Pub Date : 2023-11-02DOI: 10.1080/09535314.2023.2266559
Julien Lefèvre
AbstractTechnology-rich Integrated assessment models (IAMs) and Environmentally-Extended Input–Output Analysis (EEIOA) are widely employed for sustainability analysis, each offering unique strengths. IAMs focus on forward-looking scenarios, exploring technological shifts and climate change mitigation costs. EEIOA provides more comprehensive but static assessments of environmental and socio-economic impacts throughout supply chains, adopting a lifecycle perspective. I conduct a literature review to assess the current state of IAM-IO integration, paving the way for future research opportunities with advanced models. Existing studies have loosely linked IAM and IO models to improve one field or the other. This perspective highlights the potential for more advanced IAM-IO model linking and identifies three domains within sustainability scenarios research where IAM-IO integration could play a crucial role: the energy-industry nexus in decarbonization pathways, multi-dimensional sustainability impact assessment and demand-side solutions and post-growth climate mitigation scenarios. The expected research insights may be pivotal to design effective sustainable policies.KEYWORDS: Integrated Assessment ModelsInput–output analysismodel linkingsustainabilityclimate mitigation scenarios Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Including integrated assessment model, energy model, scenarios, input–output, lifecycle assessment.2 For constructing the core literature review which is focused on IO, I have only retained hybrid LCA-IO studies that include an explicit IO component. However, I have also considered some other papers more focused on LCA approaches to put IO approaches in perspective and to highlight the specific strengths of LCA methods compared to IO.
{"title":"Integrated assessment models and input–output analysis: bridging fields for advancing sustainability scenarios research","authors":"Julien Lefèvre","doi":"10.1080/09535314.2023.2266559","DOIUrl":"https://doi.org/10.1080/09535314.2023.2266559","url":null,"abstract":"AbstractTechnology-rich Integrated assessment models (IAMs) and Environmentally-Extended Input–Output Analysis (EEIOA) are widely employed for sustainability analysis, each offering unique strengths. IAMs focus on forward-looking scenarios, exploring technological shifts and climate change mitigation costs. EEIOA provides more comprehensive but static assessments of environmental and socio-economic impacts throughout supply chains, adopting a lifecycle perspective. I conduct a literature review to assess the current state of IAM-IO integration, paving the way for future research opportunities with advanced models. Existing studies have loosely linked IAM and IO models to improve one field or the other. This perspective highlights the potential for more advanced IAM-IO model linking and identifies three domains within sustainability scenarios research where IAM-IO integration could play a crucial role: the energy-industry nexus in decarbonization pathways, multi-dimensional sustainability impact assessment and demand-side solutions and post-growth climate mitigation scenarios. The expected research insights may be pivotal to design effective sustainable policies.KEYWORDS: Integrated Assessment ModelsInput–output analysismodel linkingsustainabilityclimate mitigation scenarios Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Including integrated assessment model, energy model, scenarios, input–output, lifecycle assessment.2 For constructing the core literature review which is focused on IO, I have only retained hybrid LCA-IO studies that include an explicit IO component. However, I have also considered some other papers more focused on LCA approaches to put IO approaches in perspective and to highlight the specific strengths of LCA methods compared to IO.","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135933629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-30DOI: 10.1080/09535314.2023.2272211
Nina Knittel, Max Tesselaar, W. J. Wouter Botzen, Gabriel Bachner, Timothy Tiggeloven
Anticipated increase in future river flood risk highlights the need for effective flood insurance, as it enables hedging against this risk. However, its design varies significantly across countries. This study contributes to the debate on designing flood insurance mechanisms from an economy-wide perspective, considering both socioeconomic and climate changes. We apply a multi-regional computable general equilibrium (CGE) model for 2050 and find that, under current insurance market systems, flood risk causes regional GDP losses of up to −0.5%, societal welfare losses of up to −1%, and private and public consumption losses of up to −0.5% and −2.4%, respectively. These estimates are all relative to a scenario without flood risk. Our results indicate that flood risk intensifies pressure on public budgets. We find that insurance market reforms, including a higher degree of risk-sharing, mandatory purchase requirements, and public reinsurance, can alleviate adverse welfare effects and the burden on public budgets.
