How do we produce the Almanac?
Overview
We estimate the size, scope and finances of the UK voluntary sector using two sources of data:
- data for all registered charities based on the Charity Commission register
- detailed financial data for a sample of charities using their financial accounts.
This core data has been collected by NCVO for over ten years.
- Data for the whole population of ‘general charities’: The Charity Commission register holds data for all registered charities in England and Wales. This data is used to provide basic information on the whole population of charities after we have applied our ‘general charities’ definition.
- A sample of the financial data: Data is obtained for a sample of 10,000 charities by taking their financial accounts and manually inputting them into a database. For the purpose of the Almanac, we then include only those charities that meet the ‘general charities’ definition. This data is then weighted up to the total population, to provide detailed information on income sources and types of spending.
Aggregate data for Northern Ireland and Scotland is added in to provide an overall picture for the whole UK.
- We supplement this core financial data with analysis of the Community Life Survey, NCVO’s Time Well Spent survey, the Labour Force Survey and a range of other data sources.
- In addition this year, we have worked in partnership with CharityJob to produce estimates of the number and types of vacancies, and average salaries offered in 2022, and how this has changed since 2019, based on jobs posted on the CharityJob website. This used a subset of the data underpinning the CharityJob Salary Report 2023.
Voluntary sector data
Financial data
Financial information on voluntary organisations is based on financial accounts data submitted to the Charity Commission. The Charity Commission publishes some of this information in the register:
- Total income and spending of all registered charities.
- More detailed financial information for all registered charities with an annual income of £500,000 or more (known as ‘part b’)
This digital data forms the basis of financial data in the Almanac and provides the total figures for income and spending for all registered charities.
However, the data available digitally is somewhat limited:
- Only larger charities have to submit financial data beyond total income and spending.
- Part b data does not give very detailed information about different income types or sources.
Therefore, NCVO extracts additional data for a sample of charities. The Charity Commission register is used as a sampling frame to select a sample of about 10,000 registered charities, of which just over 7,600 are general charities.[1]
For these charities, additional financial data is obtained by manually entering data from the PDF document of their financial accounts into a database. This data entry process is carried out for NCVO by the Centre for Data Digitisation and Analysis at Queen’s University Belfast.
Sampling the financial data
The original sample design was based on a random sample of charities stratified by their size in terms of annual income.
Income was used because this variable is both a key determinant of sampling error and a key variable for analysis.
Different sampling fractions are applied to the different strata (income bands) with fractions increasing with the size of organisations.
Most major organisations (83%) and all super-major organisations (those with an income of £100m and more) are sampled while only about 2.5% of small charities are sampled.
Data is weighted at the analysis stage to take account of the different sampling fractions, allowing us to estimate the size of the total sector.
Data classification
Within the Almanac, the income of voluntary organisations is classified by type and source. This is one of the main features of the Almanac analysis and takes up most of the time during data processing.
Income type describes how the income is obtained:
- Voluntary income: Donations, grants or legacies
- Earned income: Contracts, membership fees, charity shops, or fundraising activities
- Investment income
The source of income describes who has provided the income:
- The public
- Government
- Voluntary sector
- Corporate/business sector
- National Lottery
- Investment income
To classify the data, we use a combination of machine learning, keyword matching and, for a small proportion, manual classification.
Data cleaning
The data is then cleaned to remove errors and undergoes a series of checks to ensure validity.
These checks include:
- Comparison of income, expenditure and assets data between this year and last year to look for particularly large increases and decreases (which might indicate anomalies or errors).
- Construction of various ratios between financial variables (for example between income and expenditure, and investments and dividend income) to look for anomalies.
- Manual checking of annual accounts submitted by super-major (and some major) charities.
Consistency of financial values
- Where accounts are submitted in a foreign currency, all values are converted to Pounds Sterling using an average of the exchange rate over the year.
- Organisations have a range of financial year ends, distributed throughout the year. To assist consistency, all values are converted to April 2021 prices using the retail price index (RPIX).
- The retail price index (RPIX) is also used for trend data to convert actual values from previous years to April 2021 prices.
Producing UK totals
Once the data is cleaned, ratios are produced for all financial variables in the sample within each income band and are multiplied up to the England and Wales population size using weights based on income bands.
These ratios are also applied to supplementary data from SCVO (Scottish Council for Voluntary Organisations) and NICVA (Northern Ireland Council for Voluntary Action) to produce estimates of the UK population.
Assigning organisations to a subsector
Subsectoral analysis in the Almanac is based on assigning organisations to categories in the International Classification of Non-profit Organisations (ICNPO).
The ICNPO is a classification system for non-profit organisations designed by the Center for Civil Society Studies at Johns Hopkins University in the US as part of efforts to draw up a UN Satellite Account for the non-profit sector[2].
