An Examination of How Monetary Policy Influences Fiscal Policy in the Presence of Uncertainty
This paper investigates how monetary-policy rules and expectations formation influence the setting of fiscal policy in the presence of uncertainty. The analysis is couched in a stochastic-simulation framework wherein the monetary authority seeks to control inflation while the fiscal authority seeks to control the debt/GDP ratio. We introduce uncertainty in the form of stochastic shocks, which are interpreted as unanticipated economic developments. The stochastic shocks drive the inflation rate and the debt/GDP ratio away from their respective target levels. The monetary authority reacts by adjusting its instrument, the short-term nominal interest rate, in an effort to bring inflation back to its target over a two-year horizon. At the same time, the fiscal authority reacts by adjusting program spending and taxes to bring the debt/GDP ratio back to its desired level over a specified time horizon. Tighter debt control requires larger and more frequent discretionary changes to program spending and taxes and also results in a more pro-cyclical fiscal policy stance. The fiscal authority therefore faces a fundamental trade-off between its debt control objective and its other objectives of stabilisation and tax smoothing. We examine how this trade-off is affected by alternative monetary-policy rules and by the formation of expectations. The credibility of monetary policy plays a key role in our analysis. We explore alternative methods to model credibility as an endogenous outcome of the interaction between the monetary-policy process and the formation of inflation expectations. This includes backward- and forward-looking approaches to modelling long-term inflation expectations ("adaptive" versus "rational" expectations) as well as a simple learning algorithm based on the Kalman filter. Our analysis also considers the scope for co-ordination between monetary and fiscal policy.
Year of publication: |
1999-03-01
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Authors: | Hostland, Doug ; Matier, Chris |
Institutions: | Society for Computational Economics - SCE |
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