{"title":"利用混合频率动态因素模型构建高频世界经济指数","authors":"Chew Lian Chua, Sarantis Tsiaplias, Ruining Zhou","doi":"10.1002/for.3130","DOIUrl":null,"url":null,"abstract":"<p>This paper uses information at the daily, monthly, and quarterly frequencies to construct a daily World Economic Gauge (WEG). We postulate a mixed-frequency dynamic factor model to extract data observable at different frequencies in order to track the health of the global economy. We show that the WEG offers a reliable basis for tracking economic activity during key events such as COVID-19 and the Global Financial Crisis. Moreover, the WEG is shown to contain leading information about the output growth of the OECD, G7, NAFTA, European Union, and euro areas, in addition to the output growth of 42 individual countries.</p>","PeriodicalId":47835,"journal":{"name":"Journal of Forecasting","volume":"43 6","pages":"2212-2227"},"PeriodicalIF":3.4000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Constructing a high-frequency World Economic Gauge using a mixed-frequency dynamic factor model\",\"authors\":\"Chew Lian Chua, Sarantis Tsiaplias, Ruining Zhou\",\"doi\":\"10.1002/for.3130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper uses information at the daily, monthly, and quarterly frequencies to construct a daily World Economic Gauge (WEG). We postulate a mixed-frequency dynamic factor model to extract data observable at different frequencies in order to track the health of the global economy. We show that the WEG offers a reliable basis for tracking economic activity during key events such as COVID-19 and the Global Financial Crisis. Moreover, the WEG is shown to contain leading information about the output growth of the OECD, G7, NAFTA, European Union, and euro areas, in addition to the output growth of 42 individual countries.</p>\",\"PeriodicalId\":47835,\"journal\":{\"name\":\"Journal of Forecasting\",\"volume\":\"43 6\",\"pages\":\"2212-2227\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Forecasting\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/for.3130\",\"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.3130","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Constructing a high-frequency World Economic Gauge using a mixed-frequency dynamic factor model
This paper uses information at the daily, monthly, and quarterly frequencies to construct a daily World Economic Gauge (WEG). We postulate a mixed-frequency dynamic factor model to extract data observable at different frequencies in order to track the health of the global economy. We show that the WEG offers a reliable basis for tracking economic activity during key events such as COVID-19 and the Global Financial Crisis. Moreover, the WEG is shown to contain leading information about the output growth of the OECD, G7, NAFTA, European Union, and euro areas, in addition to the output growth of 42 individual countries.
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.