Reconciling Information from Alternative Climate-economic Models: A Posterior Integration Approach

Shchiptsova, A., Kovalevsky, D., & Rovenskaya, E. ORCID: https://orcid.org/0000-0002-2761-3443 (2015). Reconciling Information from Alternative Climate-economic Models: A Posterior Integration Approach. In: Systems Analysis 2015 - A Conference in Celebration of Howard Raiffa, 11 -13 November, 2015, Laxenburg, Austria.

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Abstract

Studies of complex systems are non-separable from the analysis of partial and imprecise information received from alternative sources. Due to the high complexity of the underlying processes, researches tend to create an ensemble of multiple models, which describe the studied phenomenon using different modeling approaches and primary assumptions. A system analysist deals then with a set of ensemble outcomes (usually represented by a family of probability distributions), which needs to be integrated into one estimate in order to install the ensemble into the modeling chain or provide support for the informed decision making. This research is focused on the application of the posterior integration method (which was originally developed in IIASA [1] to reconcile stochastic estimates from independent sources) to an ensemble of climate-economic models. Our case-study uses two versions of the stylized model SDEM (Structural Dynamic Economic Model) [2], which generate different outputs (including emissions, CO2 concentration, temperature, size of economy) under two scenarios: the business-as-usual scenario and mitigation scenario (under carbon tax). We compare original results with results of posterior integration and results of the traditional approach of averaging model outcomes.

[1] Kryazhimskiy, A. (2013) Posterior integration of independent stochastic estimates, IIASA Interim Report IR-13-006.
[2] Kovalevsky, D.V., Hasselmann, K. (2014): Assessing the transition to a low-carbon economy using actor-based system-dynamic models. Proceedings of the 7th International Congress on Environmental Modelling and Software (iEMSs), 15-19 June 2014, San Diego, California, Vol. 4, 1865-1872, URL: http://www.iemss.org/sites/iemss2014/papers/Volume_4_iEMSs2014_pp_1817-2386.pdf.

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