期刊名称：Euro Area Balance of Payments and International Investment Position Statistics
印刷版ISSN：1830-3420
电子版ISSN：1830-3439
出版年度：2021
卷号：2021
语种：English
出版社：European Central Bank
摘要：The interplay between epidemiological fundamentals of the coronavirus (COVID-19) pandemic, containment policies and the macroeconomy can be assessed by combining a macroeconomic model with an epidemiological model. ECB- BASIR [1] is an extension of the ECBBASE [2] model which addresses specific features of the COVID-19 crisis by combining a standard pandemic susceptible-infected-recovered (SIR) model with a semi-structural large-scale macroeconomic model. An SIR model – a compartmental model introduced by Kermack and McKendrick [3] – divides the population into groups and, using differential equations, predicts how a disease will spread on the basis of the number of susceptible, infected, recovered or deceased individuals. We extend that model by incorporating two additional categories: (i) quarantined individuals, and (ii) people who have been vaccinated (who are assumed to be immune to the virus). We postulate that economic behaviour will affect the transmission of the disease (with declines in consumption and work activity reducing the probability of people getting infected, for example), establishing a channel from the macroeconomic model to the epidemiological model through the sensitivity of transmission to economic interaction between people. The channel running in the opposite direction, from the epidemiological model to macroeconomic behaviour, is established by assuming that different groups of agents modelled in the epidemiological component have differing ability to work, consume and invest. For example, agents that are constrained by lockdowns can only consume part of what unconstrained agents consume, with those differences between the consumption of constrained and unconstrained agents being estimated on the basis of data for the first and second quarters of 2020. Those effects then propagate through the macroeconomic linkages in the model.
