dc.contributor.author | Larsen, Vegard Høghaug | |
dc.date.accessioned | 2018-04-24T08:12:43Z | |
dc.date.available | 2018-04-24T08:12:43Z | |
dc.date.issued | 2017 | |
dc.identifier.isbn | 978-82-7553-971-5 | |
dc.identifier.issn | 1502-8190 | |
dc.identifier.uri | http://hdl.handle.net/11250/2495586 | |
dc.description.abstract | Uncertainty is acknowledged to be a source of economic fluctuations. But, does the type of uncertainty matter for the economy's response to an uncertainty shock? This paper offers a novel identification strategy to disentangle different types of uncertainty. It uses machine learning techniques to classify different types of news instead of specifying a set of keywords. It is found that, depending on its source, the effects of uncertainty on macroeconomic variable may differ. I find that both good (expansionary effect) and bad (contractionary effect) types of uncertainty exist. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Norges Bank | nb_NO |
dc.relation.ispartofseries | Working Papers;5/2017 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.subject | JEL: D80 | nb_NO |
dc.subject | JEL: E32 | nb_NO |
dc.subject | JEL: E66 | nb_NO |
dc.subject | newspaper | nb_NO |
dc.subject | topic model | nb_NO |
dc.subject | uncertainty | nb_NO |
dc.subject | business cycles | nb_NO |
dc.subject | machine learning | nb_NO |
dc.title | Components of Uncertainty | nb_NO |
dc.type | Working paper | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.subject.nsi | VDP::Samfunnsvitenskap: 200::Økonomi: 210::Samfunnsøkonomi: 212 | nb_NO |
dc.source.pagenumber | 39 | nb_NO |