Summarizing Data using Partially Ordered Set Theory: An Application to Fiscal Frameworks in 97 Countries * Julia Bachtrögler 1 , Harald Badinger 1,2 , Aurélien Fichet de Clairfontaine 1 , and Wolf Heinrich Reuter 1 1 Vienna University of Economics and Business, Department of Economics, Welthandelsplatz 1, 1020 Vienna, Austria. E-mail: julia.bachtroegler@wu.ac.at, harald.badinger@wu.ac.at, afichet@wu.ac.at, wolf.reuter@wu.ac.at 2 Austrian Institute of Economic Research (WIFO), Arsenal, Objekt 20, 1030 Vienna, Austria. December 15, 2014 Abstract The widespread use of composite indices has often been motivated by their practicality to quantify qualitative data in an easy and intuitive way. At the same time, this approach has been challenged due to the subjective and partly ad hoc nature of computation, aggre- gation and weighting techniques as well as the handling of missing data. Partially ordered set (POSET) theory offers an alternative approach for summarizing qualitative data in terms of quantitative indices, which relies on a computation scheme that fully exploits the available information and does not require the subjective assignment of weights. The present paper makes the case for an increased use of POSET theory in the social sciences and provides a comparison of POSET indices and composite indices (from previous stud- ies) measuring the "stringency" of fiscal frameworks using data from the OECD Budget Practices and Procedures survey (2007/08). JEL Codes. C43, H60, E02, E62 Keywords. Partially Ordered Set Theory, Composite Indices, Index Functions, Fiscal Frame- works, Fiscal Rules, Budgetary Procedures ∗ Financial support by the Austrian Central Bank (OeNB, Anniversary Fund, project number: 15469) is gratefully acknowledged. We also wish to thank Elisabeth Nindl for her detailed comments on earlier drafts of this paper.