Diversity and UK Firm Performance
Lead Research Organisation:
University College London
Department Name: Centre for Advanced Spatial Analysis
Abstract
This project's aim is to explore the economic effects of diverse teams and workplaces - and the wider role of urban diversity - specifically, on entrepreneurship and firm-level innovation and productivity in the UK. These are important issues that are under-explored, especially in the UK, largely because of data challenges. And exploring these issues in the way we set out will make a valuable contribution to the huge, ongoing public debates on equalities, diversity and inclusion - both in the UK and across the world.
Our project will combine administrative microdata, novel online data sources and frontier methods in econometrics and data science. Specifically, we will match LinkedIn data on individuals (via the Diffbot knowledge graph) to companies, then to administrative firm-level data (the Business Structure Database, plus patents and other info). Working in secure settings, we will use name analysis tools to probabilistically identify gender and ethnicity, and would also gather information on nationality and country of birth. We will focus the resulting panels on sectors where we're confident LinkedIn has good coverage - likely to be strategically important industries like tech, finance and business services - and run our data through multiple quality checks. We will use various tools to get closer to causality, including instrumental variable strategies and using policy 'shocks' such as a) Brexit and subsequent policy events, and b) recent UK gender pay gap legislation. We will also deploy a robust set of technical safeguards to ensure individuals' privacy, publishing only non-disclosive results.
The project will develop new knowledge in an important but under-researched set of topics. In the process it would also build a unique data platform that other researchers could use in the future. We will work together with leading industry, policy and civil society stakeholders with expertise on relevant concepts, data/methods and policy agendas. These enable the project to directly contribute to economic policymaking on productivity and its drivers, including the UK's emerging levelling-up agenda, while also informing business decision-making and speaking to important and ongoing wider public conversations.
The project will generate a series of linked outputs:
1/ Three research papers, covering links between gender and ethnic diversity (and their intersections) and firm-level productivity, innovation and entrepreneurship. These would be published as working papers on high-profile platforms, then submitted to peer-reviewed journals.
2/ Additional non-technical, short-form content for each paper - blogs, policy briefs and so on; inviting our network / community to co-author or directly contribute whenever possible;
3/ The underlying data platform, which (subject to permissions) we will make available to other researchers as a safeguarded data asset;
4/ The wider network / community of researchers and practitioners we will build through the co-production process.
Our project will combine administrative microdata, novel online data sources and frontier methods in econometrics and data science. Specifically, we will match LinkedIn data on individuals (via the Diffbot knowledge graph) to companies, then to administrative firm-level data (the Business Structure Database, plus patents and other info). Working in secure settings, we will use name analysis tools to probabilistically identify gender and ethnicity, and would also gather information on nationality and country of birth. We will focus the resulting panels on sectors where we're confident LinkedIn has good coverage - likely to be strategically important industries like tech, finance and business services - and run our data through multiple quality checks. We will use various tools to get closer to causality, including instrumental variable strategies and using policy 'shocks' such as a) Brexit and subsequent policy events, and b) recent UK gender pay gap legislation. We will also deploy a robust set of technical safeguards to ensure individuals' privacy, publishing only non-disclosive results.
The project will develop new knowledge in an important but under-researched set of topics. In the process it would also build a unique data platform that other researchers could use in the future. We will work together with leading industry, policy and civil society stakeholders with expertise on relevant concepts, data/methods and policy agendas. These enable the project to directly contribute to economic policymaking on productivity and its drivers, including the UK's emerging levelling-up agenda, while also informing business decision-making and speaking to important and ongoing wider public conversations.
The project will generate a series of linked outputs:
1/ Three research papers, covering links between gender and ethnic diversity (and their intersections) and firm-level productivity, innovation and entrepreneurship. These would be published as working papers on high-profile platforms, then submitted to peer-reviewed journals.
2/ Additional non-technical, short-form content for each paper - blogs, policy briefs and so on; inviting our network / community to co-author or directly contribute whenever possible;
3/ The underlying data platform, which (subject to permissions) we will make available to other researchers as a safeguarded data asset;
4/ The wider network / community of researchers and practitioners we will build through the co-production process.
Organisations
- University College London, United Kingdom (Lead Research Organisation)
- Dept for Business, Innovation and Skills, United Kingdom (Project Partner)
- Core Cities UK (Project Partner)
- TechNation (Project Partner)
- Office for National Statistics, United Kingdom (Project Partner)
- Ministry of Housing, Communities & L.Gov (Project Partner)
- Greater London Authority, United Kingdom (Project Partner)