Evidence review
What was the programme and what did it aim to do?
This study evaluates the impact of the Regional Selective Assistance (RSA) programme in the UK. The policy’s main aim was to provide support to firms in areas with low GDP and high unemployment. Over 90 per cent of the funds were spent on manufacturing firms. In order to receive these grants, firms in deprived areas presented proposals for specific projects. These proposals had to show that the investment would not occur in the absence of government intervention, and that the project would increase employment. If successful, firms received up to 35 per cent of the project’s cost. Although the UK government had discretion in establishing the overall RSA budget, EU competition laws determined which areas were eligible for support.
What’s the evaluation challenge?
Evaluating regional assistance policies such as these is difficult because areas that receive support are different to those that do not. In this case, the policy targeted the most deprived areas of the country. Furthermore, firms had to apply for support. This means that firms that chose to apply for the assistance may have been better managed than those that did not. As a result of this selection, if we compare differences in outcomes for firms in treated areas to firms in untreated 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 management) of areas and firms that receive support.
What did the evaluation do?
In order to address this issue, the study exploits a source of ‘quasi-randomness’ in the subsidy available to firms due to changes to area-based eligibility criteria set at the EU level. The maximum subsidy rate (between 0% and 35%) available to firms in a specific area depended on that area’s performance against specific indicators set at the EU level every seven years. This meant that an area may have become eligible for a subsidy (or a larger subsidy) simply because the EU changed its choice of indicators. Further, the maximum subsidy rate depended on an area’s GDP per capita compared to the EU average. This meant that the subsidy available to an area may have changed simply because new states joined the EU affecting the EU’s average GDP per capita. The study therefore identifies firms that received support simply because they are in areas that became eligible as a result of arbitrary changes to the selection process (i.e. changes that are unrelated to the area’s economic performance) and compared them to firms that did not become eligible in this way. The method that the study uses to do this is called the instrumental variables approach.
How good was the evaluation?
According to our scoring guide, the Instrumental Variables 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 management) differences between supported and non-supported areas/firms. To achieve a 4, the instrument (eligibility according to EU laws) must identify firms that received support but were not different in any other way to firms that did not receive support. This is plausibly the case since firms in areas that became eligible simply due to a change of rules were likely to be similar to firms that did not become eligible, because their change in eligibility had nothing to do with changes in performance of their area. Therefore, we scored the study a 4 on the SMS.
What did the evaluation find?
The evaluation finds that the RSA programme significantly improves areas’ economic outcomes. More specifically, a ten percentage point increase in the maximum subsidy rate available to an area decreases unemployment by 3.2 per cent. Additionally, the policy also increases the number of businesses. A 10 percentage point increase in the maximum subsidy rate increases the number of manufacturing plants by 2.2 per cent. A separate analysis of large and small firms shows that while the policy has positive impacts for small firms, there are no impacts for large firms. The authors speculate that this is likely due to the fact that larger firms can “game” the system (i.e. receive the subsidy without complying with the requirement to create jobs), but also because larger firms may not actually need the support (i.e. because they are not credit constrained and should be able to borrow for viable projects). Finally, although there are positive impacts for employment, there are no impacts on firm productivity.
What can we learn from this?
This study provides robust evidence that RSA is effective in supporting employment. The results show that providing firms with subsidies for specific projects can increase employment. However, governments may use funds more efficiently by targeting these policies towards smaller firms that are more likely to benefit. From a policy design aspect, firms were required to provide the larger part (65%) of the project’s cost themselves and to demonstrate beforehand how the project would generate employment. It is also important to note that firms were required to demonstrate that they predominantly served national or international markets, rather than local markets. This requirement should reduce displacement effects on to other non-subsidised firms serving the same local market. Overall, this policy was found to be more successful than some less selective area based policies (see, for example, our companion case study on the UK’s LEGI programme here).
Reference
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, available here.]
Other area based initiatives case studies
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, 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]
