Empirical policy functions as benchmarks for evaluation of dynamic models

We describe a set of model-dependent statistical benchmarks that can be used to estimate and evaluate dynamic models of firms' investment and financing. The benchmarks characterize the empirical counterparts of the models' policy functions. These empirical policy functions (EPFs) are intuitively related to the corresponding model, their features can be estimated very easily and robustly, and they describe economically important aspects of firms' dynamic behavior. We calculate the benchmarks for a traditional trade-off model using Compustat data and use them to estimate some of its parameters. We present two Monte Carlo exercises, one that shows EPF-based estimation has lower average bias and lower variance than traditional moment-based estimation and another that shows EPF-based tests are better at detecting misspecification.