A note on uncertainty due to infectious diseases and output growth of the United States : a mixed-frequency forecasting experiment

dc.contributor.authorSalisu, Afees A.
dc.contributor.authorGupta, Rangan
dc.contributor.authorDemirer, Riza
dc.contributor.emailrangan.gupta@up.ac.zaen_US
dc.date.accessioned2023-06-02T06:43:56Z
dc.date.available2023-06-02T06:43:56Z
dc.date.issued2022-04
dc.description.abstractUtilizing a mixed data sampling (MIDAS) approach, we show that a daily newspaper-based index of uncertainty associated with infectious diseases can be used to predict, both in- and out-of-samples, low-frequency movements of output growth for the United States (US). The predictability of monthly industrial production growth and quarterly real Gross Domestic Product (GDP) growth during the current period of heightened economic uncertainty due to the COVID-19 pandemic is likely to be of tremendous value to policymakers.en_US
dc.description.departmentEconomicsen_US
dc.description.librarianhj2023en_US
dc.description.urihttp://www.worldscientific.com/worldscinet/afeen_US
dc.identifier.citationSalisu, A.A., Gupta, R. & Demirer, R. 2022, 'A note on uncertainty due to infectious diseases and output growth of the United States: a mixed-frequency forecasting experiment', Annals of Financial Economics, vol. 17, no. 2, art. 2250009, doi : 10.1142/S2010495222500099.en_US
dc.identifier.issn2010-4952 (print)
dc.identifier.issn2010-4960 (online)
dc.identifier.other10.1142/S2010495222500099
dc.identifier.urihttp://hdl.handle.net/2263/91007
dc.language.isoenen_US
dc.publisherWorld Scientific Publishingen_US
dc.rights© 2022 World Scientific Publishing.en_US
dc.subjectMixed data sampling (MIDAS)en_US
dc.subjectUnited States (US)en_US
dc.subjectGross domestic product (GDP)en_US
dc.subjectUncertaintyen_US
dc.subjectInfectious diseases related uncertaintyen_US
dc.subjectOutput growthen_US
dc.subjectForecasten_US
dc.titleA note on uncertainty due to infectious diseases and output growth of the United States : a mixed-frequency forecasting experimenten_US
dc.typePostprint Articleen_US

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