This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms. These are...

This paper contributes to a recent debate about the structural and institutional conditions under which discretion may be superior to timeless perspective. We show this is unlikely when the policy maker relies on a welfare-theoretic loss function obtained as a second-order approximation of...

This paper deals with the analysis of price-setting in U.S. manufacturing industries. Recent studies have heavily criticized the ability of the New Keynesian Phillips curve (NKPC) to fit aggregate inflation [see, e.g., Rudd and Whelan, 2006, Can Rational Expectations Sticky-Price Models Explain...

This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms. These are...

In this paper we develop a general framework to analyze state space models with timevarying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...

This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms. These are...

In this paper we develop a general framework to analyze state space models with time-varying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...