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Quality of Government Datasets (QoG Standard dataset)

Producer: 

Sören Holmberg & Bo Rothstein - QoG Institute

Stated Purpose: 

The aim of the QoG Institute is to make publicly available cross-national comparative data on quality of governance and its correlates. 

Area of Governance: 
Local Governance and Decentralization
Funding Source: 

Department of Political Science at Göteborg University, Sweden.

Current usage: 

Widely used in academic research. 

Type of data used: 

The datasets contain a wide range of different types of data: expert-coded indicators and classifications, various demographic measures, national accounts data and aggregated individual-level survey data. The data are compiled from numerous freely available and well-known data sources, including datasets produced by independent research projects, international research initiatives, NGOs and IGOs. The datasets are described in an extensive codebook, which is freely available for download. 

Coverage: 

Country Coverage: The datasets cover mainly the same countries, but the time-series version contains some additional cases. The coverage of specific variables is often more limited:

  • Cross-Section Dataset: All countries in the world recognised by the United Nations in 2002, plus Taiwan (192 countries in all).
  • Cross-Section Time-Series Dataset: All countries in the world recognised by the United Nations in 2002, plus Taiwan and 13 historical countries that no longer exist.

Year Coverage: 

  • Cross-Section Dataset: Data for 2002 or the closest year available Cross-Section
  • Time-Series Dataset: 1946-2009

The datasets will be updated continuously. Last update: April 2011.  

Contact details: 

Dataset manager
Stefan Dahlberg PhD 
stefan.dahlberg@pol.gu.se  
Phone: +46 (0) 31 786 17 81

Methodology: 

The QoG Cross-Section Dataset and the QoG Cross-Section Time-Series Dataset (version 6 April 2011) are divided into three data types or topics:  

  • WII (What It Is): variables related to the core of the institute’s research area (e.g., corruption, bureaucratic quality, human rights and democracy).
  • HTG (How To Get It): variables believed to promote the quality of government (e.g., electoral rules, political institutions, legal and colonial origin, religion and social fractionalisation).
  • WYG (What You Get): variables pertaining to some of the possible consequences of government quality (e.g., economic and human development, international and domestic peace, environmental sustainability, gender equality, and satisfied and trusting citizens).
The group of What It Is” variables relate to the core indicators of QoG such as bureaucratic quality (Evans & Rauch’s Career Opportunities, Bureaucratic Compensation, and Meritocratic Recruitment indices; International Country Risk Guide; World Bank Governance Indicators), corruption (Transparency International’s Corruption Perception Index; World Bank’s Control of Corruption), and democracy (Freedom House; Polity; Vanhanen’s Index of Democratization; Polyarchy). 
The list of “How To Get It” variables are those perceived to influence or promote the development of QoG, such as electoral systems (Gerring et al.; Cheibub & Gandhi’s Regime Institutions), presidential vs. parliamentary forms of government, federal vs. unitary systems (Database of Political Institutions), and ethno-linguistic and religious fractionalization (Alesina et al.; Roeder).
Finally, they categorize a group of “What You Get” variables intended to measure suspected consequences of QoG such as economic development (Penn World Table), environmental sustainability (Esty et al.’s Environmental Sustainability Indices), gender equality (World Economic Forum’s Gender Gap), and peace. Besides the aggregate data produced by organizations such as Freedom House and the World Bank, micro-level data such as those produced by the World Values Survey and the Global Barometers are also included.

 

Valid Use: 

A major strength of the datasets is that they often provide several measures of the same concept, allowing users to choose between several indicators and to test whether different ways of measuring a phenomenon has any effect on the analyses. Furthermore, the indicators in this dataset are not useful for only studying the quality of government; these variables can be used to inspire a research agenda focused on making claims regarding levels or quality of democracy.