{"title":"预测国际贸易:时间序列方法","authors":"Alexander Keck, Alexander Raubold, A. Truppia","doi":"10.1787/JBCMA-2009-5KS9V44BDJ32","DOIUrl":null,"url":null,"abstract":"This paper develops a time series model to forecast the growth in imports by major advanced economies in the current and following year (two to six quarters ahead). Both pure time series analysis and structural approaches that include additional predictors based on economic theory are used. Our results compare favourably with other trade forecasts, as measured by standard evaluation statistics and can serve as a benchmark for more complex macroeconomic models.","PeriodicalId":313514,"journal":{"name":"Oecd Journal: Journal of Business Cycle Measurement and Analysis","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Forecasting international trade: A time series approach\",\"authors\":\"Alexander Keck, Alexander Raubold, A. Truppia\",\"doi\":\"10.1787/JBCMA-2009-5KS9V44BDJ32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper develops a time series model to forecast the growth in imports by major advanced economies in the current and following year (two to six quarters ahead). Both pure time series analysis and structural approaches that include additional predictors based on economic theory are used. Our results compare favourably with other trade forecasts, as measured by standard evaluation statistics and can serve as a benchmark for more complex macroeconomic models.\",\"PeriodicalId\":313514,\"journal\":{\"name\":\"Oecd Journal: Journal of Business Cycle Measurement and Analysis\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"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-2009-5KS9V44BDJ32\",\"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-2009-5KS9V44BDJ32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting international trade: A time series approach
This paper develops a time series model to forecast the growth in imports by major advanced economies in the current and following year (two to six quarters ahead). Both pure time series analysis and structural approaches that include additional predictors based on economic theory are used. Our results compare favourably with other trade forecasts, as measured by standard evaluation statistics and can serve as a benchmark for more complex macroeconomic models.