• Business cycle narratives 

      Larsen, Vegard Høghaug; Thorsrud, Leif Anders (Working papers;3/2018, Working paper, 2018)
      This article quantifies the epidemiology of media narratives relevant to business cycles in the US, Japan, and Europe (euro area). We do so by first constructing daily business cycle indexes computed on the basis of the ...
    • How Do Banks’ Funding Costs Affect Interest Margins? 

      Raknerud, Arvid; Vatne, Bjørn Helge; Rakkestad, Ketil Johan (Working Papers;9/2011, Working paper, 2011)
      We use a dynamic factor model and a detailed panel data set with quarterly accounts data on all Norwegian banks to study the effects of banks’ funding costs on their retail rates. Banks’ funds are categorized into two ...
    • Monitoring multicountry macroeconomic risk 

      Korobilis, Dimitris; Schröder, Maximilian (Working paper;9/2023, Working paper, 2023)
      We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence ...
    • Nowcasting Using News Topics. Big Data Versus Big Bank 

      Thorsrud, Leif Anders (Working Papers;20/2016, Working paper, 2016)
      The agents in the economy use a plethora of high frequency information, including news media, to guide their actions and thereby shape aggregate economic fluctuations. Traditional nowcasting approches have to a relatively ...
    • The Relation Between Banks' Funding Costs, Retail Rates and Loan Volumes: An Analysis of Norwegian Bank Micro Data 

      Raknerud, Arvid; Vatne, Bjørn Helge (Working Papers;17/2012, Working paper, 2012)
      We use a dynamic factor model and a detailed panel data set for six Norwegian bank groups to analyze i) how funding costs affect retail loan rates and ii) how retail rate differences between banks affect market shares. The ...
    • Words Are the New Numbers: A Newsy Coincident Index of Business Cycles 

      Thorsrud, Leif Anders (Working Papers;21/2016, Working paper, 2016)
      I construct a daily business cycle index based on quarterly GDP and textual information contained in a daily business newspaper. The newspaper data are decomposed into time series representing newspaper topics using a ...