It’s not always easy to find reliable and robust experimental research to use to learn what works in different contexts. Therefore, to encourage evidence-based policymaking, we have updated our database and included over 150 Randomised Controlled Trials (RCTs) in the field of innovation, entrepreneurship and growth. You can access the database here.
When presented with a difficult problem that you need to resolve, it’s useful to know what others have done in the same situation. That doesn’t necessarily mean you need to copy-paste their solution, but it’s useful to gain a broad understanding of what may or may not work from other contexts. Policymaking is no different.
Evidence is key for designing effective policy. But sometimes, this evidence is not always easily accessible. Alongside this, when focusing on testing particular interventions, it’s important to consider that not all evaluation methodologies are equally robust. As we explained before, RCTs are considered to be one of the best instruments to estimate causality and isolate the effect of a particular policy. That’s why they’re located at the top of the Maryland Scientific Methods Scale. This is why we think it’s so important to have a database compiling all RCTs in this field, to ensure people can access all experimental evidence out there.
We are happy to announce that we have improved our RCT database and have increased the number of papers to create a fully-fledged repository of experimental evidence in innovation, entrepreneurship and growth policy in OECD countries. We’ve also added categories to facilitate the search for different research papers by thematic area. Policymakers, researchers and practitioners can now access a pool of more than 150 RCTs at different stages (most are complete, but some are still ongoing) with a summary of the most relevant information and a link to the paper.
We have come to the conclusion that it is not only important to collate and provide free access to this information but also to summarise the information, particularly for policymakers who don’t normally have time to read several papers in detail and decide which one is the most useful for them. That is why all entries in the database include the abstract, the year and the authors. In some cases, we've also included additional information, such as the research question, sample size, unit of analysis etc. However, the biggest change that we have introduced is the “Policy Implications” section. In short, we’ve read most of the papers for you and have summarised the main takeaway in two lines.
Of course, the database does not substitute the pleasure of reading a well-written piece of research. We understand though that some papers may be complicated and too technical for non-expert viewers, and so we wanted this audience to still benefit from the knowledge contained in the paper. Our aim at IGL is to collect all existing experimental evidence in innovation, entrepreneurship and growth and disseminate this evidence across many audiences regardless of their level of expertise.
With this new and improved database, everyone can quickly get to grips with the evidence on management practices, tech adoption, social inclusion, entrepreneurship training, access to finance, etc. It is important to note that some of the existing literature is very much tailored to a particular context, and sometimes RCTs are difficult tools to generalise learnings from. For example, firms in Indonesia increased their productivity through an intervention based on the skills of their local peers, but that doesn’t necessarily mean you would find the same results in a developed economy. That is why it is so important to adapt and replicate findings. The more cases proving an intervention can work in different settings, the stronger the evidence for its potential use across countries becomes. However, as our colleague Eszter Czibor pointed out to other experimental economists, it's not only the replicability that matters but also credibility, generalisability and relevance.
If you are a researcher and have seen your paper in the database, please let us know if you’d like to make any changes. We would like to thank the LSE students who supported us on this project and made an enormous effort to map out all the research. However as this was a large task, we’re sure we’ve missed some things along the way. If you noticed that we have missed an important RCT in this field, please let us know.
We want this to be a living database and are happy to keep growing the information and evidence. We plan to include other elements that will improve the search function such as new categories and topics, but for now, feel free to navigate around our database, send us any comments, and learn more about interventions that have been successful in promoting innovation, entrepreneurship and growth.
Hugo Cuello
Hugo is the Senior Policy Analyst at the Innovation Growth Lab (IGL).
Hugo has worked since 2018 in the intersection between the Research and the Policy teams at IGL, supporting policymakers in the early stages of policy development and helping them decide where to introduce experimentation to increase the impact of entrepreneurship and business support programmes. He leads successful projects and publications to promote experimentation and supports the design, implementation and evaluation of several government programmes across OECD countries.
Before joining Nesta, Hugo was a policy evaluation advisor for the Costa Rican government. He also evaluated employment and entrepreneurship programs for the German Development Agency (GIZ) in Central America and worked with various research institutes and consultancies in Europe and Southeast Asia. He holds a BA in Political Science and a Master of Public Policy (MPP) at the Hertie School of Governance in Berlin. In 2020, he was included in the Santander-CIDOB “35 under 35 List” for his leadership in policy innovation and transformation in Europe.