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Instrument-Based versus Target-Based Rules

Review of Economic Studies 2022 89(1), 312-345
Abstract We study rules based on instruments versus targets. Our application is a New Keynesian economy where the central bank has non-contractible information about aggregate demand shocks and cannot commit to policy. Incentives are provided to the central bank via punishment which is socially costly. Instrument-based rules condition incentives on the central bank’s observable choice of policy, whereas target-based rules condition incentives on the outcomes of policy, such as inflation, which depend on both the policy choice and realized shocks. We show that the optimal rule within each class takes a threshold form, imposing the worst punishment upon violation. Target-based rules dominate instrument-based rules if and only if the central bank’s information is sufficiently precise, and they are relatively more attractive the less severe the central bank’s commitment problem. The optimal unconstrained rule relaxes the instrument threshold whenever the target threshold is satisfied.

Fiscal Rules and Discretion Under Limited Enforcement

Econometrica 2022 90(5), 2093-2127 open access
We study a fiscal policy model in which the government is present‐biased towards public spending. Society chooses a fiscal rule to trade off the benefit of committing the government to not overspend against the benefit of granting it flexibility to react to privately observed shocks to the value of spending. Unlike prior work, we examine rules under limited enforcement: the government has full policy discretion and can only be incentivized to comply with a rule via the use of penalties which are joint and bounded. We show that optimal incentives must be bang‐bang. Moreover, under a distributional condition, the optimal rule is a maximally enforced deficit limit, triggering the maximum feasible penalty whenever violated. Violation optimally occurs under high enough shocks if and only if available penalties are weak and such shocks are relatively unlikely. We derive comparative statics showing how rules should be calibrated to features of the environment.