QoG Social Policy Dataset

Creator/Principal investigator(s):

Jan Teorell - Lund University, Department of Political Science orcid

Richard Svensson - University of Gothenburg, Department of Political Science

Marcus Samanni - University of Gothenburg, Department of Political Science

Staffan Kumlin - University of Gothenburg, Department of Political Science

Stefan Dahlberg - University of Gothenburg, Department of Political Science

Bo Rothstein - University of Gothenburg, Department of Political Science

Sören Holmberg - University of Gothenburg, Department of Political Science

Description:

The QoG Institute is an independent research institute within the Department of Political Science at the University of Gothenburg. Overall 30 researchers conduct and promote research on the causes, consequences and nature of Good Governance and the Quality of Government - that is, trustworthy, reliable, impartial, uncorrupted and competent government institutions.

The main objective of our research is to address the theoretical and empirical problem of how political institutions of high quality can be created and maintained. A second objective is to study the effects of Quality of Government on a number of policy areas, such as health, the environment, social policy, and poverty.

The dataset was created as part of a research project titled “Quality of Government and the Conditions for Sustainable Social Policy”. The aim of the dataset is to promote cross-national comparative research on social policy output and its correlates, with a special focus on the connection between social policy and Quality of Government (QoG).

The data comes in three versions: one cross-sectional dataset, and two

... Show more..

Creator/Principal investigator(s):

Jan Teorell - Lund University, Department of Political Science orcid

Richard Svensson - University of Gothenburg, Department of Political Science

Marcus Samanni - University of Gothenburg, Department of Political Science

Staffan Kumlin - University of Gothenburg, Department of Political Science

Stefan Dahlberg - University of Gothenburg, Department of Political Science

Bo Rothstein - University of Gothenburg, Department of Political Science

Sören Holmberg - University of Gothenburg, Department of Political Science

Identifiers:

SND-ID: EXT 0004

Purpose:

The primary aim of QoG is to conduct and promote research on corruption. One aim of the QoG Institute is to make publicly available cross-national comparative data on QoG and its correlates.
The aim of the QoG Social Policy Dataset is to promote cross-national comparative research on social policy output and its correlates, with a special focus on the connection between social policy and Quality of Government (QoG).

Description:

The QoG Institute is an independent research institute within the Department of Political Science at the University of Gothenburg. Overall 30 researchers conduct and promote research on the causes, consequences and nature of Good Governance and the Quality of Government - that is, trustworthy, reliable, impartial, uncorrupted and competent government institutions.

The main objective of our research is to address the theoretical and empirical problem of how political institutions of high quality can be created and maintained. A second objective is to study the effects of Quality of Government on a number of policy areas, such as health, the environment, social policy, and poverty.

The dataset was created as part of a research project titled “Quality of Government and the Conditions for Sustainable Social Policy”. The aim of the dataset is to promote cross-national comparative research on social policy output and its correlates, with a special focus on the connection between social policy and Quality of Government (QoG).

The data comes in three versions: one cross-sectional dataset, and two

... Show more..

Time period(s) investigated:

1946 — 2009

Geographic spread:

Geographic description: Time-series datsets ("long" and "wide"): 40 countries Cross-sectional dataset: 194 countries

Lowest geographic unit:

Country

Highest geographic unit:

Country

Unit of analysis:

Population:

Countries

Sampling procedure:

Total universe/Complete enumeration
Non-probability
Cross-sectional dataset: All countries recognized by United Nations as of year 2002, plus Taiwan and Serbia and Montenegro (both as a unit and as two separate states). Total 194 countries.

Time-serie dataset, long and wide: Selected accordning to two criteria. I) countries among the 30 most data-rich countries in the global sample, or II) is a current member of the European Union. Total 40 countries.

Citation requirement:

Samanni, Marcus. Jan Teorell, Staffan Kumlin, Stefan Dahlberg, Bo Rothstein, Sören Holmberg & Richard Svensson. 2012. The QoG Social Policy Dataset, version 4Apr12. University of Gothenburg:The Quality of Government Institute. http://www.qog.pol.gu.se

Contact person for questions about the data:

Stefan Dahlberg

Publications

Link to publication list:

If you have published anything based on these data, please notify us with a reference to your publication(s).

Dataset EXT 0004-001

The QoG Social Policy Cross-Section Data

Description:

A cross-section dataset based on data from and around 2002 of QoG Social Policy-dataset. If there was no data for 2002 on a variable, data from the year closest year available have been used, however not further back in time than 1995.

Data format / data structure:

Numeric

Time period(s) investigated:

2002

Dataset EXT 0004-002

The QoG Social Policy Long Time-Series CS Data

Description:

The dataset combining cross-sectional data and time-series data for a selection of 40 countries spanning the time period 1946-2009.

Data format / data structure:

Numeric

Time period(s) investigated:

1946 — 2009

Dataset EXT 0004-003

The QoG Social Policy Wide Time-Series CS Data

Description:

The dataset combining cross-sectional data and time-series data for a selection of 40 countries. The dataset is specifically tailored for the analysis of public opinion data over time, instead uses country as its unit of observation, and one variable for every 5th year from 1970-2005 (or, one per module of each public opinion data source).

Data format / data structure:

Numeric

Time period(s) investigated:

1970 — 2005