analysis, with between-group linkage
and squared Euclidean distance in order to group our variables. Below, table 23
presents the agglomeration schedule of clusters and the dendrogram the combination
of the variables.
Table 23: Agglomeration Schedule
8
9
4,805
0
0
8
3
5
7,465
0
0
5
11
12
9,077
0
0
4
4
11
26,513
0
3
7
2
3
40,206
0
2
8
6
7
45,923
0
0
10
4
13
46,189
4
0
9
2
8
48,464
5
1
11
1
4
78,622
0
7
12
6
10
81,318
6
0
11
2
6
134,404
8
10
12
1
2
376,279
9
11
0
Stage
1
2
3
4
5
6
7
8
9
10
11
12
Cluster 1 Cluster 2
Cluster Combined
Coefficients Cluster 1 Cluster 2
Stage Cluster First
Appears
Next Stage
The computer identified two clusters (although the first one is not entirely
consistent), suggesting, again, that political space of party competition is bi-
dimensional. However, the components of the clusters are different than in the case of
factor analysis, mainly because of different methods of combination. What makes us
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