A Reduced-Complexity Model of Process-Based IAMs

Bednar, J. & Baklanov, A. ORCID: https://orcid.org/0000-0003-1599-3618 (2025). A Reduced-Complexity Model of Process-Based IAMs. IIASA Working Paper. Laxenburg, Austria: WP-25-001

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Abstract

This working document presents the development and calibration of abatement cost functions for a reduced-complexity integrated assessment model (IAM). A total of ten cost functions, partially linked to one another, are developed and calibrated based on complex process-based IAMs. This design allows the reduced-complexity model to replicate scenarios produced by more detailed IAMs while running significantly faster. The improved computational efficiency enables the exploration scenarios based on multiple parameter sets, each representing a complex IAM, to provide a robust representation of technological uncertainty.
The final model is versatile, functioning either as an optimization tool (e.g., for cost minimization under
a temperature target or welfare maximization when linked to a Ramsey growth model like DICE) or as a
simulation tool that takes a carbon price path as input. It is important to note that this document focuses
solely on the cost functions, which form the model’s core, as well as some exploratory model extensions.
Other components, such as climate or economic modules, can be easily linked using existing models.

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