{"title":"我们应该多频繁地重新估计DSGE模型?","authors":"Marcin Kolasa, Michał Rubaszek","doi":"10.2139/ssrn.2646625","DOIUrl":null,"url":null,"abstract":"A common practice in policy making institutions using DSGE models for forecasting is to re-estimate them only occasionally rather than every forecasting round. In this paper we ask how such a practice affects the accuracy of DSGE model-based forecasts. To this end we use a canonical medium-sized New Keynesian model and compare how its quarterly real-time forecasts for the US economy vary with the interval between consecutive re-estimations. We find that updating the model parameters only once a year usually does not lead to any significant deterioration in the accuracy of point forecasts. On the other hand, there are some gains from increasing the frequency of re-estimation if one is interested in the quality of density forecasts.","PeriodicalId":308524,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"How Frequently Should We Re-Estimate DSGE Models?\",\"authors\":\"Marcin Kolasa, Michał Rubaszek\",\"doi\":\"10.2139/ssrn.2646625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A common practice in policy making institutions using DSGE models for forecasting is to re-estimate them only occasionally rather than every forecasting round. In this paper we ask how such a practice affects the accuracy of DSGE model-based forecasts. To this end we use a canonical medium-sized New Keynesian model and compare how its quarterly real-time forecasts for the US economy vary with the interval between consecutive re-estimations. We find that updating the model parameters only once a year usually does not lead to any significant deterioration in the accuracy of point forecasts. On the other hand, there are some gains from increasing the frequency of re-estimation if one is interested in the quality of density forecasts.\",\"PeriodicalId\":308524,\"journal\":{\"name\":\"ERN: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic)\",\"volume\":\"2015 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2646625\",\"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: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2646625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A common practice in policy making institutions using DSGE models for forecasting is to re-estimate them only occasionally rather than every forecasting round. In this paper we ask how such a practice affects the accuracy of DSGE model-based forecasts. To this end we use a canonical medium-sized New Keynesian model and compare how its quarterly real-time forecasts for the US economy vary with the interval between consecutive re-estimations. We find that updating the model parameters only once a year usually does not lead to any significant deterioration in the accuracy of point forecasts. On the other hand, there are some gains from increasing the frequency of re-estimation if one is interested in the quality of density forecasts.