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Economic recovery forecasts under impacts of COVID-19()

This paper proposes a joint model by combining the time-varying coefficient susceptible-infected-removal model with the hierarchical Bayesian vector autoregression model. This model establishes the relationship between several critical macroeconomic variables and pandemic transmission states and per...

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Detalles Bibliográficos
Autores principales: Teng, Bin, Wang, Sicong, Shi, Yufeng, Sun, Yunchuan, Wang, Wei, Hu, Wentao, Shi, Chaojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8894293/
https://www.ncbi.nlm.nih.gov/pubmed/35261424
http://dx.doi.org/10.1016/j.econmod.2022.105821
Descripción
Sumario:This paper proposes a joint model by combining the time-varying coefficient susceptible-infected-removal model with the hierarchical Bayesian vector autoregression model. This model establishes the relationship between several critical macroeconomic variables and pandemic transmission states and performs economic predictions under two predefined pandemic scenarios. The empirical part of the model predicts the economic recovery of several countries severely affected by COVID-19 (e.g., the United States and India, among others). Under the proposed pandemic scenarios, economies tend to recover rather than fall into prolonged recessions. The economy recovers faster in the scenario where the COVID-19 pandemic is controlled.