Evidence topic: Area based initiatives

Original evidence reviews published in January 2016. Updated evidence review on enterprise zones published May 2025.

Area based initiatives can have positive impacts on local growth outcomes, but displacement is a concern.

What are area based initiatives?

Area based initiatives (ABIs) are policy initiatives aimed at specific geographical areas, providing a package of support aimed at improving economic, social, or environmental outcomes within that area.

Some ABIs operate at large scales and offer a broad package of support. For example, many EU programmes targeted whole regions.

Others are more focused on a much more specifically defined geography, perhaps just a few square kilometres in size. Examples include enterprise zones and Regional Selective Assistance.

ABIs are popular in many countries as a tool for trying to tackle concentrated social or economic deprivation, especially in areas experiencing long term decline. Key elements of ABIs include:

• Tax breaks to firms
• Wage subsidies
• Reduced planning regulation
• Improvements to transport and communications infrastructure.

The rationale: How do area based initiatives deliver growth?

ABIs aim to improve local economic growth by incentivising firms to locate in the area, or by changing the economic conditions, helping firms to grow and develop. Both of these should lead to increases in the availability of jobs and improve productivity.

ABIs can also target households, for example, to improve education outcomes or labour market participation. We have not included these in our work on ABIs, but a number of the studies included in our evidence review evaluate programmes that involve some support for households as part of a wider package of support.

Evidence review: What does the evidence say about area based initiatives?

In 2016, we published the results of our review of the evaluation evidence on ABIs. This review looked for evidence on EU structural funds (such as the European Social Fund and the European Regional Development Fund), enterprise zones, and other area-based business support (such as Regional Selective Assistance). This review was published as two reports (one covering EU programmmes and one enterprise zones and other ABIs).

In 2025, we published an updated review of the evaluation evidence on enterprise zones. Both the 2016 and 2025 enterprise zone reports are available for download below. The text on this webpage on enterprise zones reflects the findings of the more recent review.

What the evidence showed:

Enterprise zones

• Half of studies that look at the effects of enterprise zones on the number of businesses find an increase in either the number of businesses, the number of new businesses or both.
• Less than 20 percent of the studies that look at employment within enterprise zones found a positive effect. Given that there are studies that show positive, mixed and no effects for the same policy, this suggests some of the variation may reflect either context or implementation.
• The evidence on whether local residents benefit (in terms of employment, unemployment or poverty) is mixed, with the strongest evidence in relation to reductions in unemployment. In some cases, positive outcomes for local residents may reflect displacement of pre-intervention residents.
• The evidence on wages and incomes is also mixed.
• The evidence on property prices and rents suggests that the benefits of enterprise zones may be capitalised into property prices.
• There is limited evidence of positive spillovers from enterprise zones on neighbouring areas, and some evidence of displacement.

EU programmes

• EU support has a positive impact on regional GDP per capita in a little under half of the evaluations that consider GDP effects.
• Half of the studies which look at employment effects show a positive effect of EU support on employment.
• The evidence on a range of other outcomes is mixed (with only one study per outcome).
• Positive impact is bigger in relatively more developed regions.
• Consistent with this, two out of three studies that consider the ‘dose’ (for example, expenditure per capita) suggest an optimum ‘level’ of treatment.

Where there was lack of evidence:

Enterprise Zones

• Whilst the evidence on enterprise zones has grown substantially since the publication of our original evidence review in 2016, there continue to be gaps in the evidence base.
• There is a need for more evaluation of the impact of the different policy levers (and different combinations of levers), whether impact varies across different types of area (for example, whether the area was growing or declining prior to designation), and on cost-effectiveness.

EU Programmes

• We have no evidence on the extent to which the different components of spend change the effectiveness of support.

Lessons:

• Policymakers should be realistic about the likely impacts of ABIs. One reason for this is that tax credits and other incentives generally result in small percentage changes in business costs and therefore may not affect outcomes. Another is that ABIs may lead to displacement – shifting activity around, rather than generating new activity.
• Policymakers should be clear on the goals of ABIs. For enterprise zones, the evidence is mixed on whether local residents benefit. Local hiring requirements may help if this is the objective as enterprise zones with these seem to be more effective at improving local residents’ labour market outcomes.
• Policymakers should consider the distributional impacts of ABIs. As with many local growth policies, the evidence suggests the benefits of enterprise zones are often capitalised into property values, benefiting property owners over renters.

Toolkit: Advice on designing area based initiatives

In addition to the evidence reviews, we have two policy design toolkits to help you to make informed decisions when designing ABIs.

Case studies: Advice on how to evaluate area based initiatives

Evaluating the economic effects of area based initiatives is challenging as they potentially affect multiple economic outcomes in ways that are hard for researchers to disentangle. There are also specific challenges in undertaking high quality impact evaluation. It is fairly easy to understand how we might construct control groups and undertake evaluation for policies targeted at individuals, households or firms. It is harder to do this for policies that explicitly target areas.

One reason evaluation of area based initiatives is particularly challenging is that often these locations will already be experiencing weaker economic growth, which is why they have been targeted by the policy. The effects of these underlying factors (‘selection effects’) must be accounted for if we want to understand the extent to which the area based initiative actually increases growth. Evaluations could, in principle, use randomised control trials to address these concerns but it is hard to imagine situations in which true randomisation would be either feasible or desirable. This means that we need to rely on alternative evaluation approaches to try to address the problem of selection and identify the causal impact of the programme

Another challenge in evaluating ABIs – especially small incentive areas like EZs – is identifying and measuring displacement. Looking only within the zone itself will not tell us if any new activity is displaced from elsewhere. Including the area surrounding the zone is not straightforward because if we draw that surrounding area too tight, we may miss displacement happening in the wider area. But if we draw the surrounding area too wide, it becomes very difficult to detect the beneficial effects of an ABI which may only be seen in a small part of that much larger geography.

To help improve evaluation of area based initiatives, we have five case studies that give examples of how previous policies have been evaluated.

Each evaluation case study has met our minimum standard of evidence, which means it (at a minimum) compares what changed for the places, businesses or individuals that benefited from an intervention with what changed over the same time frame for otherwise comparable places, businesses or individuals that didn’t benefit, or that received a different type of intervention.

The case studies use two different approaches to achieving this comparison. One study uses a randomised control trial (RCT), the gold standard of evaluation, and the others use statistical approaches to try to ‘strip out’ the impact of the other factors that could have affected outcomes in both the beneficiary group and the comparator group.