Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper investigates policy deviations from linear Taylor rules motivated by the risk management approach followed by the Fed during the Greenspan era. We estimate a nonlinear monetary policy rule via a logistic smoothing transition regression model where policy-makers' judgment, proxied by economically meaningful variables, drives the transition across policy regimes. We find that ignoring judgment‐induced nonlinearities while estimating Taylor rules has remarkable costs in terms of fit: above 250 bps in 10 quarters. Although linear Taylor rules describe well the broad contours of monetary policy, they fail to detect relevant policy decisions driven by policy‐makers' judgment.