Structural Estimation of Switching Options

We use structural estimation to determine the one-time costs associated with shutting down, restarting, and abandoning peak power plants in the United States. The sample period covers 2001-2009. The approach combines a nonparametric regression for capturing transitions in the exogenous state variable with a one-step nonlinear optimization for structural estimation. The data are well-suited to test the new method because the state variable is not described by any known stochastic process. Our results provide useful estimates of maintenance and switching costs for peak power plants.