Two papers on policy uncertainty and learning

This week’s crop had a lot of good papers, so it was difficult to choose a particular one. I chose two related papers, which both in some way address the current fiscal policy uncertainty in the United States.

The first one shows that the policy uncertainty can have a substantial impact, and one could thus consider policy uncertainty as a policy in itself. The most important channel is through expectations on capital income taxes. Reducing uncertainty on other taxes appears less crucial.

The second looks at how agents try to learn about their new environment after a fiscal policy change. The learning process itself induces swings and overshooting, which of course would be reduced with better information or more certainty.

Fiscal Volatility Shocks and Economic Activity

By Jesus Fernandez-Villaverde, Pablo Guerron-Quintana, Keith Kuester and Juan Rubio-Ramirez

We study the effects of changes in uncertainty about future fiscal policy on aggregate economic activity. Fiscal deficits and public debt have risen sharply in the wake of the financial crisis. While these developments make fisscal consolidation inevitable, there is considerable uncertainty about the policy mix and timing of such budgetary adjustment. To evaluate the consequences of this increased uncertainty, we first estimate tax and spending processes for the U.S. that allow for time-varying volatility. We then feed these processes into an otherwise standard New Keynesian business cycle model calibrated to the U.S. economy. We find that fiscal volatility shocks have an adverse effect on economic activity that is comparable to the effects of a 25-basis-point innovation in the federal funds rate.

Policy Change and Learning in the RBC Model

By Kaushik Mitra, George W. Evans and Seppo Honkapohja

What is the impact of surprise and anticipated policy changes when agents form expectations using adaptive learning rather than rational expectations? We examine this issue using the standard stochastic real business cycle model with lump-sum taxes. Agents combine knowledge about future policy with econometric forecasts of future wages and interest rates. Both permanent and temporary policy changes are analyzed. Dynamics under learning can have large impact effects and a gradual hump-shaped response, and tend to be prominently characterized by oscillations not present under rational expectations. These fluctuations reflect periods of excessive optimism or pessimism, followed by subsequent corrections.

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