It is the most useful tool to classify and compare different groups of voluntary organisations, and is used throughout the Almanac.
The classification is done through a variety of different methods including keyword searches, matching to other registers and looking at individual sources.
As the original system was not a perfect fit for the UK voluntary sector, several categories were added for specific types of organisations that occur in large numbers (such as scout groups and nurseries). For more information about the different categories, have a look at our page on definitions in the Almanac.
In reality, many organisations undertake multiple activities (e.g. housing and advice), but the ICNPO groups organisations into a single category based on their primary activity.
The advantage of the ICNPO over a multi-dimensional classifications system (such as the classification system used by the Charity Commission), is the ability to look at and compare discrete groups of charities.
Like all classifications, this classification is not perfect. However, it does allow for the comparison of groups of charities and it does cover the activities of the whole sector.
Workforce data
Labour Force Survey
Our workforce figures are based on the Labour Force Survey (LFS). The LFS surveys around 38,000 households every quarter. By pooling data for unique individuals from four quarters, it is possible to produce reliable estimates of the voluntary sector’s workforce.
Weighting is used within the LFS to compensate for non-response rates in certain groups and produce population estimates. These weightings have been updated retrospectively for the 2020 figures, which means that the values reported in this year’s Almanac for any data from 2020 will be slightly different to those used in previous editions of the Almanac[3].
The figures for each quarter presented in the Almanac are calculated by using a moving or rolling centred average over four quarters. This ensures some seasonality is smoothed out and that all four quarters are represented in any given year.
To identify the sector in which a respondent is employed, a two-stage self-classification process is used. Respondents are first asked whether they work for ‘a private firm, business or a limited company’ or ‘some other kind of organisation’.
Those respondents who choose the second option are then asked, ‘What kind of non-private organisation is it?’.
They are then presented with a range of options including ‘charity, voluntary organisation or trust’. For the purposes of the analysis for the Almanac, responses to these questions are recoded into ‘private’, ‘public’ or ‘voluntary’.
Volunteering data
Community Life Survey
The Almanac analysis on volunteering trends draws largely on the Community Life Survey (2012/13-present) and its predecessor, the Citizenship Survey (2001-2010/11), the best sources of trend data on rates of volunteering in England.
Since 2016/17 the survey has been commissioned annually by the Department for Digital, Culture, Media and Sport. It is representative of adults aged 16 and over in England.
The survey covers both ‘formal volunteering’, which takes place through a group, club or organisation; and ‘informal volunteering’, which includes volunteering time to help others independently of an organised group.
Data is drawn from the most recent survey unless otherwise stated and includes the appropriate weighting.
There was a gap in the data in 2011/12, during the transition between the two surveys, which did not disrupt the time series. In 2016/17, however, the data collection method changed.
The survey moved from being a face-to-face interview to an online/paper version which respondents complete themselves (self-completion with no interviewer assistance).
This move meant significant savings in costs, allowing DCMS to increase the sample size from 3,027 in 2015/16 to at least 10,000 a year now.
However, it also has a significant impact on response rates and question responses, affecting trend data due to sample, response and mode effects.
Time Well Spent
The volunteering section also draws on Time Well Spent survey which NCVO worked on in 2018, focusing on the experiences of volunteers and the volunteer journey.
The survey was completed by adults aged 18+ in Great Britain through YouGov’s panel, via an online self-completion questionnaire.
The total sample achieved was 10,103 respondents. The data was weighted to reflect the national population by key demographics:
- age
- gender
- education level
- social grade.
Almanac 2022
For financial years 2019 to 2020, we have used Scotland data for the period 2018-19 (inflated to 2019/20 terms).
This is because we did not have access to the Scotland data in time for publication. Also, we have used Northern Ireland data for the period 2017-18 (inflated to 2019/20 terms) as data was not available for 2018 to 2020 period.
This is to the Charity Commission for Northern Ireland (CCNI) having to rebuild its register due to a decision in the Court of Appeal about who has the power to declare an organisation a charity in that jurisdiction. See the Charity Commission website.
Vacancy salary data
CharityJob Salary Report 2023
Data on job vacancies and salary levels were provided and analysed by our Almanac salary data partners at CharityJob.
Overview figures are based on data from all 61,900 jobs posted on CharityJob’s website in 2022 using data from the CharityJob Salary Report 2023, which includes data on average salaries for different job types in the charity sector, and salary trends across the UK charity sector as a whole.
The bespoke data findings produced by CharityJob for the Almanac are based on the 29,100 UK-registered charity job vacancies posted by organisations in 2022 that meet the NCVO’s definition of general charities.
This is 47% of the total jobs posted. Comparisons are made to equivalent data from 2019 to show how the recruitment market has changed.