Financial institutions, especially in Europe, hold a disproportionate amount of domestic sovereign debt. We examine the extent to which this home bias leads to capital misallocation in a real business cycle model with imperfect information and fiscal stress. We assume banks can hold sovereign debt according to a zero-risk weight policy and contrast this scenario to one in which banks weight the sovereign debt according to default probabilities. Banks are assumed to miscalculate the probability of a disaster state due to moral hazard and imperfect monitoring. This distortion pushes the economy away from the first-best allocation. We show that the zero risk weight policy exacerbates these distortions while a non-zero risk-weight improves allocations. The welfare costs associated with zero-risk weight policies are large. Households are willing to give up 3.2 percent of their consumption to move to the first-best allocation, whereas in the economy with non-zero risk-weights households are willing to give up only 1.2 percent of their consumption to move to the first-best allocation.

Fiscal foresight --the phenomenon that legislative and implementation lags ensure that private agents receive clear signals about the tax rates they face in the future --is intrinsic to the tax policy process.This paper develops an analytical framework to study the econometric implications of fiscal foresight.Simple theoretical examples show that foresight produces equilibrium time series with nonfundamental representations, which misalign the agents' and the econometrician's information sets.Economically meaningful shocks to taxes, therefore, cannot generally be extracted from statistical innovations in conventional ways.Econometric analyses that fail to align agents' and the econometrician's information sets can produce distorted inferences about the effects of tax policies.The paper documents the sensitivity of econometric inferences of tax effects to details about how tax information flows into the economy.We show that alternative assumptions about the information flows that give rise to fiscal foresight can reconcile the diverse empirical findings in the literature on anticipated tax changes.

We quantify government spending multipliers in US data using Bayesian prior and posterior analysis of a monetary model with fiscal details and two distinct monetary-fiscal policy regimes. The combination of model specification, observable data, and relatively diffuse priors for some parameters lands posterior estimates in regions of the parameter space that yield fresh perspectives on the transmission mechanisms that underlie government spending multipliers. Short-run output multipliers are comparable across regimes—posterior means around 1.3 on impact—but much larger after 10 years under passive money/active fiscal than under active money/passive fiscal—90 percent credible sets of [1.5, 1.9] versus [0.1, 0.4] in present value, when estimated from 1955 to 2016.