Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/231298
Authors: 
Gründler, Klaus
Krieger, Tommy
Year of Publication: 
2021
Series/Report no.: 
ZEW Discussion Papers No. 21-012
Abstract: 
We provide a comprehensive overview of the literature on the measurement of democracy and present an extensive update of the Machine Learning indicator of Gründler and Krieger (2016, European Journal of Political Economy). Four improvements are particularly notable: First, we produce a continuous and a dichotomous version of the Machine Learning democracy indicator. Second, we calculate intervals that reflect the degree of measurement uncertainty. Third, we refine the conceptualization of the Machine Learning Index. Finally, we largely expand the data coverage by providing democracy indicators for 186 countries in the period from 1919 to 2019.
Subjects: 
Data aggregation
Democracy indicators
Machine Learning
Measurement Issues
Regime Classifications
Support Vector Machines
JEL: 
C38
C43
C82
E02
P16
Document Type: 
Working Paper

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