Skip to main content

Please enter a keyword and click the arrow to search the site

Learning, Parameter Drift, and the Credibility Revolution


Journal of Monetary Economics



Authors / Editors

Hennessy C A;Livdan D

Publication Year



This paper analyses extrapolation and inference using tax experiments in dynamic economies when shock processes are latent regime-shifting Markov chains. Belief revisions result in severe parameter drift: Response signs and magnitudes vary widely over time despite ideal exogeneity. Even with linear causal effects, shock responses are non-linear, preventing direct extrapolation. Analytical formulae are derived for extrapolating responses or inferring causal parameters. Extrapolation and inference hinges upon shock histories and correct assumptions regarding potential data generating processes. A martingale condition is necessary and sufficient for shock responses to directly recover comparative statics, but stochastic monotonicity is insufficient for correct sign inference.


Natural Experiment; Causality, Uncertainty, Learning

Available on ECCH


Select up to 4 programmes to compare

Select one more to compare
subscribe_image_desktop 5949B9BFE33243D782D1C7A17E3345D0

Sign up to receive our latest news and business thinking direct to your inbox


Sign up to receive our latest course information and business thinking

Leave your details above if you would like to receive emails containing the latest thought leadership, invitations to events and news about courses that could enhance your career. If you would prefer not to receive our emails, you can still access the case study by clicking the button below. You can opt-out of receiving our emails at any time by visiting: or by unsubscribing through the link provided in our emails. View our Privacy Policy for more information on your rights.