{"title":"Tractable bayesian estimation of smooth transition vector autoregressive models","authors":"Martin Bruns, Michele Piffer","doi":"10.1093/ectj/utae009","DOIUrl":null,"url":null,"abstract":"\n We develop a tractable way of estimating the parameters ruling the nonlinearity in the popular Smooth Transition VAR model, and identify structural shocks using external instruments. This jointly offers an alternative to the option of identifying shocks recursively and calibrating key parameters. In an illustration, we show that monetary policy shocks generate larger effects on economic activity during economic expansions compared to economic recessions. We then document that calibrating rather than estimating the parameters ruling the nonlinearity of the model can lead to values for which the key results are lost. This suggests caution in the calibration of these parameters.","PeriodicalId":514887,"journal":{"name":"The Econometrics Journal","volume":"27 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Econometrics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ectj/utae009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We develop a tractable way of estimating the parameters ruling the nonlinearity in the popular Smooth Transition VAR model, and identify structural shocks using external instruments. This jointly offers an alternative to the option of identifying shocks recursively and calibrating key parameters. In an illustration, we show that monetary policy shocks generate larger effects on economic activity during economic expansions compared to economic recessions. We then document that calibrating rather than estimating the parameters ruling the nonlinearity of the model can lead to values for which the key results are lost. This suggests caution in the calibration of these parameters.
我们开发了一种简便的方法来估算流行的平滑过渡 VAR 模型中的非线性参数,并利用外部工具来识别结构性冲击。与递归识别冲击和校准关键参数的方法相比,这种方法提供了另一种选择。我们举例说明,与经济衰退相比,货币政策冲击在经济扩张期间对经济活动的影响更大。然后,我们记录了校准而非估计模型非线性参数会导致关键结果丢失。这表明在校准这些参数时要谨慎。