AsPIK













Research Strategy Group Members lagom Presentations Publications Theses Media

 

Research Strategy

The project will build a series of software modules designed to represent the interaction between climatic risks and financial markets. The modules will fit the framework of the CIAMn approach as pursued in several other PIK-projects. AsPIK follows a cautious multi-agent design. We start with a small number of aggregated agents – insurance firms, banks, generic businesses, households, and governments. They form Bayesian expectations on climate risks, while differing in priors and risk aversion. They equilibrate spot, but not forward markets. In this setting, we use asymptotic methods to study the interaction between short- and long-term risk management.

Group Members


Prof. Carlo Jaeger
Anne Biewald


Dr. Armin Haas

Cezar Ionescu

Prof. Rupert Klein
Jette Krause


lagom
  • lagomd_opt
    lagomd_opt is a deterministic multi-agent general equilibrium model where rationing can occur. Each economic agent is represented as a module written in Mathematica. At the moment these agents are a producer, and a household-construct that consists of three types of households (skilled, unskilled and rich households). These types of households come as young, middle and old ones. The market mechanism of the model is implemented via a rationeing-module which generates from inconsistent demands and supplies consistent transactions, thus market-clearing need not necessarily take place. → more
  • lagomd_sim
    The model is of the stochastic dynamic general equilibrium type: several markets interact with each other and with the production process, each of them is influenced by random events, and the overall trajectory of the system is governed by the dynamic co-ordination of demand and supply for the various goods considered. The model is a macro-model in the broad sense: optimizing agents are treated implicitly via the demand and supply functions that they bring about. The agents may be faced with all sorts of uncertainties. Some of these may cancel out at the macro level, others have their traces in random processes visible at that level. The model is not a macro-model in the narrow sense: for its dynamics, the formation of relative prices does matter. → more
  • lagomb_learn
    Human decision-making is often faced with situations of uncertainty. Bayesian statistics offers valuable tools to calculate and improve probability judgements in situations where no conclusive assessment can be derived from data. This platform applies the technique of Bayesian Learning. It can be used to demonstrate how expectations change in the light of data. E.g., users can find out to what extent current expectations are confirmed by past data or, starting from different sets of expectations, they can investigate whether different learning processes converge over time. → more

Presentations


Publications
Agents, Bayes, and Climatic Risks - a modular modelling approach, Carlo Jaeger, Armin Haas, Advances in Geosciences, Vol. 4, pp 3-7, August 2005
A Long-Term Model of the German Economy: lagomd_sim, Carlo Jaeger, PIK-Report No.102, October 2005

A Dynamic Stochastic Bufferstock Model with Subsistence Level in an Overlapping Generations Framework , Anne Biewald
Rationing and Bayesian Expectations with Application to the Labour Market, Hannah Förster
Produktion unter Unsicherheit, Frank Meissner

Media

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