This paper introduces a method to study the impact of policy events on equilibrium selection in settings where strong complementarities may lead to multiple equilibria and coordination failures. 

 

Many industrial policies are rooted in coordination failures and ‘big-push’ theories, yet empirical evidence on their effectiveness remains limited since distinguishing equilibrium shifts from direct changes in fundamentals is challenging. Leveraging tools from industrial organization and algebraic geometry, I develop an approach to study the coordination effects of policy without imposing strong assumptions on the distribution or responsiveness of economic fundamentals. The method identifies the ‘types’ of factual and counterfactual equilibria before and after the policy event through a three-step procedure: model estimation and inversion, equilibrium enumeration, and type assignment. 

 

Types of factual equilibria may be used to examine how policies like urban infrastructure investment, subsidies, or trade liberalization, affect equilibrium selection. Types of counterfactual equilibria help identify the extent to which observed effects of policy are driven by fundamentals or coordination. I apply this method to study industrial zones in India. Using a newly constructed data on 4,000 industrial zones, I find that municipalities receiving a zone see a 60% increase in non-farm employment over 15 years, with significant spillovers to sectors and municipalities not targeted by the zones. 

 

Combining the type assignment methodology with event study designs, I find that industrial zones increase the probability of escaping a low-industrialization equilibrium by 38%, with coordination effects explaining roughly one-third of the observed change in outcomes.