Giving Ireland is a collaboration between 2into3 and Philanthropy Ireland.
It seeks to provide a platform for the Sector that will foster collaboration, provide insights and encourage collective action.
The Giving Ireland Report 2020 provides an analysis of how the Irish not-for-profit sector was funded in 2018. This is in response to an ongoing need for objective information on fundraising in Ireland. Formerly known as the annual ‘Irish Not-for-Profit Sector: Fundraising Performance Report,’ published by 2into3, this year marks the report’s 10th anniversary.
Giving Ireland’s objective is to provide insights into charitable giving in Ireland and support informed decision-making. The Report is intended to stimulate dialogue while encouraging more detailed and transparent reporting of fundraising data.
2into3 and Philanthropy Ireland came together to publish this report.
The research team at 2into3 are the authors of the report with contributions from Philanthropy Ireland.
BDO, one of Ireland’s largest accountancy and business advisory firms, complied the section relating to Taxation
The Giving Ireland Report estimates the total amount of philanthropic giving Ireland for the year 2018. This includes Legacies, Corporate Giving and Trusts & Foundations.
Where other reports focus on donor behaviour, such as CAF’s 2020 Ireland Giving Report, which examines the frequency of Giving by asking respondents whether they had donated funds or time in the last 30 days, Giving Ireland seeks to measure both individual and institutional fundraising in Ireland in a given year.
In addition, Giving Ireland breaks down the costs associated with fundraising by method and provides an overview of fundraising by subsector, method, and income bracket.
Giving Ireland’s data is sourced from Charities Regulator’s list of registered charities and Benefacts database.
Stratified random Sampling is used to depict the not-for-profit landscape in Ireland. This involves splitting the population of organisations into subsectors and taking a separate random sample from each of the subsector rather than a single random sample from the entire population.
When extrapolated, the relative size of each subsector is the same in both the sample and the population. Stratified sampling offers several advantages over simple random sampling, specifically it:
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