The Irish Polling Indicator combines all Irish opinion polls for the Dáil Éireann into one estimate of public support for the parties. The project is maintained by Tom Louwerse and Stefan Müller. Our estimates were reported in the Irish Times, RTÉ News, and the Business Post.
Scroll down for the latest estimates, interactive graphs, a description of the method, access to the raw data, and blog posts. You can follow the Irish Polling Indicator on Mastodon and Twitter.
| Party | Estimate | 95% Uncertainty Margins |
|---|---|---|
| Sinn Féin | 33.5% | 31.5%–35.5% |
| Fine Gael | 22.5% | 20.5%–24.5% |
| Fianna Fáil | 19.5% | 17.5%–21.5% |
| Other/Independent | 10% | 8.5%–11.5% |
| Green Party | 4.5% | 3.5%–6% |
| Labour | 3% | 2.5%–4% |
| Social Democrats | 3% | 2%–3.5% |
| Solidarity-PBP | 2.5% | 2%–3.5% |
| Aontú | 1.5% | 1.5%–2.5% |
| Latest update: Jan 22, 2023. A note on the Bayesian credible intervals: If all of the assumptions of our model hold, then there is a 95% probability that a party’s support is within the range of the 95% uncertainty margins. |
The graph below displays the house effects of the polling companies for each party. A positive house effect means that a pollster structurally estimates a certain party higher than the average pollster. The dot indicates the best estimate for the house effect, the lines display 95% uncertainty margins.
The basic idea of the Irish Polling Indicator, launched in 2014, is to take all available polling information together to arrive at the best estimate of current support for parties. Polls are great tools for measuring public opinion, but because only a limited sample is surveyed, we need to take into account sampling error. By combining multiple polls, we can reduce this error.
Moreover, with so many polls going around it is difficult to get a random sample of voters to participate in any one public opinion survey. And those that do participate might not have a clear idea who to vote for, something that is often adjusted for in polls. This may lead to structural differences between the results of different polling companies, so-called house effects.
The Irish Polling Indicator considers sampling error and house effects when aggregating support for Irish parties.
We provide full access to all available polling results (1982–2022) and daily aggregated estimates (1987–2022). We provide the daily estimates and raw polling results in four file formats. A detailed codebook describes both datasets and all variables.
Development Version (Latest Data Release)
First, we release our datasets as a development version which is updated after the release of every poll and stored in a GitHub repository.
Irish Polling Indicator estimates:
Raw polling results:
If you use the development version of the data in your work, please consider citing:
Tom Louwerse and Stefan Müller. 2023. Irish Polling Indicator Datasets: Development Version. URL: https://github.com/Irish-Polling-Indicator/ipi-data.
Stable Version
Second, we provide a stable version of the daily estimates and raw polling results. New releases are published after an election cycle. The stable version has a unique identifier (DOI: 10.7910/DVN/BY5GXC).
If you use the stable version in your work, please consider citing:
Tom Louwerse and Stefan Müller. 2022. Irish Polling Indicator Datasets: Stable Version. Harvard Dataverse, V1. DOI: 10.7910/DVN/BY5GXC
In addition to the Irish Polling Indicator data, the Irish Demographic Polling Datasets collect results on vote intentions, satisfaction with the government, and popularity of party leaders. The polling results are available for all respondents and various subsamples, such as age groups, gender, social class, geographic region, and district magnitude. The database merges over 100 polls, published between 2011 and 2022.
All datasets and variables are described in a detailed report and codebook (PDF). If you use the Irish Demographic Polling Datasets in your work, please consider citing:
Thomas Pluck and Stefan Müller. 2022. Irish Demographic Polling Datasets. URL: https://github.com/Irish-Dem-Polling/datasets
Tom Louwerse is an Associate Professor in Political Science at Leiden University, the Netherlands. Tom’s research and teaching focuses on elections, political representation and parliamentary politics in the Netherlands and other established democracies.
Website | CV | Mastodon
Stefan Müller is an Assistant Professor and Ad Astra Fellow in the School of Politics and International Relations at University College Dublin. Stefan’s research focuses on political representation, party competition, political communication, public opinion, quantitative text analysis, and the application of computer vision techniques.
Website | CV | Twitter | Mastodon
The Irish Polling Indicator is hosted at the Institute of Political Science at Leiden University and the Connected_Politics Lab at University College Dublin. The project received financial support from the 2021 Strategic Funding Scheme of the UCD College of Social Sciences and Law.
Please do not hesitate contact us if you have any questions about the project or if you would like to include our estimates in reports or articles. If you refer to our data, please mention the Irish Polling Indicator and its maintainers, Tom Louwerse and Stefan Müller. Feel free to use the data in your academic work, and please consider citing the Irish Polling Indicator data.
