Periodic Reporting for period 4 - SCALAR (Scaling up behavior and autonomous adaptation for macro models of climate change damage assessment)
Okres sprawozdawczy: 2022-10-01 do 2024-08-31
SCALAR aims to bridge a gap between micro and macro research traditions in climate change damage assessment by modeling behavioral aspects of private adaptation of heterogeneous agents and integrating them into macro climate policy models. The project focuses on SLR and floods, as the costliest climate-induced hazards worldwide. It adds novel contributions to the scientific understanding of feedback between the climate change adaptation (CCA) behavior of households & firms and macro-level damages. As such the project revisits the classic micro-macro aggregation problem in social sciences by means of new computational social science methods and micro-data. Specifically, SCALAR uniquely combines:
1) New behavioral data on CCA decisions collected via longitudinal cross-country household surveys, going beyond a snapshot to uncover evolving decision processes;
2) Advances in agent-based modeling (ABM) to scale up CCA decisions of heterogeneous households and firms to a regional economy while including rich behavioral, economic & spatial hazard data;
3) Cutting-edge ways of integrating micro-simulation models with traditional macro models, like Computable General Equilibrium models (CGE) to synergize the two approaches for developing new theory- and data-grounded macro damage assessments.
SCALAR integrates human behavior into macro climate policy models. It enables quantifying distributional impacts of shocks and of CCA among diverse households, firms and regions. By consolidating micro-surveys on households CCA with ABMs and macro-economic damage assessment models, SCALAR unites their strengths. Being grounded in behavioral and regional economic theories and supported by empirical CCA data, such models explore an interplay of public and private adaptations. Current macro climate policy models face limitations in informing the design of CCA policies that include adaptation across different scales, from government-led public to private CCA of households & firms. Our methods enable the quantification of cross-scale damage cascades, and the tracing of socio-economic resilience as climate change unfolds. Our methodological advancements are usable beyond the CCA domain.
The objective of SCALAR is to support the analysis of climate damages and of CCA policy by developing methods to account for behavioral aspects of private CCA by households & firms in macro-level climate policy models. Towards this end, SCALAR:
1. Synthesizes the existing empirical evidence on private CCA of households globally to identify generic patterns, and complements it with new behavioral data on private CCA in two Global North (US, NL) and two Global South (ID, CN) countries;
2. Develops innovative simulation tools to aggregate private CCA of heterogeneous individuals & firms in a regional economy;
3. Integrates micro ABM (providing solid theoretical and empirical ground for CCA and damages), with macro level climate policy models (CGE) to trace cross-scale feedback between private CCA, damages, and non-monetary socio-economic resilience.
1) New behavioral data on CCA decisions collected via longitudinal cross-country household surveys, going beyond a snapshot to uncover evolving decision processes;
2) Advances in agent-based modeling (ABM) to scale up CCA decisions of heterogeneous households and firms to a regional economy while including rich behavioral, economic & spatial hazard data;
3) Cutting-edge ways of integrating micro-simulation models with traditional macro models, like Computable General Equilibrium models (CGE) to synergize the two approaches for developing new theory- and data-grounded macro damage assessments.
SCALAR integrates human behavior into macro climate policy models. It enables quantifying distributional impacts of shocks and of CCA among diverse households, firms and regions. By consolidating micro-surveys on households CCA with ABMs and macro-economic damage assessment models, SCALAR unites their strengths. Being grounded in behavioral and regional economic theories and supported by empirical CCA data, such models explore an interplay of public and private adaptations. Current macro climate policy models face limitations in informing the design of CCA policies that include adaptation across different scales, from government-led public to private CCA of households & firms. Our methods enable the quantification of cross-scale damage cascades, and the tracing of socio-economic resilience as climate change unfolds. Our methodological advancements are usable beyond the CCA domain.
