FACTS AND ARTIFACTS - CALIBRATION AND THE EMPIRICAL-ASSESSMENT OF REAL-BUSINESS-CYCLE MODELS

Advocates of real-business-cycle models typically hold calibration methods to be superior to econometric estimation as means of quantifying the models for policy analysis. This paper finds a coherent foundation for calibration methods in Herbert Simon's Sciences of the Artificial and the methodology of idealization in the philosophy of science. Although coherent, these foundations are not fundamentally connected real-business-cycle models per se. Furthermore, adequate comparative standards have not yet been developed for calibrated models.