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Lessons from a robust evaluation of the UK’s Eat Out to Help Out scheme

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Eat Out to Help Out had a limited effect on footfall and recruitment. Supporting businesses in any context (Covid-19, energy crisis, etc.) needs consideration of effective mechanisms for encouraging programme take-up and changing behaviour.

The Eat Out to Help Out (EOTHO) scheme was introduced to support recovery after the firstCovid-19 lockdown. It aimed to boost demand and protect jobs in the food service sector. Over 160 million meals were claimed by the end of September 2020, with government spending £849 million on the scheme. While that might be a small amount compared to the total spend on Covid-19 support, it’s still important to try to understand what impact the scheme had, and how such schemes might be better designed in the future.

Measures of footfall and recruitment suggest EOTHO had a limited effect on the economy

In recent work, my colleagues and I looked at the impact of the programme on footfall using daily mobility data from Google and on employment using daily data on job posts from Indeed UK. If EOTHO increased the demand for food services this should be reflected in higher levels of footfall in recreational activities and more jobs adverts as restaurants, pubs, and cafes hired more staff. Although employment and business survival were the ultimate objectives, we use these indirect measures due to the lack of high frequency publicly available data that allow us to understand some of the effects from the scheme.

Our approach relies on the observed spatial variation in uptake, as not all eligible businesses participated in the programme. As the map below shows, there were higher levels of participation in Scotland, Northern and South West England. However, comparing locations with different levels of take-up isn’t enough on its own, since firms opted into the scheme and thus the level of take-up of a location may depend on factors that are also directly associated with footfall and economic activity (e.g., the ability of firms to survive after lockdown measures were introduce). To deal with these concerns and improve the robustness of our approach, we exploit the fact that some restaurant chains made centralised decisions on whether to participate in EOTHO or not, independent of local conditions. In this way, the number of restaurant chains affects take-up while arguably being independent of local mobility patterns and the local labour market.

Figure 1: variation in the take-up of EOTHO across the UK

Note: The map shows the take-up rate by the end of the scheme on 31st August 2020 for every LAD in the UK. The darker the color, the higher the take-up rate. Source: Author calculations using data from HMRC’s GitHub repository.

We find that EOTHO induced 2%-5% increase in visits to retail and recreation venues than would have been expected, and this rise was concentrated on days when the discount was available (Mondays to Wednesdays in August). However, the programme failed to encourage people to go out for other purposes or to eat out after the discount ended. We also observe a temporary increase in the number of jobs adverts by 6%-8% on the Indeed jobs website in the ‘food preparation and service’ category. We do not find evidence of large increases in the number of job posts in other industries, suggesting the effect on recruitment was concentrated on food establishments.

Our analysis cannot determine whether EOTHO was good value for money, but it does shed light on some economic impacts of the scheme

The results from our evaluation cannot alone determine whether EOTHO was a good policy option. Several questions remain unanswered due to lack of comprehensive data on key outcomes:

  • We do not know if job posts resulted in individuals being hired, or if any changes in employment were permanent or temporary (although we find some suggestive evidence that more EOTHO didn’t lead to higher employment levels a month after the programme ended).
  • We also do not know if EOTHO increased turnover or the probability of firm survival.

In addition, both the footfall data (biased towards young people) and online job posts (biased towards expanding businesses) may overestimate the overall impact of EOTHO. These issues, as well as the interaction between different policies (e.g., the Coronavirus Job Retention Scheme) complicate any cost-benefit calculation of the programme. Despite this, our analysis provides evidence on some of the economic impacts and helps improving our understanding of EOTHO and similar policies. We hope that a future evaluation can directly assess the effect of EOTHO on employment, turnover and survival when the relevant data becomes available (towards the end 2023) in the Inter Departmental Business Register (IDBR) – although this would require the government to be willing to identify subsidised firms in that data.

Learning from evaluations can help with future programme design

Policies from local governments aimed at shifting people’s behaviour, as EOTHO intended, need to carefully assess whether they are appealing for businesses and implemented at the right time. Only 33% of eligible food outlets participated in EOTHO, which is less than half of what the UK government expected. This might be surprising given that the food sector had been struggling after lockdown measures were introduced. However, the low demand for the EOTHO scheme is in line with the evidence from other types of interventions such as business support programmes. As the government ponders a new set of policies to help businesses with the energy crisis, this reminds us of the importance of considering mechanisms for achieving a high take-up among businesses. This requires increasing awareness of programmes and facilitating the enrolment process.