JOB DESCRIPTION

This 4-year fully funded PhD position is part of the ERC Consolidator project “Systemic physical climate risk in complex adaptive economies” (SPHINX). The SPHINX-research program is made possible thanks to a 2-million-euro grant from the European Research Council.
Background:
Globally, climate change already manifests via physical risks – damages from floods, storms, wildfires, heatwaves, droughts, and sea-level rise. Concerns are rising that these risks may become systemic, when local damages to one element cannot be contained and adversely affect the entire socio-economic system. Usually, physical climate risk assessments overlay hazard probability, exposure and vulnerability. These future damage estimates linearly extrapolate historic data, assuming that markets efficiently capitalize full information about climate risks and adjust gradually, economic actors have perfect future insight, and socio-economic systems will react to and price unprecedented climate-induced hazards as they did in the past. This approach is criticized for underestimating true costs of climate change (e.g., at just 1-3% of GDP loss even under severe scenarios), impeding climate action. In contrast, analysis of systemic risks embraces complex interactions among elements/agents, adjusting expectations, mechanisms of contagion dynamics, feedbacks, and non-linear tipping. The SPHINX research program aims to fundamentally advance simulation methods and consolidate novel data to understand how systemic physical climate risks emerge in the socio-economic system, and to explore strategies to curtail their spiraling costs. The project focuses on Europe, with a detailed analysis of three selected case-study regions. Methodologically, SPHINX embraces five pillars, ranging from data collection to agent-based and computable general equilibrium modeling led by five team members. The first three pillars concern the development of computational agent-based models to explore three different channels of risk propagation. The current PhD position specifically focuses on advancing agent-based housing market models.
Job description:
The successful candidate will work within the SPHINX research team to explore interactions between households and banks in the presence of increasing climate physical risks. To explore price dynamics in climate-sensitive areas, the candidate will develop a set of agent-based housing market models supported by theory and data for a range of scales (from urban to regional). During this 4-year-long project, the PhD student will build up on the latest progress in housing market agent-based modeling (RHEA, Bank of England, etc.) and advance it by introducing adaptive price expectations of households and climate-aware policies of the financial sector (banks, insurance). Synthesizing knowledge on the socio-behavioral and economic mechanisms through which housing markets capture hazard risks and on possible cross-scale risk transfers will be essential here. This modeling effort will benefit from the behavioral data on expectations elicited via tailored household surveys (carried out by another team member) and other spatial and physical climate risk data. The goal of this agent-based modeling is to identify conditions under which risk contagion causes housing to become stranded assets and contributes to climate gentrification, with corresponding policy levers to avert these systemic failures.

JOB REQUIREMENTS

Your profile

A candidate should ideally have:

• MSc in Computational Science, Geography, Spatial Economics, Environmental Studies, or Engineering & Policy Analysis;
• knowledge of a programming language (Python, Julia, etc) and training in any of the simulation methods;
• experience with (statistical) data analysis;
• previous experience with agent-based modeling or any type of spatial modeling is beneficial;
• ability to work with spatial data/GIS is an asset;
• domain knowledge in the field of coupled social-environmental systems, climate change or global environmental change in general is an advantage;
• solid problem-solving skills and capacity to take the initiative;
• fluent written and spoken English. For more details, please check the Graduate Schools Admission Requirements: https://www.tudelft.nl/onderwijs/opleidingen/phd/admission. Dutch is not obligatory; TU Delft offers opportunities to learn the language if desired.

Please refer the Job description for details