{"title":"预测非洲实际GDP增长","authors":"Philip Hans Franses, Max Welz","doi":"10.3390/econometrics10010003","DOIUrl":null,"url":null,"abstract":"We propose a simple and reproducible methodology to create a single equation forecasting model (SEFM) for low-frequency macroeconomic variables. Our methodology is illustrated by forecasting annual real GDP growth rates for 52 African countries, where the data are obtained from the World Bank and start in 1960. The models include lagged growth rates of other countries, as well as a cointegration relationship to capture potential common stochastic trends. With a few selection steps, our methodology quickly arrives at a reasonably small forecasting model per country. Compared with benchmark models, the single equation forecasting models seem to perform quite well.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":"28 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting Real GDP Growth for Africa\",\"authors\":\"Philip Hans Franses, Max Welz\",\"doi\":\"10.3390/econometrics10010003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a simple and reproducible methodology to create a single equation forecasting model (SEFM) for low-frequency macroeconomic variables. Our methodology is illustrated by forecasting annual real GDP growth rates for 52 African countries, where the data are obtained from the World Bank and start in 1960. The models include lagged growth rates of other countries, as well as a cointegration relationship to capture potential common stochastic trends. With a few selection steps, our methodology quickly arrives at a reasonably small forecasting model per country. Compared with benchmark models, the single equation forecasting models seem to perform quite well.\",\"PeriodicalId\":11499,\"journal\":{\"name\":\"Econometrics\",\"volume\":\"28 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2022-01-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/econometrics10010003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/econometrics10010003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
We propose a simple and reproducible methodology to create a single equation forecasting model (SEFM) for low-frequency macroeconomic variables. Our methodology is illustrated by forecasting annual real GDP growth rates for 52 African countries, where the data are obtained from the World Bank and start in 1960. The models include lagged growth rates of other countries, as well as a cointegration relationship to capture potential common stochastic trends. With a few selection steps, our methodology quickly arrives at a reasonably small forecasting model per country. Compared with benchmark models, the single equation forecasting models seem to perform quite well.