This paper considers the performance of average inflation targeting (AIT) policy when there is imperfect knowledge. There are concerns regarding robustness of AIT in a New Keynesian model with learning agents. The target steady state may not be robustly stable under adaptive learning if the...

Situations where simple and affordable testing tools are available but not accurate enough to be operationally relevant are ubiquitous. For COVID-19 detection, rapid point-of-care tests are cheap and provide results in minutes, but largely fail policymakers' accuracy requirements. We propose an...

Interest rates have fallen worldwide in recent decades, a phenomenon that has been linked at least in part to a decline in the natural rate of interest, r* (a.k.a. “r-star”). To investigate this decline, we consider a multivariate trend-cycle decomposition of real interest rates using a...

This paper gives the formulas for and derivation of ridge regression methods when there are weights associated with each observation. A Bayesian motivation is used and various choices of k are discussed. A suggestion is made as to how to combine ridge regression with robust regression methods

It is natural for humans to judge the outcome of a decision under uncertainty as a percentage of an ex-post optimal performance. We propose a robust decision-making framework based on a relative performance index. It is shown that if the decision maker's preferences satisfy quasisupermodularity,...

We extend the popular bias-based test of Stock and Yogo (2005) for instrument strength in linear instrumental variables regressions with multiple endogenous regressors to be robust to heteroskedasticity and autocorrelation. Equivalently, we extend the robust test of Montiel Olea and Pflueger...