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Using small scale output data to inform local economic policy

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One of the things What Works Growth hopes to do over the next couple of years is provide more advice on using data to understand local context when developing policy. One of the challenges in this work has been difficulty in accessing timely data at the right spatial scale. The UK Office for National Statistics (ONS) is doing a lot of work to address these problems and on Tuesday they published their latest data resource – experimental data on GVA for small areas.

GVA, short for Gross Value Added, is one way of measuring the size of an economy using the value of the goods and services produced, excluding any intermediate products (hence ‘value added’). Because it excludes intermediate products – most of which will be shipped in from outside the local area – it provides a measure of the value of output that is available to compensate local workers and the firms that employ them.

Historically, GVA data has been available for countries and regions. More recently it has been available for local authority areas. ONS’s new experimental data provides GVA at a much smaller spatial scale – lower-layer super output areas (LSOAs) (England and Wales), data zones (DZs) (Scotland) and super output areas (SOAs) (Northern Ireland). To give a sense of the scale, LSOAs typically have a population of between 1,000 and 3,000, whilst DZs generally have between 500 and 1,000.

Such data should be useful for policymakers who want to understand what’s happening in different parts of their local economy – for example, Tyne Valley within Northumberland, or Caithness and Sutherland within Highlands. Alternatively, a local authority might want to look at the overall pattern of production – for example, identifying areas which account for a high proportion of local output.

More detailed data is useful because it can be aggregated up to geographies that policymakers might be interested in – such as constituencies or travel to work areas – or to understand what is happening in an area that cuts across local authority boundaries, for example, a transport route (e.g. West Midlands Metro).

The data published this week helps fill these gaps. Used properly it can:

  • Help policymakers to understand more about what’s happening to their local economy, supporting them to plan more effective policies.
  • Enable better evaluation of place-based policies (including infrastructure) to be undertaken.
  • Support research into local economic growth. For example, ONS has recently published interesting research looking at employment growth outside of towns and cities, giving useful insights on the dynamics of jobs growth in a way that wouldn’t be possible if ‘small area’ data didn’t exist.

As with all datasets, it’s important to understand how the data has been compiled and how it should be used. In this case, one important limitation is that whilst the data has been published for small areas, ONS recommends that you shouldn’t use it to look at individual small areas.

One of the main reasons for this is that because LSOAs, DZs and SOAs are small, they can play very different roles in an economy. For example, many LSOAs are predominately residential meaning their GVA is likely to be low, whilst others (for example, in a city centre) may have high GVA because high value jobs are concentrated in the area. Comparing these areas won’t be very insightful. It’s particularly important not to fall into the trap of dividing small area GVA by population and think that this provides a proxy for income – the example of city centre (lots of firms, few people) and residential areas (no firms, lots of people) should make the problem clear.

It’s also important to remember that ONS use other data sources to attribute higher level GVA data down to small spatial scales – which introduces measurement error at small spatial scales. The point of the small spatial scales is to allow flexibility in aggregating up to larger geographies, rather than provide a spuriously precise measure of how much GVA is produced in a specific LSOA. ONS has published data for some of the geographies they think might be of most useful such as travel to work areas and constituencies, but it’s possible for areas to build their own (making sure you understand the issues involved when moving to smaller spatial scales).

We’ve previously published a number of guides to using data to understand what’s happening in your economy including Using data for local economic policy and Recovery from Covid-19 at the local level: Using data to inform decision-making. This dataset is a useful addition to the data we highlight in these guides – and we encourage you to explore it.