Australian Election Study Interactive Data

Sarah Cameron and Ian McAllister have launched an interactive online tool to explore the Australian Election Study (AES) data from 1987 to 2016. The tool shows trends in Australian political opinion over time, and enables the user to explore these trends by age group, gender, education level, and vote choice. Almost 100 charts are included, covering citizen attitudes towards: the election campaign; voting and partisanship; election issues; the economy; politics and political parties; the left-right dimension; the political leaders; democracy and institutions; trade unions, business and wealth; social issues; and defence and foreign affairs. The online tool is intended as a resource for those who teach, research, and study Australian politics, as well as journalists and members of the public.  The tool was produced with support from Small Multiples.

Follow the link below to explore the data online. If you would like to recreate a graph from the interactive web tool, you can download the underlying data in excel by following the second link.

To cite: Sarah Cameron and Ian McAllister. 2018.
Australian Election Study Interactive Data.
www.australianelectionstudy.org

Electoral Integrity Project Data

  Electoral Integrity worldwide, 2012-2017

Electoral Integrity worldwide, 2012-2017

The Electoral Integrity Project produces a number of datasets on the quality of elections around the world. Central to this is the Perceptions of Electoral Integrity (PEI) survey, a worldwide post-election expert survey of electoral integrity, currently managed by Thomas Wynter. The latest release of Perceptions of Electoral Integrity (PEI 6.0) covers 285 elections in 164 countries from 2012 to 2017. In addition to the global survey of electoral integrity, the Electoral Integrity Project has fielded sub-state PEI expert surveys in the United States, Russia, the UK, and Mexico. The project fielded the Australian Voter Experience survey in 2016, looking at citizen perceptions of electoral integrity. These datasets can all be found on Dataverse following the link below.