Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/128347
Authors: 
Gründler, Klaus
Krieger, Tommy
Year of Publication: 
2015
Series/Report no.: 
CESifo Working Paper 5647
Abstract: 
We present a novel approach for measuring democracy based on Support Vector Machines, a mathematical algorithm for pattern recognition. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-interval and enables a very detailed measurement of democracy for 188 countries between 1981 and 2011. Application of the SVMDI highlights a robust positive relationship between democracy and economic growth. We argue that the ambiguity in recent studies mainly originates from the lack of sensitivity of traditional democracy indicators. Analyzing transmission channels we conclude that democratic countries have better educated populations, higher investment shares, and lower fertility rates, but not necessarily higher levels of redistribution.
Subjects: 
democracy
economic growth
democracy index
support vector machines
JEL: 
C43
F50
F55
H00
O11
P48
Document Type: 
Working Paper

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