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Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery
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 n...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459978/ https://www.ncbi.nlm.nih.gov/pubmed/30975987 http://dx.doi.org/10.1038/s41467-019-09357-w |
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author | Klimek, Peter Poledna, Sebastian Thurner, Stefan |
author_facet | Klimek, Peter Poledna, Sebastian Thurner, Stefan |
author_sort | Klimek, Peter |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6459978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64599782019-04-15 Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery Klimek, Peter Poledna, Sebastian Thurner, Stefan Nat Commun Article 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. Nature Publishing Group UK 2019-04-11 /pmc/articles/PMC6459978/ /pubmed/30975987 http://dx.doi.org/10.1038/s41467-019-09357-w Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Klimek, Peter Poledna, Sebastian Thurner, Stefan Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery |
title | Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery |
title_full | Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery |
title_fullStr | Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery |
title_full_unstemmed | Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery |
title_short | Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery |
title_sort | quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459978/ https://www.ncbi.nlm.nih.gov/pubmed/30975987 http://dx.doi.org/10.1038/s41467-019-09357-w |
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