Collaborative Research: Monetary DSGE Models at the Zero Lower Bound: Policy Analysis and Econometric Inference

合作研究：零下限的货币 DSGE 模型：政策分析和计量经济学推理

• 批准号: 1425740
• 负责人: Sadik Boragan Aruoba
• 金额: $ 22.5万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1425740&HistoricalAwards=false
• 关键词: Collaborative; Research; Monetary; DSGE; Models

This award funds research in macroeconomics, focusing on the development of tools and methods for building and testing mathematical models of an entire economy. The goal is to better understand how economies operate when nominal interest rates are very close or equal to zero; standard models use mathematical assumptions that do not work well with 0% interest. These challenges limit the ability of researchers to study the causes of business cycle fluctuations when an economy is near this interest rate. Because policymakers use some of the same modeling methods, the challenges also affect policymakers' ability to understand the possible effects of changes in monetary policy. The PIs will develop new algorithms and methods for modeling economies with 0% interest. The PIs will examine monetary policy analysis at the Zero Lower Bound (ZLB), considering the effects of forward guidance at the ZLB and characterizing the optimal target inflation rate when the ZLB is a constraint and there are also realistic frictions that generate money demand. They will consider the multiple equilibrium problem caused by impose the ZLB in many DSGE models by considering two specific equilibria, one in which inflation and inflation expectations drift slowly, and one where the change in regimes is triggered by fundamental shocks. Finally, the team will develop two kinds of nonlinear vector autoregressive models that mimic the nonlinearities in the DSGE model without imposing tight cross-coefficient restrictions.

该奖项为宏观经济学提供了资金研究，重点是开发建立和测试整个经济模型的工具和方法。目的是更好地了解当名义利率非常接近或等于零时经济的运作方式；标准模型使用数学假设，这些假设与0％的兴趣相关。这些挑战限制了研究人员研究经济接近这种利率时的商业周期波动原因的能力。由于决策者使用一些相同的建模方法，因此挑战还会影响决策者了解货币政策变化可能影响的能力。 PI将开发新的算法和方法，以建模为0％的兴趣。考虑到ZLB的远期指导的影响，PIS将在零下限（ZLB）处检查货币政策分析，并在ZLB是一个约束时表征最佳目标通货膨胀率，并且也存在造成货币需求的现实摩擦。他们将通过考虑两个特定的平衡来考虑通过在许多DSGE模型中强加ZLB引起的多个均衡问题，其中通货膨胀和通货膨胀的预期缓慢漂移，而该方案的变化是由基本冲击触发的。最后，团队将开发两种非线性矢量自回归模型，它们模仿DSGE模型中的非线性，而不会施加紧密的交叉限制。