This research evaluates the causal impact of a flagship UK technology cluster programme, Tech City, which launched in East London in late 2010.
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Despite academic scepticism, cluster policies remain popular with policymakers. In theory, public policy should be able to improve cluster welfare. But clustering is an outcome of many firm and worker decisions; market and co-ordination failures are complex; and this complexity leads to policy trade-offs and blowback. The real-world scale of these challenges is an empirical question, but the empirical literature evaluating cluster policies is small. Within this, the set of robustly designed evaluations is smaller still.
This case study uses quasi-experimental methods and administrative microdata. Building on previous exploratory studies, I exploit the policy's unusual quasi-random origins to identify causal effects of the policy. I estimate these using both synthetic controls and standard difference-in-difference approaches. I test for aggregate impact on counts of firms and jobs, cluster density, and tech firm revenue productivity. I further test for timing, cross-space variation, churn, and high growth episodes. The project is partly supported by an RSA Early Career Grant.