Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery

Klimek P, Poledna S, & Thurner S (2019). Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery. Nature Communications 10 (1): e1677. DOI:10.1038/s41467-019-09357-w.

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Project: Smart Resilience Indicators for Smart Critical Infrastructures (SmartResilience, H2020)

Abstract

Modern macroeconomic theories were unable to foresee the last Great Recession and could neither predict its prolonged duration nor the recovery rate. They are based on supply-demand equilibria that do not exist during recessionary shocks. Here we focus on resilience as a nonequilibrium property of networked production systems and develop a linear response theory for input-output economics. By calibrating the framework to data from 56 industrial sectors in 43 countries between 2000 and 2014, we find that the susceptibility of individual industrial sectors to economic shocks varies greatly across countries, sectors, and time. We show that susceptibility-based growth predictions that take sector- and country-specific recovery into account, outperform-by far-standard econometric models. Our results are analytically rigorous, empirically testable, and flexible enough to address policy-relevant scenarios. We illustrate the latter by estimating the impact of recently imposed tariffs on US imports (steel and aluminum) on specific sectors across European countries.

Item Type: Article
Research Programs: Advanced Systems Analysis (ASA)
Risk & Resilience (RISK)
Depositing User: Luke Kirwan
Date Deposited: 15 Apr 2019 06:44
Last Modified: 15 Apr 2019 06:49
URI: http://pure.iiasa.ac.at/15851

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