Economic recovery forecasts under impacts of COVID-19

Bin Teng, Sicong Wang, Yufeng Shi, Yunchuan Sun, Wei Wang, Wentao Hu and Chaojun Shi

Economic Modelling, 2022, vol. 110, issue C

Abstract: 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.

Keywords: COVID-19; Economic recovery; Bayesian vector autoregression; Time-varying coefficient SIR model (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:110:y:2022:i:c:s0264999322000670

DOI: 10.1016/j.econmod.2022.105821

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