Using support vector machines for measuring democracy

Klaus Gründler () and Tommy Krieger

No 130, Discussion Paper Series from Julius Maximilian University of Würzburg, Chair of Economic Order and Social Policy

Abstract: We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its exibility it is also a valuable tool for comparison studies.

Keywords: Democracy; Support Vector Machines; Democracy Index (search for similar items in EconPapers)
JEL-codes: C43 C65 C82 H11 P16 (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-cmp and nep-pol
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:wuewwb:130

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