{"title":"OccBin:一个解决偶尔绑定约束的动态模型的工具","authors":"L. Guerrieri, Matteo Iacoviello","doi":"10.2139/ssrn.2466637","DOIUrl":null,"url":null,"abstract":"We describe how to adapt a first-order perturbation approach and apply it in a piecewise fashion to handle occasionally binding constraints in dynamic models. Our examples include a real business cycle model with a constraint on the level of investment and a New Keynesian model subject to the zero lower bound on nominal interest rates. We compare the piecewise linear perturbation solution with a high-quality numerical solution that can be taken to be virtually exact. The piecewise linear perturbation method can adequately capture key properties of the models we consider. A key advantage of this method is its applicability to models with a large number of state variables.","PeriodicalId":123778,"journal":{"name":"ERN: Theoretical Dynamic Models (Topic)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"415","resultStr":"{\"title\":\"OccBin: A Toolkit for Solving Dynamic Models with Occasionally Binding Constraints Easily\",\"authors\":\"L. Guerrieri, Matteo Iacoviello\",\"doi\":\"10.2139/ssrn.2466637\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We describe how to adapt a first-order perturbation approach and apply it in a piecewise fashion to handle occasionally binding constraints in dynamic models. Our examples include a real business cycle model with a constraint on the level of investment and a New Keynesian model subject to the zero lower bound on nominal interest rates. We compare the piecewise linear perturbation solution with a high-quality numerical solution that can be taken to be virtually exact. The piecewise linear perturbation method can adequately capture key properties of the models we consider. A key advantage of this method is its applicability to models with a large number of state variables.\",\"PeriodicalId\":123778,\"journal\":{\"name\":\"ERN: Theoretical Dynamic Models (Topic)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"415\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Theoretical Dynamic Models (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2466637\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Theoretical Dynamic Models (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2466637","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OccBin: A Toolkit for Solving Dynamic Models with Occasionally Binding Constraints Easily
We describe how to adapt a first-order perturbation approach and apply it in a piecewise fashion to handle occasionally binding constraints in dynamic models. Our examples include a real business cycle model with a constraint on the level of investment and a New Keynesian model subject to the zero lower bound on nominal interest rates. We compare the piecewise linear perturbation solution with a high-quality numerical solution that can be taken to be virtually exact. The piecewise linear perturbation method can adequately capture key properties of the models we consider. A key advantage of this method is its applicability to models with a large number of state variables.