How to evaluate area based initiatives – UK Local Enterprise Growth Initiative (LEGI)

What was the programme and what did it aim to do?

This study analyses the impact of the UK’s Local Enterprise Growth Initiative (LEGI). From 2006 to 2011, the UK government disbursed 418 million pounds to 30 deprived areas. The policy aimed to generate economic growth in underperforming areas by supporting local businesses in the retail and services industries. Although Local Authorities had discretion regarding how the funds were allocated, in practice 60 per cent of the funds went towards business support in the form of business advice, grants, and loans. Businesses that benefited from the programme were typically those not reached by other business programmes, such as those headed by women and individuals from ethnic minorities.

What’s the evaluation challenge?

Evaluating revitalisation policies such as these is hard because the areas which receive the support are different to those which who do not. In this case, the policy targeted particular areas within the most deprived Local Authorities. In order to receive funding, Local Authorities had to present a proposal which means that areas that received the grants might have been better run than those that did not. As a result of this selection, if we compare differences in outcomes for business in treated areas to firm in other areas, these differences may not reflect the impact of the programme. Instead, they may simply reflect differences in the other characteristics (e.g. deprivation, quality of governance) of areas that receive support.

What did the evaluation do?

In order to address the issue of targeting within Local Authorities, the study focuses on identifying the overall effects for Local Authorities that receive support. To address concerns about which Local Authorities were targeted it exploits the fact that Local Authorities were eligible for treatment if they ranked below 50th place on one of six deprivation rankings. The study employs the regression discontinuity design (RDD) method to compare areas that were just eligible for treatment to areas that were very close to eligibility but did not meet the threshold. The basic premise of this method is that, given that threshold is arbitrary, areas with similar ranks are likely to be very similar except for the fact that those below the threshold are likely to receive the treatment. This means that differences in outcomes for areas around the threshold can be attributed to the treatment.

How good was the evaluation?

According to our scoring guide, the RDD method receives a maximum of 4 (out of 5) on the Maryland Scientific Methods Scale. This is because it does well to control for both observable (e.g. deprivation) and unobservable (e.g. quality of governance) differences between supported and non-supported areas. To achieve a 4, it must be that the Local Authorities did not change their behaviour to meet the threshold. This is plausibly the case since the data that was used to determine deprivation was collected before the programme was announced. Furthermore, it must be that the only thing that changes at the 50th place threshold is eligibility for treatment. The authors convincingly show that other factors do not significantly change at the threshold. For these reasons we gave the study a 4 on the SMS.

What did the evaluation find?

The study finds that LEGI increases employment in areas close to the boundary of treated areas, but does so at the expense of employment in nearby untreated areas. Essentially, the policy ‘displaces’ employment from one area to another. The idea that the policy displaces employment is further corroborated by the fact that there are no employment effects found when using areas that are further away from the boundary of the treated areas. Furthermore, results suggest that the positive employment impacts inside treated areas disappear as soon as support is discontinued. The study also finds that the policy does not significantly impact the creation of new businesses (regardless of catchment area size). The study suggests that this is likely due to the fact that in densely populated areas, business premises are already occupied to capacity. Similarly, the study concludes that the policy has no impact whatsoever on local unemployment, which suggests that any increases in employment are associated with the hiring of non-residents.

What can we learn from this?

This study suggests that policies such as LEGI may only lead to a temporary displacement of jobs. It is possible that the lack of real impact may be due to the design of LEGI which provided non-selective support to businesses that predominantly served local markets. This contrasts to the findings for selective RSA as discussed in our companion evidence sample here. The effects of LEGI on local residents may also have been different if incentives were tied to the hiring of local residents (see our comparison evidence sample on US EZs here).

Reference

Einiö, E. and Overman, H.G., 2016. The (displacement) effects of spatially targeted enterprise initiatives: evidence from UK LEGI. [Study 1315 from our Area Based Initiatives review, available here]

Other Area Based Initiatives case studies

Criscuolo, C., Martin, R., Overman, H., & Van Reenen, J. (2012). The causal effects of an industrial policy (No. w17842). National Bureau of Economic Research. [Study 1314 from our Area Based Initiatives review, discussed here]

Ham, J. C., Swenson, C., Imrohoroglu, A., & Song, H. (2011). Government programs can improve local labor markets: Evidence from state enterprise zones, federal empowerment zones and federal enterprise community. Journal of Public Economics, 95(7), 779-797. [Study 1225 from our Area Based Initiatives review, discussed here]

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