- The HCI framework is designed to show how well cities fairly and sustainably provide the conditions that create wellbeing. Cities are given overall scores and rankings in three dimensions: City Conditions, Equality and Sustainability (Level 1)
- Equality is assessed using indicators on inequalities in income, health and wellbeing across the city. Sustainability is assessed using indicators on CO2 emissions and household recycling and energy consumption levels.
- Cities can ‘drill down’ into the City Conditions dimension to see how well they are doing in five wellbeing domains – Work, Health, Education, Place and Community (Level 2)
- Each of these domains is further divided into sub-domains concerning key policy areas within each domain (Level 3)
This framework provides a systematic, empirical foundation to guide city progress. It collates a broad range of (60+) indicators from recognised national data sources, all of which are frequently updated and available at a local authority level for the England Core Cities (including London).
The development of the Happy City Index has been a collaboration between Happy City and New Economics Foundation (NEF). It has benefited from the substantial academic support of both University of Bristol and University of Swansea. For more details please see our Full HCI academic Report here
For a full list of our advisory group, funders and supporters please see our partners page here
Below is a summary of the ten key design principles incorporated in the Happy City Index:
1. Outputs not inputs
The HCI measures city outcomes not inputs – it is concerned with the actual conditions faced by people within a city. For example, the Health domain consists in indicators on mortality and life expectancy, illness and disability, healthy and risky behaviours and mental health, rather than measuring the amount of money spent on public health.
2. Drivers of wellbeing
The HCI does not directly measure personal wellbeing. Instead, it measures the City Conditions that create wellbeing (i.e. the ‘Drivers of wellbeing’). Many of these conditions are considered to be policy outcomes in themselves, such as health, quality work, accommodation, neighborhood safety, and so on. Although indicators of personal wellbeing are available at a local level, they do not provide the same level of detail as available indicators on the city conditions that create wellbeing.
For example, overall measures of personal wellbeing measures, such as life satisfaction, may not be responsive to changes in health or quality work, despite these conditions being important drivers of wellbeing. We recommend that local authorities collect a wider range of personal wellbeing indicators, which can be used to understand both the drivers of wellbeing and citizens’ actual wellbeing.
3. Equality and Sustainability
In addition to City Conditions that create wellbeing, the HCI collates separate indicators on both Equality and Sustainability. This emphasizes the importance of how cities are providing drivers of wellbeing, namely that they are doing so in a fair and sustainable way.
Although it is possible to collect data on the distribution of particular city conditions, this data is not available for all indicators. Moreover, collecting general indicators on equality enables the comparison of key aspects of equality, such as income, health and wellbeing inequality. The same can be said of general sustainability indicators, such as carbon emissions, energy consumption and household recycling.
4. Wide range of indicators
The HCI is made up of indicators on a large range of policy areas and topics, with 60+ indicators from a number of different recognised national data sources (for a list of data sources see Appendix B of the overall Report here).
For instance, the City Conditions indicators are grouped into five domains shown by wellbeing research to be important aspects of wellbeing, namely Work, Health, Education, Place and Community. For each policy topic measured, there are multiple indicators related to that area. For instance, within the Place domain, there are five indicators for the topic of Transport, namely indicators on public transport and active transport (walking, cycling), air pollution, traffic, road maintenance and road traffic accidents. This ensures a number of key aspects are covered for each policy topic.
This broad range of indicators reflects the increasing understanding that wellbeing is a multi-dimensional concept, determined by a number of diverse factors. Moreover, these factors tend to be causally connected to each other to create a ‘web’ of conditions that impact on people’s wellbeing. In order to effectively and systematically improve people’s wellbeing, policymakers need to consider all of these indicators together, rather than trying to improve particular factors in isolation.
5. Accounting for measurement ‘gaps’
The HCI dimensions, domains and sub-domains do not include equal amounts of indicators – with a number of policy topics there are ‘gaps’ in the indicators available. For instance, on the topic of Social isolation, there is only one available indicator for all England Core Cities, which focuses on the social isolation experienced by care workers. This indicator can be improved on in the future, with a wider focus, as well as being complemented by additional indicators on social isolation. Nonetheless, the topic was included within the HCI to reflect its importance for people’s wellbeing and inspire local authorities to account for such measurement gaps in the future.
6. Broad range of objective and subjective indicators:
The HCI aims to gather both objective and subjective indicators on each topic. For instance, within the Community domain, there are two indicators for the topic of Culture, one objective (number of museums, libraries etc. per capita) and one subjective (how often people access museums, libraries etc.). This mix of objective and subjective indicators provides a richer understanding of the topic.
However, both objective and subjective indicators are not available for each topic included in the HCI. For example, within the Place domain, there are five indicators for Safety. Currently, each indicator is objective, relating to the crime rate per capita. In the future, these objective indicators could potentially be complemented with subjective indicators, such as perceive neighbourhood trust, safety or security.
7. Frequently updated
The HCI indicators were chosen to understand city progress over time, with the majority of indicators being updated on an annual basis. This enables local policymakers to see what conditions in the city are getting better or worse and thereby which policy areas they need to prioritise to improve people’s wellbeing.
8. High-level data
The HCI consists in high-level city data – indicators available at a local authority level, rather than at lower levels, such as ward-level or LSOA-level. The wide range of indicators that make up the HCI is unfortunately not available at lower levels.
Future iterations of the HCI could include data on the indicators available at both a local authority level and lower levels. This can provide local policymakers with the capacity to further ‘drill down’ on the data and see how key policy outcomes vary across the city.
9. England Core Cities
The HCI project collects data for each of the England Core Cities, including London. This enables cities to compare how well they are doing in comparison with similar cities. The wide range of indicators that make up the HCI is unfortunately not available for the other UK Core Cities, in Wales, Scotland and Northern Ireland.
Similar to lower levels of data, future iterations of the HCI could include data on the indicators available for both England and other UK Core Cities. Data can also be collected for a larger range of local authorities in the UK, including cities and towns that are not part of the Core Cities network.
10. Urban and Rural
The HCI is a unified dataset for both urban and rural local authorities. This accounts for the fact that many local authorities cover both urban and rural areas and require a unified set of progress indicators.
The conditions that create wellbeing are different for urban and rural contexts. For example, the amount of citizens that walk or cycle to work, in comparison to using ‘non-active’ transport (e.g. driving a car) will be greater in urban areas than rural areas. This does not necessarily reflect the fact that rural areas are doing worse than urban areas in this respect. These kinds of considerations are important when interpreting the HCI results and comparing different local authorities.