Replication data for: Competitive Learning in Yardstick Competition: Testing Models of Policy Diffusion With Performance Data

Organizations that learn from others’ successful policies not only become more competitive because their policies improve but also avoid the costs of policy innovation. While economists have widely recognized latecomer advantage, the policy diffusion literature in political science has failed to emphasize the connection between learning and competition. This article distinguishes competitive learning from learning that is not driven by competitive pressure (that is, ‘pure learning’). It models policy diffusion as a game played on social networks that govern competitive pressure and the possibilities of information transfer. The article develops an empirical test for competitive learning using spatial lags, which are applied to data on the performance of larger English local authorities from 2002 to 2006. Evidence is found for both competitive learning and pure learning. The sharper distinction between causal mechanisms proposed in this article should be widely applicable to diffusion across international boundaries and sub-national units.