{"title":"利用报纸跟踪经济周期:德国和瑞士的比较研究","authors":"David Iselin, Boriss Siliverstovs","doi":"10.2139/ssrn.2280245","DOIUrl":null,"url":null,"abstract":"On the basis of keyword searches in newspaper articles, several versions of the Recession-Word Index (RWI) are constructed for Germany and Switzerland. We use these indices in order to track the business cycle dynamics in these two countries. Our main findings are the following. First, we show that augmenting benchmark auto-regressive models with the RWI generally leads to improvement in accuracy of one-step ahead forecasts of GDP, compared to those obtained by the benchmark model. Second, the accuracy of out-of-sample forecasts obtained with models augmented with the RWI is comparable to that of models augmented with established economic indicators in both countries; such as the Ifo Business Climate Index and the ZEW Indicator of Economic Sentiment for Germany, and the KOF Economic Barometer and the Purchasing Managers Index in manufacturing for Switzerland. Third, we show that the RWI-based forecasts are more accurate than the consensus forecasts, (published by Consensus Economics, Inc.), for Switzerland, whereas we reach the opposite conclusion for Germany. In fact, the accuracy of the consensus forecasts of GDP growth for Germany appears to be superior to that of any other indicator considered in our study. These results are robust to changes in estimation/forecast samples, the use of rolling vs.expanding estimation windows, and the inclusion of a web-based recession indicator extracted from Google Trends into a set of the competing models.","PeriodicalId":308524,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Using Newspapers for Tracking the Business Cycle: A Comparative Study for Germany and Switzerland\",\"authors\":\"David Iselin, Boriss Siliverstovs\",\"doi\":\"10.2139/ssrn.2280245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"On the basis of keyword searches in newspaper articles, several versions of the Recession-Word Index (RWI) are constructed for Germany and Switzerland. We use these indices in order to track the business cycle dynamics in these two countries. Our main findings are the following. First, we show that augmenting benchmark auto-regressive models with the RWI generally leads to improvement in accuracy of one-step ahead forecasts of GDP, compared to those obtained by the benchmark model. Second, the accuracy of out-of-sample forecasts obtained with models augmented with the RWI is comparable to that of models augmented with established economic indicators in both countries; such as the Ifo Business Climate Index and the ZEW Indicator of Economic Sentiment for Germany, and the KOF Economic Barometer and the Purchasing Managers Index in manufacturing for Switzerland. Third, we show that the RWI-based forecasts are more accurate than the consensus forecasts, (published by Consensus Economics, Inc.), for Switzerland, whereas we reach the opposite conclusion for Germany. In fact, the accuracy of the consensus forecasts of GDP growth for Germany appears to be superior to that of any other indicator considered in our study. These results are robust to changes in estimation/forecast samples, the use of rolling vs.expanding estimation windows, and the inclusion of a web-based recession indicator extracted from Google Trends into a set of the competing models.\",\"PeriodicalId\":308524,\"journal\":{\"name\":\"ERN: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic)\",\"volume\":\"146 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2280245\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2280245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Newspapers for Tracking the Business Cycle: A Comparative Study for Germany and Switzerland
On the basis of keyword searches in newspaper articles, several versions of the Recession-Word Index (RWI) are constructed for Germany and Switzerland. We use these indices in order to track the business cycle dynamics in these two countries. Our main findings are the following. First, we show that augmenting benchmark auto-regressive models with the RWI generally leads to improvement in accuracy of one-step ahead forecasts of GDP, compared to those obtained by the benchmark model. Second, the accuracy of out-of-sample forecasts obtained with models augmented with the RWI is comparable to that of models augmented with established economic indicators in both countries; such as the Ifo Business Climate Index and the ZEW Indicator of Economic Sentiment for Germany, and the KOF Economic Barometer and the Purchasing Managers Index in manufacturing for Switzerland. Third, we show that the RWI-based forecasts are more accurate than the consensus forecasts, (published by Consensus Economics, Inc.), for Switzerland, whereas we reach the opposite conclusion for Germany. In fact, the accuracy of the consensus forecasts of GDP growth for Germany appears to be superior to that of any other indicator considered in our study. These results are robust to changes in estimation/forecast samples, the use of rolling vs.expanding estimation windows, and the inclusion of a web-based recession indicator extracted from Google Trends into a set of the competing models.