Although the concept of monetary policy lag has historical roots deep in the monetary economics literature, relatively little attention has been paid to the idea. In this paper, we build on Svensson's (1997) inflation targeting framework by explicitly taking into account the lagged effect of...

We show how to use optimal control theory to derive optimal time-consistent Markov-perfect government policies in nonlinear dynamic general equilibrium models, extending the result of Cohen and Michel (1988) for models with quadratic objective functions and linear dynamics. We replace private...

Given China's complex monetary policy framework, the People's Bank of China's (PBOC) monetary policy rule is difficult to infer from its observed behaviour. In this paper, we adopt a novel approach, using text analytics to estimate and interpret the unknown component in the PBOC's reaction...

How wrong could policymakers be when using linearized solutions to their macroeconomic models instead of nonlinear global solutions? This question became of much practical interest during the Great Recession and the recent zero lower bound crisis. We assess the importance of nonlinearities in a...

We model bank management actions in severe stress test conditions using a game-theoretical framework. Banks update their balance sheets to strategically maximize risk-adjusted returns to shareholders given three regulatory constraints and feedback effects related to fire sales, interactions of...

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. Using the quantum Monte Carlo (QMC) algorithm, we are the first to study whether quantum computing can improve the run time of economic applications and challenges in doing so....

The uncertainty around future changes to the Federal Reserve target rate varies over time. In our results, the main driver of uncertainty is a "path" factor signaling information about future policy actions, which is filtered from federal funds futures data. The uncertainty is highest when it...

This paper shows that changes in market participants' fear of rare events implied by crude oil options contribute to oil price volatility and oil return predictability. Using 25 years of historical data, we document economically large tail risk premia that vary substantially over time and...

We introduce the Homoscedastic Gamma [HG] model where the distribution of returns is characterized by its mean, variance and an independent skewness parameter under both measures. The model predicts that the spread between historical and risk-neutral volatilities is a function of the risk...

Most central banks effect changes to their target or policy rate in discrete increments (e.g., multiples of 0.25%) following public announcements on scheduled dates. Still, for most applications, researchers rely on the assumption that the policy rate changes linearly with economic conditions...