{"title":"美国经济衰退前的可靠数据模式","authors":"Edward E. Leamer","doi":"10.1002/for.3140","DOIUrl":null,"url":null,"abstract":"<p>This paper proposes a method of forecasting US recessions beginning with data displays that contain the last 12 quarters of seven US expansions. These end-of-expansion displays allow observers to see for themselves what is different about the last year before recessions compared with the two earlier years. Using a statistical model that treats this historical data as draws from a 12-dimensional multivariate normal distribution, the most recent data are probabilistically inserted into these images where the recent data are most like the historical data. This is a recession forecast based not on presumed patterns but on patterns revealed by the data.</p>","PeriodicalId":47835,"journal":{"name":"Journal of Forecasting","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/for.3140","citationCount":"0","resultStr":"{\"title\":\"Data patterns that reliably precede US recessions\",\"authors\":\"Edward E. Leamer\",\"doi\":\"10.1002/for.3140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper proposes a method of forecasting US recessions beginning with data displays that contain the last 12 quarters of seven US expansions. These end-of-expansion displays allow observers to see for themselves what is different about the last year before recessions compared with the two earlier years. Using a statistical model that treats this historical data as draws from a 12-dimensional multivariate normal distribution, the most recent data are probabilistically inserted into these images where the recent data are most like the historical data. This is a recession forecast based not on presumed patterns but on patterns revealed by the data.</p>\",\"PeriodicalId\":47835,\"journal\":{\"name\":\"Journal of Forecasting\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/for.3140\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Forecasting\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/for.3140\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forecasting","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/for.3140","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
This paper proposes a method of forecasting US recessions beginning with data displays that contain the last 12 quarters of seven US expansions. These end-of-expansion displays allow observers to see for themselves what is different about the last year before recessions compared with the two earlier years. Using a statistical model that treats this historical data as draws from a 12-dimensional multivariate normal distribution, the most recent data are probabilistically inserted into these images where the recent data are most like the historical data. This is a recession forecast based not on presumed patterns but on patterns revealed by the data.
期刊介绍:
The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.