Hosted by: Funded by: Researching the Third Sector

Guiding questions for session 1. Representativeness: what are we not seeing? 2. What are the challenges and opportunities provided by longitudinal perspectives? 3. How can we identify and think about different dimensions of organisational change? 4. Are specific methods needed for researching the third sector? 5. The future: what are the next steps relating to data and method?

Hosted by: Funded by: Reflecting on the use of administrative data for research: challenges, opportunities and future directions John Mohan and David Clifford Third Sector Research Centre, University of Southampton

Context: administrative data Exciting times for social science! Flagship social surveys in UK, but increasingly also access to administrative data Here: reflecting on TSRC’s experience of use of administrative data collected by Charity Commission

Context: Charity Commission data Charities – charitable purpose and public benefit Data collected as part of Charity Commission’s regulatory role Register computerised since early 1990s Financial information (detail depending on size), area of operation, what they do/ who they work with/ how they do it, etc.

Challenges What are we not seeing? Differences in administrative practice – Over time: changes in composition of charities on Register – Over space: Charity Commission vs OSCR Lack of metadata (but P-ADLS..)

Opportunities 1. Individual organisations’ income and expenditure over time – Cross-sectional (snapshot) and longitudinal (following organisations through time) perspectives 2. Population of organisations (large numbers) – Detailed disaggregation of patterns possible: e.g. by organisation and area characteristics

Example of opportunities Example of work on survival of charities Which kinds of charities, in which kinds of areas, have a higher probability of dissolution? – Inactive organisations included in our data – Focus on those charities to have had at least £5,000 in income at some point since 1995 (around 140,000 charities) – Disaggregation by: initial income; type of charity; area

Probability of charity dissolution in a given year: charity and area characteristics

Probability of charity dissolution in a given year: by local authority

Future directions.. 1.Detailed financial information for a random sample of 10,000 charities (in collaboration with NCVO), e.g. income streams, income sources 2.Linking organisations (charities) and individuals (trustees)

Future directions.. 3. Other sources of administrative data: move towards data sharing (‘open data’) -collected by voluntary organisations: finance and funding records; information about where services are delivered; feedback and performance data -collected by government and Big Lottery Fund: organisations and projects funded

Future directions.. Challenges of using these datasets -consistency -representativeness -metadata (P-ADLS: collating this information) -recognising limits as well as opportunities

Acknowledgements Steve Barnard, Peter Backus, Frida Geyne Charity Commission ADLS National Council of Voluntary Organisations

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