Winston Dou, Xiang Fang, Andrew W. Lo, Harald Uhlig
{"title":"非线性动力学宏观金融模型","authors":"Winston Dou, Xiang Fang, Andrew W. Lo, Harald Uhlig","doi":"10.1146/annurev-financial-110921-112053","DOIUrl":null,"url":null,"abstract":"We review macro-finance models featuring nonlinear dynamics that have recently been developed in the literature, including models with funding liquidity constraints, market liquidity frictions, and bank run frictions, and discuss the empirical evidence and challenges of this class of models. We also construct an illustrative model featuring financial frictions and nonlinear dynamics for readers who are unfamiliar with the literature. We solve the model using different solution techniques, including both global and perturbation solution methods, and comprehensively compare the accuracy of these solutions. Within this framework, we highlight that local linearization approximations omit important nonlinear dynamics and yield biased impulse responses.","PeriodicalId":47162,"journal":{"name":"Annual Review of Financial Economics","volume":"47 11","pages":"0"},"PeriodicalIF":5.0000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Macro-Finance Models with Nonlinear Dynamics\",\"authors\":\"Winston Dou, Xiang Fang, Andrew W. Lo, Harald Uhlig\",\"doi\":\"10.1146/annurev-financial-110921-112053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We review macro-finance models featuring nonlinear dynamics that have recently been developed in the literature, including models with funding liquidity constraints, market liquidity frictions, and bank run frictions, and discuss the empirical evidence and challenges of this class of models. We also construct an illustrative model featuring financial frictions and nonlinear dynamics for readers who are unfamiliar with the literature. We solve the model using different solution techniques, including both global and perturbation solution methods, and comprehensively compare the accuracy of these solutions. Within this framework, we highlight that local linearization approximations omit important nonlinear dynamics and yield biased impulse responses.\",\"PeriodicalId\":47162,\"journal\":{\"name\":\"Annual Review of Financial Economics\",\"volume\":\"47 11\",\"pages\":\"0\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review of Financial Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-financial-110921-112053\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Financial Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1146/annurev-financial-110921-112053","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
We review macro-finance models featuring nonlinear dynamics that have recently been developed in the literature, including models with funding liquidity constraints, market liquidity frictions, and bank run frictions, and discuss the empirical evidence and challenges of this class of models. We also construct an illustrative model featuring financial frictions and nonlinear dynamics for readers who are unfamiliar with the literature. We solve the model using different solution techniques, including both global and perturbation solution methods, and comprehensively compare the accuracy of these solutions. Within this framework, we highlight that local linearization approximations omit important nonlinear dynamics and yield biased impulse responses.