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Michael Miess joined both IIASA’s Risk and Resilience (RISK) as well as Advanced Systems Analysis (ASA) programs as a Research Assistant in October 2016. His work at IIASA is centered on an agent-based big-data modeling approach to systemic financial risk in very large financial networks. The aim is to develop a computational methodology making it possible to quantify systemic risk from financial contracts in an entire national economy using macroeconomic data from national accounts complemented by detailed information on financial and non-financial firms from micro-level datasets.
Mr. Miess is currently engaged in writing his PhD thesis in economics at the Vienna University of Economics and Business (WU), with its main focus on a stock-flow consistent macroeconomic modeling approach depicting financial-real economic linkages, endogenous business cycles, and empirically derived model dynamics. He completed his master’s thesis in economics on computable general equilibrium (CGE) modeling for energy and environmental applications at the University of Vienna in 2012.
Mr. Miess has been a researcher at the Institute for Advanced Studies (IHS) Vienna since 2008 (currently on leave), and has been active in applied and basic research in the fields of macroeconomics, financial markets and their link to the real economy, energy and environmental economics, as well as in the coordination of a EU co-funded project on electromobility. As a Research Assistant at the Institute for Ecological Economics at the WU (2014 – 2015), he was involved in macroeconomic modeling of the links between financialization, economic growth and biophysical limits.
Last update: 12-OCT-2016
Poledna S, Hochrainer-Stigler S, Miess M, Klimek P, Schmelzer S, Sorger J, Shchekinova E, Rovenskaya E, et al. (2018). When does a disaster become a systemic event? Estimating indirect economic losses from natural disasters. arXiv preprint
Poledna S, Miess M, Schmelzer S, Rovenskaya E, Hochrainer-Stigler S, & Thurner S (2017). Agent-based Modelling of Systemic Risk: A Big-data Approach. In: IIASA Institutional Evaluation 2017, 27 February-1 March 2017, IIASA, Laxenburg, Austria.
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