U.S. Macroeconomic Policy Evaluation in an Open Economy Context using Wavelet Decomposed Optimal Control Methods

Arbeitspapier

It is widely recognized that the policy objectives of fiscal and monetary policymakers usually have different time horizons, and this feature may not be captured by traditional econometric techniques. In this paper, we first decompose U.S macroeconomic data using a time-frequency domain technique, namely discrete wavelet analysis. We then model the behavior of the U.S. economy over each wavelet frequency range and use our estimated parameters to construct a tracking model. To illustrate the usefulness of this approach, we simulate jointly optimal fiscal and monetary policy with different short-term targets: an inflation target, a money growth target, an interest rate target, and a real exchange rate target. The results determine the reaction in fiscal and monetary policy that is required to achieve an inflation target in a low inflation environment, and when both fiscal and monetary policy are concerned with meeting certain economic growth objectives. The combination of wavelet decomposition in an optimal control framework can also provide a new approach to macroeconomic forecasting.

Object Details

• ISBN: 978-952-323-279-2
• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Bank of Finland Research Discussion Papers ; No. 11/2019

Classification and Topics

• Classification: Wirtschaft ; Optimization Techniques; Programming Models; Dynamic Analysis ; Computational Techniques; Simulation Modeling ; Data Collection and Data Estimation Methodology; Computer Programs: Other Computer Software ; Monetary Policy ; Policy Objectives; Policy Designs and Consistency; Policy Coordination ; Macroeconomic Aspects of International Trade and Finance: Forecasting and Simulation: Models and Applications

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Crowley, Patrick M. ; Hudgins, David
• Event: Veröffentlichung
• (who): Bank of Finland
• (where): Helsinki
• (when): 2019

Further information

• Handle: http://hdl.handle.net/10419/212445
• Last update: 10.03.2025, 11:43 AM CET