A New Keynesian model, estimated using Bayesian methods over a sample period that includes the recent episode of zero nominal interest rates, illustrates the effects of replacing the Federal Reserve's historical policy of interest rate management with one targeting money growth instead. Counterfactual simulations show that a rule for adjusting the money growth rate, modestly and gradually, in response to changes in the output gap delivers performance comparable to the estimated interest rate rule in stabilizing output and inflation. The simulations also reveal that, under the same money growth rule, the US economy would have recovered more quickly from the 2007- 09 recession, with a much shorter period of exceptionally low interest rates. These results suggest that money growth rules can serve as simple but useful guides for monetary policy and eliminate concerns about monetary policy effectiveness when the zero lower bound constraint is binding.
Jesús Fernández-Villaverde, University of Pennsylvania
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Yoosoon Chang, Indiana University Bloomington
Time-Varying Expectation Effects of Switching Financial Uncertainty
Friday, September 18, 2020
This paper investigates how regime switches in capital market conditions affect macroeconomic variables by employing a dynamic stochastic general equilibrium (DSGE) model with financial frictions derived from costly-state-verification and a risk process of switching steady-state means. Defining switches to the financial regimes as uncertainty shocks, transition probabilities between financial regimes influence entrepreneurial choices: upon an adverse shock, a bleak outlook of the capital market causes slow recovery of investment. By utilizing a latent factor method, our approach explicitly estimates time-varying transitions resulting from statistical feedbacks from past fundamental shocks to switching of financial regimes. We uncover evidence of time-varying expectations significantly affected by the feedback in the U.S. data and quantify the contribution of each fundamental shock. We also find that our uncertainty factor significantly explains the existing credit market uncertainty measures.
James Morley, University of Sydney
An empirical defence of inflation targeting and the open-economy Phillips Curve from a data-rich perspective
On Friday, September 20, 2019, Professor Morley presented the results of his two ongoing research projects related to empirical analysis of inflation. The first project evaluates inflation targeting in Australia using a factor modelling approach. The second project conducts a cross-country analysis of the open-economy Phillips Curve for a number of advanced and emerging economies (including Canada).
James Morley was appointed as Professor of Macroeconomics at the University of Sydney in 2017 and is Co-Director of the "Global Perspectives on Economic Policy" initiative for the Faculty of Arts & Social Sciences. He received his PhD from the University of Washington in 1999 and previously held positions at Washington University in St. Louis and the University of New South Wales, most recently as Associate Dean (Research) of the UNSW Business School from 2014-2017. His research focuses on the empirical analysis of business cycles, stabilization policy, and sources of persistent changes in macroeconomic and financial conditions.
He is an Academic Fellow of the Reserve Bank of New Zealand and has been a visiting scholar at various policy institutions worldwide, including the Bank of Canada, Bank Negara Malaysia, and the Bank for International Settlements. He is a former President of the Society for Nonlinear Dynamics and Econometrics and is currently Co-Editor of The Economic Record.
Regis Barnichon, Federal Reserve Bank of San Francisco
A Sufficient Statistic Approach for Optimal Monetary Policy (with G. Mesters)
Wednesday, May 15, 2019
If a monetary policy path is chosen optimally, any perturbation to that path should have no first-order effect on welfare. Drawing on this insight, we show that the impulse responses to monetary shocks are sufficient statistics to evaluate the optimality of a given policy, and we propose a “sufficient statistic targeting rule” that preserves all the benefits of targeting rules ---simplicity, transparency and immunity to time-consistency problems---, while remedying their one major limitation: non-robustness to model variations. The sufficient statistic targeting rule encompasses earlier targeting rules from the literature and generalizes the Brainard conservatism principle to a model-free setting. We test the optimality of the Fed monetary policy over the recent period, and we reject that the Fed policy was/is optimal.
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