The objective of SCALAR is to support the analysis of climate damages and of CCA policy by developing methods to account for behavioral aspects of private CCA by households & firms in macro-level climate policy models. Towards this end, SCALAR:
1. Synthesizes the existing empirical evidence on private CCA of households globally to identify generic patterns, and complements it with new behavioral data on private CCA in two Global North (US, NL) and two Global South (ID, CN) countries;
2. Develops innovative simulation tools to aggregate private CCA of heterogeneous individuals & firms in a regional economy;
3. Integrates micro ABM (providing solid theoretical and empirical ground for CCA and damages), with macro level climate policy models (CGE) to trace cross-scale feedback between private CCA, damages, and non-monetary socio-economic resilience.
I. Patterns in CCA behavior
Our meta-analysis of surveys on household CCA found a Global North bias in data, and statistically significant relationships between drivers of private CCA and Hofstede cultural rankings (Noll et al., 2020). We ran 5 survey waves in 4 countries (US, NL, CN, ID), with the 5th country (UK) added in wave5. Our longitudinal surveys elicit household CCA (18 on-site actions, insurance, relocation), theory-grounded CCA drivers, self-assessed resilience, place attachment, socio-economic and damage data. Our survey analysis covers household perceptions and behavior (Noll et al., 2021; Noll et al., 2022; Noll et al., 2023). Our Nature Climate Change article was highlighted on Dutch National Television. The questionnaires & the survey data batch are Open Access: 1841 downloads(odnośnik otworzy się w nowym oknie).
II. Agent-based model
Following our review of flood ABMs (Taberna et al; 2020), we developed the Climate-economy Regional Agent-Based (CRAB) model to trace the interplay between climate shocks and agglomeration dynamics of heterogeneous firms & households (Taberna et al 2022A; Taberna et al 2022B). We linked CRAB with our surveys to analyze (i) inequality and regional impacts of household CCA along a gradient of rationality – from perfect-optimizers to empirical behavior (Taberna et al., 2023A); and (ii) synergies of public-private CCA (Taberna et al., 2023B). We analyzed firms' data on CCA investments in 137 sectors in 5 regions (Taberna et al., Under Submission).
III. Macro-economic damages & private CCA
Our team assessed indirect impacts of SLR at sector-region resolution (Cortés Arbués et al., 2024), supporting local CCA needs. The analysis raised media attention (by 57 international newspapers) and was acknowledged with the University Best Paper award. Additionally, we have analyzed trends in private firms CCA in EU27&UK, and assessed the impact of public CCA spending on these private investments (Cortés Arbués et al., Under Submission). Our results show uneven investment in CCA across economic sectors and countries, and elicit that public investments in adaptation encourage autonomous firms CCA.
IV. Coupling micro and macro
To assess the economy-wide effects of CCA behavior of households & firms and distributional flood impacts, we couple ABM (CRAB) with CGE (EU-EMS). By linking ABM (individual-NUTS2) with CGE (EU-world) we find significant differences in GDP, sectoral dynamics, and distributional impacts when compared to CGE alone. This coupling enhances the assessment of CCA policies by capturing both large-scale economic impacts and private CCA (Chatzivasileiadis et al, Under Submission). We organized a Workshop on Micro-Macro Model Integration for Climate Policy, with experts from 3 siloed communities (ABM, CGE, IAM), resulting in the PNAS Perspective (Filatova, et al, Under Review).
V. Scalability and Modularity
The ABM code was improved for efficiency, scalability, flexibility, and reusability. We set up an Open Access platform for sharing peer-reviewed reusable blocks for ABM that supports the international movement: https://www.agentblocks.org/(odnośnik otworzy się w nowym oknie)
VI. Education
Besides PhD education, 12 MSc students linked their thesis projects to the ideas, data, and models our ERC Team develops.
Our meta-analysis of surveys on household CCA found a Global North bias in data, and statistically significant relationships between drivers of private CCA and Hofstede cultural rankings (Noll et al., 2020). We ran 5 survey waves in 4 countries (US, NL, CN, ID), with the 5th country (UK) added in wave5. Our longitudinal surveys elicit household CCA (18 on-site actions, insurance, relocation), theory-grounded CCA drivers, self-assessed resilience, place attachment, socio-economic and damage data. Our survey analysis covers household perceptions and behavior (Noll et al., 2021; Noll et al., 2022; Noll et al., 2023). Our Nature Climate Change article was highlighted on Dutch National Television. The questionnaires & the survey data batch are Open Access: 1841 downloads(odnośnik otworzy się w nowym oknie).
