Driving regional economic models with a statistical model: Hypothesis testing for economic impact analysis

Abstract

Policy models such as Input-Output (IO) or Computable General Equilibrium (CGE) are deterministic, with exogenous final demand shocks producing point estimates of local impacts. Confidence intervals around these point estimates, while desirable, are not readily available. Using the causal statistical model to form confidence intervals around the input/shock estimates allows for the configuration of confidence intervals around the output/impact results. The method is demonstrated on a sample policy scenario, which tests the relative significance of population versus climate change as a determinant of local economic activity in Rocky Mountain National Park's gateway community.