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Working Paper
Retail Central Bank Digital Currencies: Implications for Banking and Financial Stability
This paper reviews the literature examining how the introduction of a retail CBDC would affect the banking sector and financial stability. A CBDC has the potential to improve welfare by reducing financial frictions, countering market power in deposit markets and enhancing the payment system. However, a CBDC also entails noteworthy risks, including the possibility of bank disintermediation and associated contraction in bank credit, as well as potential adverse effects on financial stability. The recycling of the new CBDC liability through asset purchases or lending by the central bank plays ...
Working Paper
Robust monetary policy with misspecified models: does model uncertainty always call for attenuated policy?
This paper explores Knightian model uncertainty as a possible explanation of the considerable difference between estimated interest rate rules and optimal feedback descriptions of monetary policy. We focus on two types of uncertainty: (i) unstructured model uncertainty reflected in additive shock error processes that result from omitted-variable misspecifications, and (ii) structured model uncertainty, where one or more parameters are identified as the source of misspecification. For an estimated forward-looking model of the U.S. economy, we find that rules that are robust against ...
Working Paper
Avoiding Nash Inflation : Bayesian and Robust Responses to Model Uncertainty
We examine learning, model misspecification, and robust policy responses to misspecification in a quasi-real-time environment. The laboratory for the analysis is the Sargent (1999) explanation for the origins of inflation in the 1970s and the subsequent disinflation. Three robust policy rules are derived that differ according to the extent that misspecification is taken as a parametric phenomenon. These responses to drifting estimated parameters and apparent misspecification are compared to the certainty-equivalent case studied by Sargent. We find gains from utilizing robust approaches to ...
Working Paper
The Macroeconomic Implications of CBDC: A Review of the Literature
This paper provides an overview of the literature examining how the introduction of a CBDC would affect the banking sector, financial stability, and the implementation and transmission of monetary policy in a developed economy such as the United States. A CBDC has the potential to improve welfare by reducing financial frictions in deposit markets, by boosting financial inclusion, and by improving the transmission of monetary policy. However, a CBDC also entails noteworthy risks, including the possibility of bank disintermediation and associated contraction in bank credit, as well as potential ...
Working Paper
Optimal control of large, forward-looking models efficient solutions and two examples
An optimal control tool is described that is particularly useful for computing rules of large-scale models where users might otherwise have difficulty determining the state vector a priori and where the inversion of large, sparse matrices is involved. A small-scale demonstration is presented, as are data on performance with the Board of Governors large-scale rational expectations macroeconometric model, FRB/US.
Working Paper
Some Implications of Uncertainty and Misperception for Monetary Policy
When choosing a strategy for monetary policy, policymakers must grapple with mismeasurement of labor market slack, and of the responsiveness of price inflation to that slack. Using stochastic simulations of a small-scale version of the Federal Reserve Board?s principal New Keynesian macroeconomic model, we evaluate representative rule-based policy strategies, paying particular attention to how those strategies interact with initial conditions in the U.S. as they are seen today and with the current outlook. To do this, we construct a current relevant baseline forecast, one that is loosely ...
Working Paper
Real-time model uncertainty in the United States: the Fed from 1996-2003
We study 30 vintages of FRB/US, the principal macro model used by the Federal Reserve Board staff for forecasting and policy analysis. To do this, we exploit archives of the model code, coefficients, baseline databases and stochastic shock sets stored after each FOMC meeting from the model's inception in July 1996 until November 2003. The period of study was one of important changes in the U.S. economy with a productivity boom, a stock market boom and bust, a recession, the Asia crisis, the Russian debt default, and an abrupt change in fiscal policy. We document the surprisingly large and ...
Working Paper
Robustifying learnability
In recent years, the learnability of rational expectations equilibria (REE) and determinacy of economic structures have rightfully joined the usual performance criteria among the sought-after goals of policy design. Some contributions to the literature, including Bullard and Mitra (2001) and Evans and Honkapohja (2002), have made significant headway in establishing certain features of monetary policy rules that facilitate learning. However a treatment of policy design for learnability in worlds where agents have potentially misspecified their learning models has yet to surface. This paper ...
Working Paper
Retail Central Bank Digital Currencies: Implications for Banking and Financial Stability
This paper reviews the literature examining how the introduction of a retail CBDC would affect the banking sector and financial stability. A CBDC has the potential to improve welfare by reducing financial frictions, countering market power in deposit markets and enhancing the payment system. However, a CBDC also entails noteworthy risks, including the possibility of bank disintermediation and associated contraction in bank credit, as well as potential adverse effects on financial stability. The recycling of the new CBDC liability through asset purchases or lending by the central bank plays ...
Working Paper
Simplicity versus optimality the choice of monetary policy rules when agents must learn
The monetary policy rules that are widely discussed--notably the Taylor rule--are remarkable for their simplicity. One reason for the apparent preference for simple ad hoc rules over optimal rules might be the assumption of full information maintained in the computation of an optimal rule. Arguably this makes optimal control rules less robust to model specification errors. In this paper, we drop the full-information assumption and investigate the choice of policy rules when agents must learn the rule that is in use. To do this, we conduct stochastic simulations on a small, estimated ...