Search Results
Working Paper
Monetary Policy, Uncertainty, and Communications
We review the design and communication of monetary policy strategies that take into account risks and uncertainty. A key element in a robust monetary strategy is the concept of risk management, which is the weighing of key risks when setting policy. When risks to the outlook are balanced, the baseline outlook may be sufficient to guide policy decisions. However, risk-management considerations become important when risks are asymmetric. We discuss how robust simple interest rate rules and optimal control policy can incorporate risk-management considerations into the design of a monetary ...
Working Paper
Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach
Vector autoregressions with Markov-switching parameters (MS-VARs) offer dramatically better data fit than their constant-parameter predecessors. However, computational complications, as well as negative results about the importance of switching in parameters other than shock variances, have caused MS-VARs to see only sparse usage. For our first contribution, we document the effectiveness of Sequential Monte Carlo (SMC) algorithms at estimating MSVAR posteriors. Relative to multi-step, model-specific MCMC routines, SMC has the advantages of being simpler to implement, readily parallelizable, ...
Working Paper
Discussion of "Dynamic Causal Effects in a Nonlinear World: the Good, the Bad, and the Ugly''
This comment discusses Kolesár and Plagborg-Møller's (2025) finding that the standard linear local projection (LP) estimator recovers the average marginal effect (AME) even in nonlinear settings. We apply and discuss a subset their results using a simple nonlinear time series model, emphasizing the role of the weighting function and the impact of nonlinearities on small-sample properties.
Working Paper
Monetary Policy, Uncertainty, and Communications
We review the design and communication of monetary policy strategies that take into account risks and uncertainty. A key element in a robust monetary strategy is the concept of risk management, which is the weighing of key risks when setting policy. When risks to the outlook are balanced, the baseline outlook may be sufficient to guide policy decisions. However, risk-management considerations become important when risks are asymmetric. We discuss how robust simple interest rate rules and optimal control policy can incorporate risk-management considerations into the design of a monetary ...
Working Paper
Alternative Scenarios at the Federal Reserve from 1968 to 2020: Data, Interpretation, and Evaluation
We comprehensively document 1,265 Federal Reserve staff alternative scenarios presented to the Federal Open Market Committee in publicly released materials from 1968 to 2020. Scenarios grew in frequency and sophistication, typically spanning a range of outcomes around the baseline. We construct a taxonomy with six categories: aggregate demand, aggregate supply, external risks, financial conditions, fiscal policy, and expectation shifts. Staff qualitative risk assessments complemented the scenario composition. Comparing scenario forecasts to realized outcomes, the most accurate scenarios often ...
Working Paper
Inflation Uncertainty and Endogenous Planning Horizons
We develop a finite-horizon planning model in which firms choose how far ahead to plan when setting prices. Planning further ahead improves a firm's pricing decision but requires cognitive effort. We derive analytical solutions for a firm's chosen planning horizon and show that large and persistent aggregate demand or supply disturbances induce firms to plan further ahead, making inflation more sensitive to shocks and generating endogenous movements in inflation uncertainty. Quantitatively, we show that the model matches the positive relationship between the size of inflation forecast ...
Working Paper
Optimal Pooling in Taylor Rule Estimation with Multiple-Horizon Forecast Panels
Multiple-horizon forecast panels are increasingly used to infer perceived monetary policy rules, but inference depends on how coefficients are pooled across forecasters, dates, and horizons. We treat this pooling structure as the object of inference. In a participant-date-horizon Taylor-rule regression model, we compare pooling patterns using Bayesian marginal likelihoods, applying the framework to the Blue Chip Financial Forecasts, Survey of Professional Forecasters, and the Summary of Economic Projections. The preferred specifications place much of the systematic variation in policy-rate ...
Working Paper
Forward Guidance with Bayesian Learning and Estimation
Considerable attention has been devoted to evaluating the macroeconomic effectiveness of the Federal Reserve's communications about future policy rates (forward guidance) in light of the U.S. economy's long spell at the zero lower bound (ZLB). In this paper, we study whether forward guidance represented a shift in the systematic description of monetary policy by estimating a New Keynesian model using Bayesian techniques. In doing so, we take into account the uncertainty that agents have about policy regimes using an incomplete information setup in which they update their beliefs using Bayes ...
Working Paper
Evaluating DSGE model forecasts of comovements
This paper develops and applies tools to assess multivariate aspects of Bayesian Dynamic Stochastic General Equilibrium (DSGE) model forecasts and their ability to predict comovements among key macroeconomic variables. We construct posterior predictive checks to evaluate conditional and unconditional density forecasts, in addition to checks for root-mean-squared errors and event probabilities associated with these forecasts. The checks are implemented on a three-equation DSGE model as well as the Smets and Wouters (2007) model using real-time data. We find that the additional features ...
Working Paper
Monetary Policy, Real Activity, and Credit Spreads : Evidence from Bayesian Proxy SVARs
This paper studies the interaction between monetary policy, financial markets, and the real economy. We develop a Bayesian framework to estimate proxy structural vector autoregressions (SVARs) in which monetary policy shocks are identified by exploiting the information contained in high frequency data. For the Great Moderation period, we find that monetary policy shocks are key drivers of fluctuations in industrial output and corporate credit spreads, explaining about 20 percent of the volatility of these variables. Central to this result is a systematic component of monetary policy ...