{"title":"Who bears the indirect costs of flood risk? An economy-wide assessment of different insurance systems in Europe under climate change","authors":"Nina Knittel, Max Tesselaar, W. J. Wouter Botzen, Gabriel Bachner, Timothy Tiggeloven","doi":"10.1080/09535314.2023.2272211","DOIUrl":"https://doi.org/10.1080/09535314.2023.2272211","url":null,"abstract":"Anticipated increase in future river flood risk highlights the need for effective flood insurance, as it enables hedging against this risk. However, its design varies significantly across countries. This study contributes to the debate on designing flood insurance mechanisms from an economy-wide perspective, considering both socioeconomic and climate changes. We apply a multi-regional computable general equilibrium (CGE) model for 2050 and find that, under current insurance market systems, flood risk causes regional GDP losses of up to −0.5%, societal welfare losses of up to −1%, and private and public consumption losses of up to −0.5% and −2.4%, respectively. These estimates are all relative to a scenario without flood risk. Our results indicate that flood risk intensifies pressure on public budgets. We find that insurance market reforms, including a higher degree of risk-sharing, mandatory purchase requirements, and public reinsurance, can alleviate adverse welfare effects and the burden on public budgets.","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136069534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-30DOI: 10.1080/09535314.2023.2245544
Mengyu Li, Lorenz T. Keyßer, J. Kikstra, J. Hickel, P. Brockway, Nicolas Dai, Arunima Malik, M. Lenzen
Empirical evidence increasingly indicates that to achieve sufficiently rapid decarbonisation, high-income economies may need to adopt degrowth policies, scaling down less-necessary forms of production and demand, in addition to rapid deployment of renewables. Calls have been made for degrowth climate mitigation scenarios. However, so far these have not been modelled within the established Integrated Assessment Models (IAMs) for future scenario analysis of the energy-economy-emission nexus, partly because the architecture of these IAMs has growth ‘baked in’. In this work, we modify one of the common IAMs – MESSAGEix – to make it compatible with degrowth scenarios. We simulate scenarios featuring low and negative growth in a high-income economy (Australia). We achieve this by detaching MESSAGEix from its monotonically growing utility function, and by formulating an alternative utility function based on non-monotonic preferences. The outcomes from such modified scenarios reflect some characteristics of degrowth futures, including reduced aggregate production and declining energy and emissions. However, further work is needed to explore other key degrowth fea-turessuchassectoraldifferentiation,redistribution,andprovisioningsystemtransformation.
{"title":"Integrated assessment modelling of degrowth scenarios for Australia","authors":"Mengyu Li, Lorenz T. Keyßer, J. Kikstra, J. Hickel, P. Brockway, Nicolas Dai, Arunima Malik, M. Lenzen","doi":"10.1080/09535314.2023.2245544","DOIUrl":"https://doi.org/10.1080/09535314.2023.2245544","url":null,"abstract":"Empirical evidence increasingly indicates that to achieve sufficiently rapid decarbonisation, high-income economies may need to adopt degrowth policies, scaling down less-necessary forms of production and demand, in addition to rapid deployment of renewables. Calls have been made for degrowth climate mitigation scenarios. However, so far these have not been modelled within the established Integrated Assessment Models (IAMs) for future scenario analysis of the energy-economy-emission nexus, partly because the architecture of these IAMs has growth ‘baked in’. In this work, we modify one of the common IAMs – MESSAGEix – to make it compatible with degrowth scenarios. We simulate scenarios featuring low and negative growth in a high-income economy (Australia). We achieve this by detaching MESSAGEix from its monotonically growing utility function, and by formulating an alternative utility function based on non-monotonic preferences. The outcomes from such modified scenarios reflect some characteristics of degrowth futures, including reduced aggregate production and declining energy and emissions. However, further work is needed to explore other key degrowth fea-turessuchassectoraldifferentiation,redistribution,andprovisioningsystemtransformation.","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46669781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-24DOI: 10.1080/09535314.2023.2230653
Ana Norman-López, Rafael Garaffa, Krzysztof Wojtowicz, Marie Tamba
{"title":"Building a baseline to better integrate air passenger and air freight transport into a global Computable General Equilibrium (CGE) model","authors":"Ana Norman-López, Rafael Garaffa, Krzysztof Wojtowicz, Marie Tamba","doi":"10.1080/09535314.2023.2230653","DOIUrl":"https://doi.org/10.1080/09535314.2023.2230653","url":null,"abstract":"","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47330434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-13DOI: 10.1080/09535314.2023.2213394
Severin Reissl, Alessandro Caiani, F. Lamperti, Tommaso Ferraresi, L. Ghezzi
We extend the regional input-output model for the economic impact assessment of Covid-19 lockdowns in Italy proposed in Reissl et al. (2021) by incorporating the effects of changes in mobility on the level and composition of consumption demand. We estimate the model on sectoral data for 2020 and perform an out-of-sample validation exercise for the first half of 2021, finding that the model performs well. We then evaluate the relative importance of demandand supply-side factors in determining our simulation results. During the national lockdown of spring 2020 the impacts of supply-side (labor) shocks can account for the vast majority of output losses. In the following stages of the epidemic income and mobility-related effects on final demand play pivotal roles at the aggregate and regional levels, as well as for most sectors. While policies supporting demand may hence be appropriate, their effectiveness may be hampered when demand is chiefly restrained by the mobilityrelated effect, and not by income.