II. Agent-based model
Following our review of flood ABMs (Taberna et al; 2020), we developed the Climate-economy Regional Agent-Based (CRAB) model to trace the interplay between climate shocks and agglomeration dynamics of heterogeneous firms & households (Taberna et al 2022A; Taberna et al 2022B). We linked CRAB with our surveys to analyze (i) inequality and regional impacts of household CCA along a gradient of rationality – from perfect-optimizers to empirical behavior (Taberna et al., 2023A); and (ii) synergies of public-private CCA (Taberna et al., 2023B). We analyzed firms' data on CCA investments in 137 sectors in 5 regions (Taberna et al., Under Submission).
III. Macro-economic damages & private CCA
Our team assessed indirect impacts of SLR at sector-region resolution (Cortés Arbués et al., 2024), supporting local CCA needs. The analysis raised media attention (by 57 international newspapers) and was acknowledged with the University Best Paper award. Additionally, we have analyzed trends in private firms CCA in EU27&UK, and assessed the impact of public CCA spending on these private investments (Cortés Arbués et al., Under Submission). Our results show uneven investment in CCA across economic sectors and countries, and elicit that public investments in adaptation encourage autonomous firms CCA.
IV. Coupling micro and macro
To assess the economy-wide effects of CCA behavior of households & firms and distributional flood impacts, we couple ABM (CRAB) with CGE (EU-EMS). By linking ABM (individual-NUTS2) with CGE (EU-world) we find significant differences in GDP, sectoral dynamics, and distributional impacts when compared to CGE alone. This coupling enhances the assessment of CCA policies by capturing both large-scale economic impacts and private CCA (Chatzivasileiadis et al, Under Submission). We organized a Workshop on Micro-Macro Model Integration for Climate Policy, with experts from 3 siloed communities (ABM, CGE, IAM), resulting in the PNAS Perspective (Filatova, et al, Under Review).
V. Scalability and Modularity
The ABM code was improved for efficiency, scalability, flexibility, and reusability. We set up an Open Access platform for sharing peer-reviewed reusable blocks for ABM that supports the international movement: https://www.agentblocks.org/(odnośnik otworzy się w nowym oknie)
VI. Education
Besides PhD education, 12 MSc students linked their thesis projects to the ideas, data, and models our ERC Team develops.
1) Collected unique microdata on household CCA (longitudinal, cross-country), with analyses delivering several novel insights. This data was featured during invited talks and at national CCA discussions with NL policymakers and the financial sector.
2) Our Open Access CRAB model is the 1st ABM to explore agglomeration, climate shocks, and adaptation nexus. Its novelty is in the endogenous migration of firms & households that generate self-reinforcing agglomeration and in quantifying CCA limits under various adaptation constraints.
3) Developed methods to quantify macroeconomic impacts of asset-level losses and private CCA of firms & households beyond the traditional approach. Our disaggregated analysis was highlighted as the article of the month and featured by 57 international media. Our methodological innovation in coupling ABM-CGE harnesses the strengths of both methods and captures macroeconomic adjustments and micro-level behaviors to inform CCA policies.
Expected results: while SCALAR has finished, two members continue in our team for the next 4 years.
2) Our Open Access CRAB model is the 1st ABM to explore agglomeration, climate shocks, and adaptation nexus. Its novelty is in the endogenous migration of firms & households that generate self-reinforcing agglomeration and in quantifying CCA limits under various adaptation constraints.
3) Developed methods to quantify macroeconomic impacts of asset-level losses and private CCA of firms & households beyond the traditional approach. Our disaggregated analysis was highlighted as the article of the month and featured by 57 international media. Our methodological innovation in coupling ABM-CGE harnesses the strengths of both methods and captures macroeconomic adjustments and micro-level behaviors to inform CCA policies.
Expected results: while SCALAR has finished, two members continue in our team for the next 4 years.