Optimal policy with general signal extraction

• 成果类型: Article
• 署名作者: Hauk, Esther; Lanteri, Andrea; Marcet, Albert
• 署名单位: Consejo Superior de Investigaciones Cientificas (CSIC); CSIC - Institut d'Analisi Economica (IAE); Autonomous University of Barcelona; Barcelona School of Economics; Autonomous University of Barcelona; Duke University; Center for Economic & Policy Research (CEPR); Duke University; ICREA; Pompeu Fabra University; Centre de Recerca en Economia Internacional (CREI); Barcelona School of Economics; Centre de Recerca en Economia Internacional (CREI); Pompeu Fabra University
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/j.jmoneco.2021.01.002
• 发表日期: 2021
• 页码: 54-86
• 关键词: Optimal policy; Partial information; Calculus of variations; fiscal policy

摘要

Most available results on optimal decisions under partial information are derived under separation. But this principle does not always hold. We derive a non-standard first order condition of optimality from first principles when signal extraction and optimal policy must be jointly determined. This allows us to solve a model of optimal fiscal policy where separation does not apply. Tax smoothing prevails in normal times, but taxes respond strongly in recessions. This non-linearity arises because signal extraction interacts differently with optimal policy depending on the value of the observed signals. Existing results based on the separation principle follow as special cases.