Research units A-Z

‘Inclusive growth’, ‘inclusive economy’ and ‘wellbeing economy’ are a family of ideas.

Each has various definitions but they are concerned with developing more inclusive, sustainable economic systems and outcomes.

In SIPHER, we focus on developing evidence and policy tools to support economic inclusion rather than inclusive growth, and have been working with our policy partners to identify appropriate indicators and credible datasets.

Systems approaches are closely aligned with inclusive economy ideas since both aim to take a holistic understanding of policy systems in which the economy is recognised as a complex, interconnected system rather than a collection of isolated components. This holistic perspective helps policymakers better understand the interdependencies and feedback loops that influence outcomes and goals across a range of policy areas (e.g. for SIPHER this includes economic and health policy goals).

Systems science often involves engaging a wide range of stakeholders to ‘map’ the policy system. This kind of participatory approach can help ensure a range of different perspectives (e.g. policymakers responsible for the economy and those responsible for health, as well as more marginalized community perspectives) are considered in policymaking processes.

Some systems models also identify how outcomes vary by social group or context, which can inform decision-making about where and how to reduce inequalities.

Dynamic systems modelling can simulate how economic systems change over time (and how this varies with different policy scenarios). This can support policymakers in thinking about longer-term impacts (as well as easier to measure, more immediate impacts). 

All this can help policymakers identify policies that are more likely to be inclusive.

SIPHER offers a range of support and tools to assit in the development of Inclusive Economies policy including: 

• Policy analysis that:
  • examines how policy teams working on different areas (i.e. different parts of the policy system) understand inclusive economy ideas;
  • clarifies ‘what the problem is represented to be’; and
  • identifies the priority policy goals and evidence needs.

• Participatory mapping to develop visual maps of the inclusive economy system, which enables an understanding of how different groups understand the inclusive economy policy system and facilitates evidence and data led analysis to identify key pathways leading to health outcomes.

• Critical analysis of potential inclusive economy indicators, informed by five criteria: Meaningful to decision makers as capturing a recognisable, relevant aspect of inclusive economies; Possible to estimate at local authority (LA) level (for LA analysis and as a building block for larger geographies); Capable of analysis over time (a consistent time series), both historic and updateable; Accessible (i.e. published, free and not requiring application process to enable use by non-specialists), in order to enable future use.

• Macro and micro, data-driven models to identify how different policy decisions will impact on inclusive economic and health indicators.

• Decision-support tools that draw on these models to provide relevant information, analysis, and visual (graphical) overviews that can help decision-makers think through the potential consequences of different decisions, for different social groups, over time.

• Policy analysis of inclusive growth as a malleable idea, which demonstrates the political utility of malleability and the political risks of metricisation.

Read: Hill O’Connor, C. , Smith, K., Hughes, C., Meier, P.  and Purshouse, R. (2023) Operationalising inclusive growth: can malleable ideas survive metricised governance? Public Administration (doi: 10.1111/padm.12916)  

• SIPHER-7 Wellbeing Indicators

• SIPHER Inclusive Economy dataset

• Employment and Health Evidence and Gap Map

• SIPHER Decision Support Tool