{"title":"A regional input-output model of the COVID-19 crisis in Italy: decomposing demand and supply factors","authors":"Severin Reissl, Alessandro Caiani, F. Lamperti, Tommaso Ferraresi, L. Ghezzi","doi":"10.1080/09535314.2023.2213394","DOIUrl":"https://doi.org/10.1080/09535314.2023.2213394","url":null,"abstract":"We extend the regional input-output model for the economic impact assessment of Covid-19 lockdowns in Italy proposed in Reissl et al. (2021) by incorporating the effects of changes in mobility on the level and composition of consumption demand. We estimate the model on sectoral data for 2020 and perform an out-of-sample validation exercise for the first half of 2021, finding that the model performs well. We then evaluate the relative importance of demandand supply-side factors in determining our simulation results. During the national lockdown of spring 2020 the impacts of supply-side (labor) shocks can account for the vast majority of output losses. In the following stages of the epidemic income and mobility-related effects on final demand play pivotal roles at the aggregate and regional levels, as well as for most sectors. While policies supporting demand may hence be appropriate, their effectiveness may be hampered when demand is chiefly restrained by the mobilityrelated effect, and not by income.","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45537214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-08DOI: 10.1080/09535314.2023.2213392
Ana-Isabel Guerra, Ferran Sancho
{"title":"An extension of the hypothetical extraction method: endogenous consumption and the armington treatment of imports","authors":"Ana-Isabel Guerra, Ferran Sancho","doi":"10.1080/09535314.2023.2213392","DOIUrl":"https://doi.org/10.1080/09535314.2023.2213392","url":null,"abstract":"","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":"1 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41709953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-30DOI: 10.1080/09535314.2023.2215909
Ran Huang, Haixin Wang
AbstractThe input-output network of an industrial chain provides a channel for risk transmission. Using Smooth-Transition Vector Autoregression model (STVAR) and Diebold-Yilmaz directional connectedness measures, we explore tail risk (extreme risk) contagion across China’s automotive industrial chain. We find significant spillover effects that are asymmetric in different phases of China’s business cycle, monetary cycle, and policy uncertainty. When China’s economy is in a recession, under a monetary expansion, or at a high level of policy uncertainty, the total risk spillover across the chain is higher. We also find apparent risk spillover from the financial services industries to the automotive industrial chain as China’s economy is in a recession or a monetary expansion period. Still, a reverse spillover is found as policy uncertainty is at a high level. Meanwhile, the direction of risk propagation across the automotive industrial chain may change with the transition in the economic state or policy uncertainty state.KEYWORDS: Tail riskinput–output linkageasymmetric contagionChina’s automotive industrial chainJEL Classifications: C34E32E42F13L62 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The data for some variables in our research, such as the manufacturing PMI index, is only available from January 2005.2 The stock index of China’s insurance industry starts from January 2007, so we set its CoVaRs between January 2005 and November 2006 constant, equaling the CoVaR of January 2007.3 We collect data on China’s manufacturing PMI, CCI, MSR, and IOR from the WIND database of China.4 The Trade Policy Uncertainty Index (based on mainland newspapers) was made by Davis et al. (Citation2019). It can be found at www.policyuncertainty.com. The Exchange Rate and Capital Account Policy Uncertainty Index (based on the full sample of 114 mainland newspapers) constructed by Huang and Luk (Citation2019) is available at http://economicpolicyuncertaintyinchina.weebly.com.9 We use two composite indicators to check whether the probability of the economy being in recession matches the recession dates in China’s economy. One is the Macroeconomic Climate Index (MCI), published by China’s National Bureau of Statistics. The other one is the Composite Leading Indicator (CLI), designed by the OECD. Based on MCI, we find 77 months are in recession, occupying about 38.9% of the time in our sample period. Based on CLI, we find 76 months in our sample period are identified as recession dates, which occupy about 38.4% of the total 198 sample months. In our results, the number of months that the transition function F(zt) of PMI or CCI is smaller than 0.5 is 74, occupying about 37.4% of the total. According to MCI and CLI, the likelihood that the economy is in a recession roughly corresponds with the recession dates in China’s economy.10 In the NBER’s convention for measuring the duration of a recession, the first month of the recessi
