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  1. TI=How to go viral: A COVID 19 model with endogenously time varying parameters
  2. TI=Physician experiences in management of COVID 19 associated coagulopathy in pregnancy: Communication from the ISTH SSC Subcommittee on Women s Health Issues in Thrombosis and Haemostasis

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  1. Article: How to go viral: A COVID-19 model with endogenously time-varying parameters.

    Ho, Paul / Lubik, Thomas A / Matthes, Christian

    Journal of econometrics

    2021  Volume 232, Issue 1, Page(s) 70–86

    Abstract: We estimate a panel model with endogenously time-varying parameters for COVID-19 cases and deaths ... among reported cases. The model forecasts perform well, even relative to models from epidemiology and statistics. ... that social distancing and testing have significant effects on the parameters. For example, a 10 percentage point ...

    Abstract We estimate a panel model with endogenously time-varying parameters for COVID-19 cases and deaths in U.S. states. The functional form for infections incorporates important features of epidemiological models but is flexibly parameterized to capture different trajectories of the pandemic. Daily deaths are modeled as a spike-and-slab regression on lagged cases. Our Bayesian estimation reveals that social distancing and testing have significant effects on the parameters. For example, a 10 percentage point increase in the positive test rate is associated with a 2 percentage point increase in the death rate among reported cases. The model forecasts perform well, even relative to models from epidemiology and statistics.
    Language English
    Publishing date 2021-01-15
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1460617-3
    ISSN 0304-4076
    ISSN 0304-4076
    DOI 10.1016/j.jeconom.2021.01.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: How to go viral: A COVID-19 model with endogenously time-varying parameters

    Ho, Paul / Lubik, Thomas A / Matthes, Christian

    Journal of econometrics. 2021 Jan. 07,

    2021  

    Abstract: We estimate a panel model with endogenously time-varying parameters for COVID-19 cases and deaths ... among reported cases. The model forecasts perform well, even relative to models from epidemiology and statistics. ... that social distancing and testing have significant effects on the parameters. For example, a 10 percentage point ...

    Abstract We estimate a panel model with endogenously time-varying parameters for COVID-19 cases and deaths in U.S. states. The functional form for infections incorporates important features of epidemiological models but is flexibly parameterized to capture different trajectories of the pandemic. Daily deaths are modeled as a spike-and-slab regression on lagged cases. Our Bayesian estimation reveals that social distancing and testing have significant effects on the parameters. For example, a 10 percentage point increase in the positive test rate is associated with a 2 percentage point increase in the death rate among reported cases. The model forecasts perform well, even relative to models from epidemiology and statistics.
    Keywords Bayesian theory ; Coronavirus infections ; econometrics ; models ; mortality ; pandemic ; testing ; trajectories
    Language English
    Dates of publication 2021-0107
    Publishing place Elsevier B.V.
    Document type Article
    Note NAL-light ; Pre-press version
    ZDB-ID 1460617-3
    ISSN 0304-4076
    ISSN 0304-4076
    DOI 10.1016/j.jeconom.2021.01.001
    Database NAL-Catalogue (AGRICOLA)

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