Forecasting the propagation of pandemic shocks with a dynamic input-output model

被引:19
作者
Pichler, Anton [1 ,2 ,3 ]
Pangallo, Marco [4 ,5 ]
Rio-Chanona, R. Maria del [1 ,2 ,3 ]
Lafond, Francois [2 ,3 ]
Farmer, J. Doyne [2 ,3 ,6 ]
机构
[1] Complex Sci Hub Vienna, A-1080 Vienna, Austria
[2] Univ Oxford, Inst New Econ Thinking, Oxford Martin Sch, Oxford OX2 6ED, England
[3] Univ Oxford, Math Inst, Oxford OX1 3LP, England
[4] Inst Econ, Pisa, Italy
[5] Santa Anna Sch Adv Studies, EMbeDS Dept, Pisa, Italy
[6] Santa Fe Inst, Santa Fe, NM USA
基金
英国经济与社会研究理事会;
关键词
COVID-19; Production network; Production function; Inventories; Out-of-equilibrium modeling; UPSTREAMNESS; DEMAND; COSTS;
D O I
10.1016/j.jedc.2022.104527
中图分类号
F [经济];
学科分类号
02 ;
摘要
We introduce a dynamic disequilibrium input-output model that was used to forecast the economics of the COVID-19 pandemic. This model was designed to understand the upstream and downstream propagation of the industry-specific demand and supply shocks caused by COVID-19, which were exceptional in their severity, suddenness and heterogene-ity across industries. The model, which was inspired in part by previous work on the response to natural disasters, includes the introduction of a new functional form for production functions, which allowed us to create bespoke production functions for each industry based on a survey of industry analysts. We also introduced new elements for modeling inventories, consumption and labor. The resulting model made accurate real-time forecasts for the decline of sectoral and aggregate economic activity in the United Kingdom in the second quarter of 2020. We examine some of the theoretical implications of our model and find that the choice of production functions and inventory levels plays a key role in the propagation of pandemic shocks. Our work demonstrates that an out of equilibrium model calibrated against national accounting data can serve as a useful real time policy evaluation and forecasting tool. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ )
引用
收藏
页数:34
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