20 June 2017

Sebastian Poledna gave a talk on Economic Forecasting with an Agent-Based Model

Sebastian Poledna presented IIASA research on application of a large-scale agent-based model to economic forecasting at the seminar organized by Complexity Hub Vienna.

© ESB Professional | Shutterstock

© ESB Professional | Shutterstock

The macroeconomic agent-based model developed at IIASA models the complete national economy of Austria
with all institutional sectors (households, non-financial corporations, financial corporations, and a general
government) and is empirically calibrated to actual macro and micro data. The model simultaneously fits observed macroeconomic variables, stylized facts, and (some) observed distributions between agents on the micro-level.

Abstract

We develop an agent-based model (ABM) for the Austrian economy using data from national accounts, input-output tables, government statistics, census data, and business surveys. The model incorporates all economic activities (producing and distributive transactions) as classified by the European system of accounts (ESA). All economic entities, i.e. all juridical and natural persons, are represented by agents (at a scale of 1:10). We show that this model is able to compete with vector autoregressive (VAR) and autoregressive–moving-average (ARMA) models in out-of-sample prediction. Potential applications of this ABM include economic forecasting, as well as the prediction of responses of the economy to endogenous shocks, e.g. from the financial system, or exogenous shocks like natural disasters, transformative technological innovations, or unintended consequences of political interventions such as subsidies and tax policies.


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Last edited: 14 July 2017

CONTACT DETAILS

Sebastian Poledna

Research Scholar

Risk and Resilience

Advanced Systems Analysis

T +43(0) 2236 807 261

PUBLICATIONS

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.

Hochrainer-Stigler S & Poledna S (2016). Modelling Macroeconomic Effects of Natural Disaster Risk: A Large Scale Agent Based Modelling Approach Using Copulas. In: IDRiM 2016 7th International Conference on Integrated Disaster Risk Management Disasters and Development: Towards a Risk Aware Society, October 1-3, 2016, Isfahan, Islamic Republic of Iran.

Hochrainer-Stigler S & Poledna S (2016). Modelling Dependent Risk With Copulas: An Application On Flooding Using Agent-Based Modelling. Geoinformatics Research Papers 4 (BS4002) DOI:10.2205/2016BS01Sochi.

Systemic Risk and Network Dynamics

EEP-ASA-RISK crosscutting project

RESEARCH PARTNERS

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313