Does size or age matter? Describing charity demographics
How does the size and age of a charity impact their needs and the challenges they face? Understanding the nuances and supporting the diverse landscape of charitable organizations in Canada can only be achieved with data enabling us to conduct deeper analyses. However, agreeing to what those measures and ranges should be is no simple task. The Charity Insights Canada Project (CICP) is delving into the nuances of assessing charities based on their size and age, using data provided by the Canada Revenue Agency (CRA) and the survey responses of our participating charities.
Defining Size and Age
Size and age are multifaceted dimensions that provide valuable context when evaluating charities. To classify participating charities in the CICP by size, we rely on data from the CRA, primarily focusing on total expenditures as reported in the T3010 forms. This metric offers a tangible measure of a charity’s financial scope and operational capacity. While revenue is more volatile from year to year, expenditure provides a more stable indicator of a charity’s ongoing commitments and activities.
Age, on the other hand, reflects the “official” duration of a charity’s existence. While CRA records typically indicate the date of incorporation, exceptions exist which can complicate a precise age determination of an organization. Nonetheless, understanding whether a charity is a newly established initiative, or a longstanding institution is crucial for assessing its potential needs and challenges.
Why is it so difficult then?
Despite the wealth of information available from CRA records, several challenges must be navigated when analyzing charities based on size and age. Firstly, there is a time delay in accessing the most recent financial data, as CRA processes and releases T3010 filings over a year after they are completed. This time delay is due to the time it takes to input filings received by CRA and also because some charities may refile within the year with changes to financial information. However, this delay means we are unable to access the complete T3010 information from 2022 for our analysis of 2023 survey respondents. Instead, we will rely on 2021 CRA filings for our analysis until more recent data is available.
Secondly, incomplete records and instances of duplicate filings further complicate data interpretation. It is not uncommon to find the same organization multiple times in the CRA’s publicly available database as “updates” from charities are added as a new entry. This requires careful validation and reconciliation efforts on the part of our research team. Additionally, reporting errors, whether due to inaccuracies in filling out forms or data entry mishaps, can affect the accuracy of records on file. Our team does its best to diligently review and reconcile errors.
What about size and age?
There is no clear consensus of what constitutes a small organization or an older one. Reporting the exact age or budget could also infringe on the agreed confidentiality of survey participants as one could figure out which charities responded to our surveys by mining these precise identifying data attributes. What can we do if we want to explore the data while respecting our ethical obligations? One approach is to analyze the population data, i.e. all organizations from which our random sample has been recruited to understand the distribution of the data and create “filtering” categories. For example, we found that the Canadian population of registered charities (excluding schools, university, hospitals, and places of worships for instance) for the CICP project consists of the following age and size categories:
Expenditures of Charities Groups | Number of Charities | Number of CICP Participants from 2023 |
---|---|---|
$1-$11,661 | 6379 | 41 |
$11,662-$61,529 | 6378 | 55 |
$61,530-$229,133 | 6378 | 160 |
$229,134-$791,421 | 6378 | 277 |
$791,421-$4,690,000,000 | 6378 | 404 |
Age of Charity Groups | Number of Charities | Number of CICP Participants from 2023 |
---|---|---|
1-15 years old | 7045 | 105 |
16-24 years old | 6069 | 99 |
25-32 years old | 6364 | 128 |
33-41 years old | 6191 | 272 |
42-57 years old | 6198 | 333 |
There is no perfect solution, there can only be transparent approaches. By creating these five distinct categories based on the actual data we have of our study population, we can assess the validity of our study sample and the areas where more recruitment efforts might be needed. We know extra small organizations are challenging to reach but consist of a large number of the Canadian population of registered charities. We hope we can eventually converge toward shared measures, however imperfect they may be, to increase our ability to compare across sectors of activities and other important dimensions. We hope to spur a healthy and robust conversation.
In Conclusion
Assessing the charities participating in the CICP project through the lenses of size and age provides us with more ways to determine their diverse needs and challenges. For instance, we will be exploring the differences in survey responses between larger and smaller participating charities as well as between more established and emerging charities. By leveraging data from the CRA and contextualizing it in relation to our survey information, we aim to provide insights that can be used by stakeholders to better tailor support mechanisms, foster collaboration, and maximize the collective impact of the charitable sector.
Authors
McWhinney, Tara
- Postdoctoral Fellow
- taramcwhinney@cunet.carleton.ca
Raggo, Paloma
- CICP Director & Principal Investigator
- paloma.raggo@ carleton.ca
- 613-520-2600 ext x 2555
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