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Introducing the MaxRange Dataset: Monthly Data on Political Institutions and Regimes Since 1789 and Yearly Since 1600
Halmstad University, School of Education, Humanities and Social Science.
West Virginia University, Morgantown, West Virginia, USA.
Halmstad University, School of Education, Humanities and Social Science, Center for Social Analysis (CESAM). Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).ORCID iD: 0000-0001-9495-3571
2015 (English)Conference paper, Published paper (Other academic)
Abstract [en]

The MaxRange dataset provides information on political institutions for all countries of the world going back to 1789 on a monthly and yearly basis, and to 1600 on a yearly one.  The yearly dataset spanning 1600 to 2014 has over 90,000 country-year observations, and in its monthly format from 1789 has over 660,000 observations.  The time-series data are at least 200 years longer than any other comparable time-series dataset on political institutions.  Created by Max Rånge, the datasets aggregate specific attributes to create nominal and ordinal rankings of political regimes on a 1-100 scale (the MaxRange1 dataset) and on a 1-1,000 scale (the MaxRange2 dataset).  At the same time, however, the codes for each attribute underlying the categorization of political regimes are also included.  It is more detailed than any other dataset on political institutions, yielding up to 1,000 different unique combinations of institutional features.  In addition to supporting a rigorous classification of democratic and nondemocratic regimes, the dataset allows researchers to exploit institutional variation and to explore alternative ways of aggregating political institutions.  The MaxRange dataset on political institutions is by far the biggest and most comprehensive political regime dataset to date, and it offers several advantages compared to other available data.  In particular, the availability of monthly time-series data provides greater detail and reliability to support more accurate research on political transitions.  

Place, publisher, year, edition, pages
2015. 1-35 p.
Keyword [en]
institutions, political institutions, democratization, democracy, dataset, time series, MaxRange, regime types
National Category
Social Sciences Interdisciplinary
Identifiers
URN: urn:nbn:se:hh:diva-29352OAI: oai:DiVA.org:hh-29352DiVA: diva2:850666
Conference
Second WINIR Conference (World Interdisciplinary Network for Institutional Research), Rio de Janeiro, Brazil, 10-13 September, 2015
Note

Article plus appendices, 57 pages.

Available from: 2015-09-02 Created: 2015-09-02 Last updated: 2016-02-01Bibliographically approved

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Rånge, MaxSandberg, Mikael
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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
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