Recent proposals to reduce U.S. debt reveal large differences in their implied targets. These differences demonstrate the uncertainty surrounding future tax rates and long-run debt targets. We use a standard real business cycle model in which a Bayesian household learns about the state-dependent debt target in an endogenous tax rule. The household extracts the debt target state from a noisy tax process and jointly estimates the transition probabilities. We compare the household's ability to learn and the consequences of the uncertainty across different limited information sets. The information set influences the household's behavior but also impose two-sided risk. Despite the popular viewpoint that fiscal uncertainty has negative effects, limited information can result in welfare gains or losses, depending on whether the household's expectations are consistent with the realization of future states. Although the welfare distribution includes gains, we stress that the uncertainty created by the recent fiscal policy debate slowed the recovery and led to welfare losses. When Congress provides clarity about future policy, output and welfare increase and the economy quickly recovers.
D83 - Search, Learning, Information and Knowledge ; E32 - Business Fluctuations; Cycles ; E62 - Fiscal Policy; Public Expenditures, Investment, and Finance; Taxation ; H68 - Forecasts of Budgets, Deficits, and Debt