Antoine Mandel

A multi-agent model of several economic regions

This paper presents Lagom regiO: a multi-agent model of several growing economic areas in interaction. The model is part of the Lagom model family: economic multi-agent models developed to make steps toward understanding equilibrium selection and identifying win-win opportunities for climate policy. The particular feature of the model presented here is that it locates agents in one of a user-chosen number of regions. It can thus be used to represent diverse economic areas by specifying characteristics of agents and their interaction network as depending on their regions.

Describing economic agent-based models – Dahlem ABM documentation guidelines

At the 100th Dahlem conference “New Approaches in Economics after the Financial Crisis” a working group devised guidelines for the documentation of computational economic agent-based models, based upon – but differing from – the ODD protocol Grimm et al. (2006, 2010). This paper sketches the motivation for coming up with a new set of guidelines tailored to economic multi-agent modelling, and presents these. While analytical economic models can often be precisely and concisely stated by a few equations together with an economic interpretation of their elements, a computational agentbased model, as a conceptual piece of work, may not always be a very tangible entity. For example, it is represented by but usually not identical to the (many) equations constituting the computer code. It is therefore not always easy to describe the model in a way that provides the reader with a thorough understanding of the model. The present guidelines are an attempt at standardizing such descriptions to support understanding and communication, as well as the comparability of economic multi-agent models.

Stochastic Stability in the Scarf Economy

We present a mathematical model for the analysis of the bargaining games based on private prices used by Gintis to simulate the dynamics of prices in exchange economies in Gintis (2007). We then characterize, in the Scarf economy, a class of dynamics for which the Walrasian equilibrium is the only stochastically stable state. Hence, we provide dynamic foundations for general equilibrium for one of the best-known example of instability of the tâtonement process.

A Note on Herbert Gintis' "Emergence of a Price System from Decentralized Bilateral Exchange"

Building upon recent work of Gintis, we study evolutionary dynamics in an economy with Leontieff preferences and corner endowments for which the equilibrium is completely indeterminate. We exhibit a class of dynamics which selects, via stochastic stability, the equilibrium minimizing the quantities traded.

Transformative targets in sustainability policy making: the case of the 30% EU mitigation goal

This paper explores to what extent moving towards the 30% GHG emission reductions by 2020 with respect to 1990 in the EU can be considered a transformative target. To do so, we first define the concept of transformative targets from a complex systems perspective and show a novel approach and original results using an extended application of the GEM-E3 model. Traditional macroeconomic models cannot easily handle key synergetic system effects derived from green growth and sustainability policies, and thus require additional features. We analyse the role of semi-endogenous growth driven by learning-by-doing and low-carbon investment expectations following a long-term transformative trajectory.

Towards agent-based integrated assessment models: examples, challenges, and future developments

Understanding the complex, dynamic, and non-linear relationships between human activities, the environment and the evolution of the climate is pivotal for policy design and requires appropriate tools. Despite the existence of different attempts to link the economy (or parts of it) to the evolution of the climate, results have often been disappointing and criticized. In this paper, we discuss the use of agent-based modeling for climate policy integrated assessment. First, we identify the main limitations of current mainstream models and stress how framing the problem from a complex system perspective might help, in particular when extreme climate conditions are at stake and general equilibrium effects are questionable. Second, we present two agent-based models that serve as prototypes for the analysis of coupled climate, energy, and macroeconomic dynamics. We argue that such models constitute examples of a promising approach for the integrated assessment of climate change and economic dynamics. They allow a bottom-up representation of climate damages and their cross-sectoral percolation, naturally embed distributional issues, and traditionally account for the role of finance in sustaining economic development and shaping the dynamics of energy transitions. All these issues are at the fore-front of the research in integrated assessment. Finally, we provide a careful discussion of testable policy exercises, modeling limitations, and open challenges for this stream of research. Notwithstanding great potential, there is a long way-to-go for agent-based models to catch-up with the richness of many existing integrated assessment models and overcome their major problems. This should encourage research in the area.

The changing value of the ‘green’ label on the US municipal bond market

Green bonds are seen as a key instrument to unlock climate finance. While their volume has grown steadily in recent years, the impact of the ‘green’ label on the bond market is poorly understood. Here, we investigate the differences between the yield term structures of green and conventional bonds in the US municipal bond market. We show that, although returns on conventional bonds are on average higher than for green bonds, the differences can largely be explained by the fundamental properties of the bonds. Historically, green bonds have been penalized on the municipal market, being traded at lower prices and higher yields than expected by their credit profiles. In recent years, however, the credit quality of municipal green bonds has increased and the premium turned positive. Green bonds are thus becoming an increasingly attractive investment, with scope to bridge the climate finance gap for mitigation and adaptation.In comparison to conventional bonds, green bonds have been penalized on the municipal market. However, in recent years the credit quality of green bonds has improved, and they now represent an increasingly feasible option to unlock climate finance.

Dynamic Competition on Social Networks

We provide an analytical approach to the problem of influence maximization in a social network when two players compete by means of dynamic targeting strategies. We formulate the problem as a two-player zero-sum stochastic game. We prove the existence of the uniform value: if the players are sufficiently patient, both players can guarantee the same mean-average opinion without knowing the exact discount factor. Further, we put forward some elements for the characterization of equilibrium strategies. In general, players must implement a trade-off between a forward-looking perspective, according to which they shall aim at maximizing the future spread of their opinion in the network, and a backward-looking perspective, according to which they shall aim at counteracting their opponents previous actions. When the influence potential of players is small, an equilibrium strategy is to systematically target the agent with the largest eigenvector centrality.

A Network-Based Analysis of the European Emission Market

This paper analyses the European Emission Trading System (ETS) from a network perspective. It is shown that the network exhibits a strong core-periphery structure also reflected in the network formation process. Due to a lack of centralized market places, operators of installations which fall under the EU ETS regulations have to resort to local networks or financial intermediaries if they want to participate in the market. This undermines the central idea of the ETS to exploit marginal abatement costs.