The GTAP Data Base: Version 10

Aguiar, Angel; Chepeliev, Maksym; Corong, Erwin; McDougall, Robert; Mensbrugghe, Dominique van der

doi:10.21642/jgea.040101af

Cited by 438 publications

(328 citation statements)

References 7 publications

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“…Europe (through EUROSTAT and the FIGARO project (Eurostat, 2018a)); worldwide level e.g. WIOD (Timmer et al, 2015), EORA (Lenzen et al, 2012(Lenzen et al, , 2013, GTAP (Hertel, 1997;Aguiar et al, 2019), EXIOBASE (Tukker et al, 2013;Wood et al, 2014;Stadler et al, 2018) or TiVA (OECD, 2019). These worldwide MRIO databases are also EE-MRIO (except for TiVA) that are continuously updated and upgraded (for example the third version of EXIOBASE was released in 2018 and the tenth version of GTAP in summer 2019).…”

Section: Objectives Of This Studymentioning

confidence: 99%

No mining activities, no environmental impacts? Assessing the carbon footprint of metal requirements induced by the consumption of a country with almost no mines

Lai

Beylot

Boitier

et al. 2020

Sustainable Production and Consumption

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Section: Objectives Of This Studymentioning

confidence: 99%

No mining activities, no environmental impacts? Assessing the carbon footprint of metal requirements induced by the consumption of a country with almost no mines

Lai

Beylot

Boitier

et al. 2020

Sustainable Production and Consumption

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“…In summary, we model the short-term economic shocks of different COVID-19 response scenarios as sector-specific transportation and labour supply constraints. The model operates at weekly time-steps, using the latest available global input-output data 11 and taking into account interactions throughout complex global supply chains and the contexts of scarcity and imbalance that prevail in most markets 10,12 . It should be noted that the goal of this study is not to predict the true cost of the COVID-19 pandemic, but to identify the most important factors (e.g., the strictness and duration of lockdowns) and test the sensitivity of economic impacts to those factors as those impacts ripple through global supply chains.…”

mentioning

confidence: 99%

Global economic footprint of the COVID-19 pandemic

Guan

Wang

Hallegatte

et al. 2020

Preprint

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Countries around the world have sought to stop the spread of the 2019 novel coronavirus (COVID-19) by severely restricting travel and in-person commercial activities. Here, we analyse the economic footprint of such “lockdowns” using detailed datasets of global supply chains and a set of pandemic scenarios. We find that COVID-related economic losses are largely dependent on the number of countries imposing lockdowns, and that losses are more sensitive to the duration of a lockdown that its strictness—suggesting that more severe restrictions can reduce economic damages if they successfully shorten the duration of a lockdown. Our results also highlight several key vulnerabilities in global supply chains: Even countries that are not directly affected by COVID-19 can experience large losses (e.g., >20% of their GDP)—with such cascading impacts often occurring in low- and middle-income countries. Open and highly-specialized economies suffer particularly large losses (e.g., energy-exporting Central Asian countries or tourism-focused Caribbean countries). Supply bottlenecks and declines in consumer demand lead to especially large losses in globalized sectors such as electronics (production decreases of 13-53% across our scenarios) and automobiles (2-49%). Although retrospective analyses will undoubtedly provide further policy-relevant insights, our findings already imply that earlier, stricter, and thus shorter lockdowns are likely to minimize overall economic damages, and that global supply chains will magnify economic losses in some countries and industry sectors regardless of direct effects of the coronavirus.

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“…We use the Global Trade Analysis Project (GTAP) MRIO data to construct the EE-MRIO model because the GTAP database has relatively high resolutions of nations and comparable sectors. GTAP database has a quality control process to prioritize the usage of data sources with higher degrees of reliability 43 . The comparison studies for MRIO databases show that GTAP produces similar results with Eora 44 and WIOD 45 for the majority of regions.…”

Section: Methodsmentioning

confidence: 99%

“…The comparison studies for MRIO databases show that GTAP produces similar results with Eora 44 and WIOD 45 for the majority of regions. Meanwhile, GTAP also has a policy of placing a premium on the continuity of data suppliers 43 . This property makes it suitable for the structural decomposition analysis using two GTAP MRIO tables.…”

Section: Methodsmentioning

confidence: 99%

Saving less in China facilitates global CO2 mitigation

Lin

Liang

et al. 2020

Nat Commun

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Transforming China's economic growth pattern from investment-driven to consumptiondriven can significantly change global CO 2 emissions. This study is the first to analyse the impacts of changes in China's saving rates on global CO 2 emissions both theoretically and empirically. Here, we show that the increase in the saving rates of Chinese regions has led to increments of global industrial CO 2 emissions by 189 million tonnes (Mt) during 2007-2012. A 15-percentage-point decrease in the saving rate of China can lower global CO 2 emissions by 186 Mt, or 0.7% of global industrial CO 2 emissions. Greener consumption in China can lead to a further 14% reduction in global industrial CO 2 emissions. In particular, decreasing the saving rate of Shandong has the most massive potential for global CO 2 reductions, while that of Inner Mongolia has adverse effects. Removing economic frictions to allow the production system to fit China's increased consumption can facilitate global CO 2 mitigation.

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The GTAP Data Base: Version 10

Cited by 438 publications

References 7 publications

No mining activities, no environmental impacts? Assessing the carbon footprint of metal requirements induced by the consumption of a country with almost no mines

No mining activities, no environmental impacts? Assessing the carbon footprint of metal requirements induced by the consumption of a country with almost no mines

Global economic footprint of the COVID-19 pandemic

Saving less in China facilitates global CO2 mitigation

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