{"title":"商业周期动力学:使用马尔可夫链测量的自底向上方法","authors":"Christian Müller, Eva M. Köberl","doi":"10.1787/JBCMA-2015-5JRS0LV6XS7B","DOIUrl":null,"url":null,"abstract":"Business cycle dynamics can be seen as footprints left by individual decision makers. Tracing those footprints we offer a novel, largely model independent and exogenous measure of the business cycle dynamics. This measure also, allows for distinguishing positive and negative shocks without prior estimation. Utilizing more than twentythousand observations of firms surveyed quarterly in the periods (1999-2006), we employ a Markov-chain approach combined with conventional time series econometrics for gauging the dynamics of business cycles. Since we start the analysis with firm level data we label our method the “bottom-up approach”.","PeriodicalId":313514,"journal":{"name":"Oecd Journal: Journal of Business Cycle Measurement and Analysis","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Business cycle dynamics: A bottom-up approach with Markov-chain measurement\",\"authors\":\"Christian Müller, Eva M. Köberl\",\"doi\":\"10.1787/JBCMA-2015-5JRS0LV6XS7B\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Business cycle dynamics can be seen as footprints left by individual decision makers. Tracing those footprints we offer a novel, largely model independent and exogenous measure of the business cycle dynamics. This measure also, allows for distinguishing positive and negative shocks without prior estimation. Utilizing more than twentythousand observations of firms surveyed quarterly in the periods (1999-2006), we employ a Markov-chain approach combined with conventional time series econometrics for gauging the dynamics of business cycles. Since we start the analysis with firm level data we label our method the “bottom-up approach”.\",\"PeriodicalId\":313514,\"journal\":{\"name\":\"Oecd Journal: Journal of Business Cycle Measurement and Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"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-2015-5JRS0LV6XS7B\",\"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-2015-5JRS0LV6XS7B","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Business cycle dynamics: A bottom-up approach with Markov-chain measurement
Business cycle dynamics can be seen as footprints left by individual decision makers. Tracing those footprints we offer a novel, largely model independent and exogenous measure of the business cycle dynamics. This measure also, allows for distinguishing positive and negative shocks without prior estimation. Utilizing more than twentythousand observations of firms surveyed quarterly in the periods (1999-2006), we employ a Markov-chain approach combined with conventional time series econometrics for gauging the dynamics of business cycles. Since we start the analysis with firm level data we label our method the “bottom-up approach”.