{"title":"Asymmetric tail risk contagion across China’s automotive industrial chain: a study based on input–output network","authors":"Ran Huang, Haixin Wang","doi":"10.1080/09535314.2023.2215909","DOIUrl":"https://doi.org/10.1080/09535314.2023.2215909","url":null,"abstract":"AbstractThe input-output network of an industrial chain provides a channel for risk transmission. Using Smooth-Transition Vector Autoregression model (STVAR) and Diebold-Yilmaz directional connectedness measures, we explore tail risk (extreme risk) contagion across China’s automotive industrial chain. We find significant spillover effects that are asymmetric in different phases of China’s business cycle, monetary cycle, and policy uncertainty. When China’s economy is in a recession, under a monetary expansion, or at a high level of policy uncertainty, the total risk spillover across the chain is higher. We also find apparent risk spillover from the financial services industries to the automotive industrial chain as China’s economy is in a recession or a monetary expansion period. Still, a reverse spillover is found as policy uncertainty is at a high level. Meanwhile, the direction of risk propagation across the automotive industrial chain may change with the transition in the economic state or policy uncertainty state.KEYWORDS: Tail riskinput–output linkageasymmetric contagionChina’s automotive industrial chainJEL Classifications: C34E32E42F13L62 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The data for some variables in our research, such as the manufacturing PMI index, is only available from January 2005.2 The stock index of China’s insurance industry starts from January 2007, so we set its CoVaRs between January 2005 and November 2006 constant, equaling the CoVaR of January 2007.3 We collect data on China’s manufacturing PMI, CCI, MSR, and IOR from the WIND database of China.4 The Trade Policy Uncertainty Index (based on mainland newspapers) was made by Davis et al. (Citation2019). It can be found at www.policyuncertainty.com. The Exchange Rate and Capital Account Policy Uncertainty Index (based on the full sample of 114 mainland newspapers) constructed by Huang and Luk (Citation2019) is available at http://economicpolicyuncertaintyinchina.weebly.com.9 We use two composite indicators to check whether the probability of the economy being in recession matches the recession dates in China’s economy. One is the Macroeconomic Climate Index (MCI), published by China’s National Bureau of Statistics. The other one is the Composite Leading Indicator (CLI), designed by the OECD. Based on MCI, we find 77 months are in recession, occupying about 38.9% of the time in our sample period. Based on CLI, we find 76 months in our sample period are identified as recession dates, which occupy about 38.4% of the total 198 sample months. In our results, the number of months that the transition function F(zt) of PMI or CCI is smaller than 0.5 is 74, occupying about 37.4% of the total. According to MCI and CLI, the likelihood that the economy is in a recession roughly corresponds with the recession dates in China’s economy.10 In the NBER’s convention for measuring the duration of a recession, the first month of the recessi","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135643409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-25DOI: 10.1080/09535314.2023.2216355
Yiyi Ju, Nur Firdaus, Tao Cao
{"title":"Industry’s role in Japan’s energy transition: soft-linking GCAM and National IO table with extended electricity supply sectors","authors":"Yiyi Ju, Nur Firdaus, Tao Cao","doi":"10.1080/09535314.2023.2216355","DOIUrl":"https://doi.org/10.1080/09535314.2023.2216355","url":null,"abstract":"","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48941372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-22DOI: 10.1080/09535314.2023.2204393
K. Kratena
{"title":"Effective demand, wages and prices, and the multiplier","authors":"K. Kratena","doi":"10.1080/09535314.2023.2204393","DOIUrl":"https://doi.org/10.1080/09535314.2023.2204393","url":null,"abstract":"","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46457669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-13DOI: 10.1080/09535314.2023.2188436
C. Socci, M. Signorelli, S. D’Andrea, S. Deriu, F. Severini
{"title":"The three plans by Biden: effects on economic growth and income inequality","authors":"C. Socci, M. Signorelli, S. D’Andrea, S. Deriu, F. Severini","doi":"10.1080/09535314.2023.2188436","DOIUrl":"https://doi.org/10.1080/09535314.2023.2188436","url":null,"abstract":"","PeriodicalId":47760,"journal":{"name":"Economic Systems Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44207066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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