{"title":"预测聚合时间序列变量:一项调查","authors":"H. Lütkepohl","doi":"10.1787/JBCMA-2010-5KM399R2JZ9N","DOIUrl":null,"url":null,"abstract":"Aggregated times series variables can be forecasted in different ways. For example, they may be forecasted on the basis of the aggregate series or forecasts of disaggregated variables may be obtained fi rst and then these forecasts may be aggregated. A number of forecasts are presented and compared. Classical theoretical results on the relative effi ciencies of different forecasts are reviewed and some complications are discussed which invalidate the theoretical results. Contemporaneous as well as temporal aggregation are considered. JEL classifi cation : C22, C32 Key Words : Autoregressive moving-average process, contemporaneous aggregation, temporal aggregation, vector autoregressive moving-average process","PeriodicalId":313514,"journal":{"name":"Oecd Journal: Journal of Business Cycle Measurement and Analysis","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"49","resultStr":"{\"title\":\"Forecasting Aggregated Time Series Variables: A Survey\",\"authors\":\"H. Lütkepohl\",\"doi\":\"10.1787/JBCMA-2010-5KM399R2JZ9N\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aggregated times series variables can be forecasted in different ways. For example, they may be forecasted on the basis of the aggregate series or forecasts of disaggregated variables may be obtained fi rst and then these forecasts may be aggregated. A number of forecasts are presented and compared. Classical theoretical results on the relative effi ciencies of different forecasts are reviewed and some complications are discussed which invalidate the theoretical results. Contemporaneous as well as temporal aggregation are considered. JEL classifi cation : C22, C32 Key Words : Autoregressive moving-average process, contemporaneous aggregation, temporal aggregation, vector autoregressive moving-average process\",\"PeriodicalId\":313514,\"journal\":{\"name\":\"Oecd Journal: Journal of Business Cycle Measurement and Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-02-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"49\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Oecd Journal: Journal of Business Cycle Measurement and Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1787/JBCMA-2010-5KM399R2JZ9N\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oecd Journal: Journal of Business Cycle Measurement and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1787/JBCMA-2010-5KM399R2JZ9N","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting Aggregated Time Series Variables: A Survey
Aggregated times series variables can be forecasted in different ways. For example, they may be forecasted on the basis of the aggregate series or forecasts of disaggregated variables may be obtained fi rst and then these forecasts may be aggregated. A number of forecasts are presented and compared. Classical theoretical results on the relative effi ciencies of different forecasts are reviewed and some complications are discussed which invalidate the theoretical results. Contemporaneous as well as temporal aggregation are considered. JEL classifi cation : C22, C32 Key Words : Autoregressive moving-average process, contemporaneous aggregation, temporal aggregation, vector autoregressive moving-average process