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.
