Dynamic Firm Location Network Model with Anticipatory Scenarios for the Northeast Ohio Region

Public policy and planning decisions require glimpses into the future, to assess how the social-ecological systems we plan for might evolve with or without policy intervention. To do so, one approach gaining currency is using anticipatory tools rather than predictions. Anticipation entails generating a range of possible systems futures (scenarios), instead of attempting to predict the one that will prevail. We use here a scenario-generating model, to anticipate where in a region businesses are likely to locate in time. Using data for Northeast Ohio, including the Cleveland–Akron–Lorain– Elyria, Ohio Combined Statistical Area, we estimate the model parameters. We evaluate its prediction accuracy against 2001–2015 regional data. To illustrate how policymakers could use the model, we generate three scenarios to explore what might happen to the spatial configuration of businesses if policies were implemented to attract businesses at specific locations or discourage them from locating in parts of the region.