In this project on the Distributional Implications of Climate-related Disasters (DIoD) we study the feedback effects on macroeconomic aggregates due to changes in income distributions once a disaster has hit. We do so by introducing agent heterogeneity into two state-of-the-art disaster models already used by many researchers as well as policymakers.
The first model is a DSGE model in the real business cycle tradition where we replace the representative agent and allow for differential wealth holdings and income sources (capital and labor). Changes in the 2 distributions of wealth and income therefore affect prices, employment, and growth. The second model follows a dynamic structuralist framework. Here we focus on the demand-side responses due to disaster shocks and their effects on income distribution. While the advancement of the modeling techniques is a key part of the project, we also emphasize usefulness and applicability of the advances. Throughout the entire project, we involve end-users from policy and administration to make sure our models remain grounded in the policy domain. Ultimately, we aim for novel insights which allow governments, central banks, and multilateral development institutions to design and implement effective policies that moderate the burdens of extreme weather shocks and enable economies to achieve their sustainable development goals, while also protecting their most vulnerable members.
DIoD aims to assess the effects of shifts in the distributions of income and wealth on the macroeconomic recovery process once a disaster has occurred and provide policy-relevant recommendations. DIoD achieves this goal by introducing conceptual and methodological innovations in the modelling of disaster risks, introducing a distributional dimension into two state-of-the-art disaster models used for policy analysis. Model advancement will co-evolve with involvement of and feedback from end-users during the entire project to ensure the appropriateness and usefulness of the developed model tools. DIoD strives to answer six interconnected research questions (RQs):
RQ1: What are the distributive effects of extreme weather events?
RQ2: How do distributive effects, following an extreme weather event, impact the macroeconomic recovery process?
RQ3: How do distinct disaster response policies help to mitigate distributive effects and in turn their consequences for macroeconomic recovery processes?
RQ4: Which scientific uncertainties remain in the assessment of RQ1-RQ3 and the derived policy recommendations? How can these be quantified?
RQ5: How can the macroeconomic models for the assessment of distributional effects of disasters developed in DIoD be turned into effective tools for policy-makers and intergovernmental decision makers?
RQ6: What robust and policy-relevant lessons can be learned from modeling the impact of extreme events on income and wealth distribution?
To achieve a scientific breakthrough in the key research objectives as well as societal and policy impacts, the project develops and applies cutting-edge theoretical, empirical, and modelling analyses, while giving a central role to end-users’ involvement and the timely communication of ideas. By integrating robust quantitative and policy-relevant methodologies, the project yields data-driven results to inform how distribution and disasters interact on a macroeconomic level. In particular, the project advances the research frontier by introducing distribution and risks in the domain of growth dynamics. We hope that thereby we can promote crossfertilization between knowledge domains and disciplines that have remained disconnected so far (e.g. political economy distribution, climate economics, growth theory, and monetary models).
This project has received funding from the Jubiläumsfonds of the Austrian National Bank (OENB).
Schinko, T. , Mechler, R. , & Hochrainer-Stigler, S. (2016). A methodological framework to operationalize Climate Risk Management: Managing sovereign climate-related extreme event risk in Austria. Mitigation and Adaptation Strategies for Global Change 1-24. 10.1007/s11027-016-9713-0.
Mechler, R. & Schinko, T. (2017). Climate risk analysis for identifying the policy space for loss and damage. In: IIASA Institutional Evaluation 2017, 27 February-1 March 2017, IIASA, Laxenburg, Austria.
Scrieciu, S., Rezai, A., & Mechler, R. (2013). On the economic foundations of green growth discourses: The case of climate change mitigation and macroeconomic dynamics in economic modeling. Wiley Interdisciplinary Reviews (WIREs). Energy and Environment 2 (3) 251-268. 10.1002/wene.57.