PhD Position on Firms Expectations & Systemic Risk in Climate-Prone Regional Economies

PhD Position on Firms Expectations & Systemic Risk in Climate-Prone Regional Economies

Join our ERC SPHINX Team to model how climate risks cascade through regional economies. Help uncover when businesses shift investment due to climate risks. Help shaping climate resilient policies!

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 climate-economy modeling.

Job description:

The successful candidate will work within the SPHINX research team to explore interactions between businesses in a regional economy exposed to climate physical risks. To explore regional economic performance in climate-sensitive areas, the candidate will develop a set of regional agent-based models supported by theory and data. During this 4-year-long project, the PhD student will build up on the latest progress in climate economy agent-based modeling (CRAB, EMERGO, etc.) and extend it further by introducing adaptive expectations of firms regarding investments and pricing under increasing physical climate risks in connected supply chain networks. Feedbacks between firms’ decisions, governmental and financial sector actors, and households is important here. It will be essential to synthesize knowledge on mechanisms driving business decisions in the context of climate-induced risks, differentiating between amplifying and attenuating feedbacks relevant for firms and economic development/decline of regions. This modeling effort will benefit from the behavioral data on expectations elicited via tailored business surveys (carried out by another team member) and other climate risk and firms adaptation investment data. The goal of this agent-based modeling is to identify conditions under which risk contagion causes bankruptcies, disorderly disinvestments or relocation of businesses, potentially amplifying local downturns in specific economic sectors/regions to systemic economy-wide risk. Diverse risk-attenuating interventions will also be explored within this PhD project.

Job requirements

Your profile:

• Master’s degree 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;
• interest in economics / finance 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. Dutch is not obligatory; TU Delft offers opportunities to learn the language, if desired.

TU Delft

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Technology, Policy and Management

The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2901 per month in the first year to € 3707 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Additional information
If you would like more information about this vacancy or the selection procedure, please contact Prof Dr. T.Filatova, via t.filatova@tudelft.nl.