Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Automation with Heterogeneous Agents: The Effect on Consumption Inequality
Tommaso Santini
IWH Discussion Papers,
Nr. 28,
2022
Abstract
In this paper, I study technological change as a candidate for the observed increase in consumption inequality in the United States. I build an incomplete market model with educational choice combined with a task-based model on the production side. I consider two channels through which technology affects inequality: the skill that an agent can supply in the labor market and the level of capital she owns. In a quantitative analysis, I show that (i) the model replicates the increase in consumption inequality between 1981 and 2008 in the US (ii) educational choice and the return to wealth are quantitatively important in explaining the increase in consumption inequality.
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The Diablo 3 Economy: An Agent Based Approach
Makram El-Shagi, Gregor von Schweinitz
Computational Economics,
Nr. 2,
2016
Abstract
Designers of MMOs such as Diablo 3 face economic problems much like policy makers in the real world, e.g. inflation and distributional issues. Solving economic problems through regular updates (patches) became as important to those games as traditional gameplay issues. In this paper we provide an agent framework inspired by the economic features of Diablo 3 and analyze the effect of monetary policy in the game. Our model reproduces a number of features known from the Diablo 3 economy such as a heterogeneous price development, driven almost exclusively by goods of high quality, a highly unequal wealth distribution and strongly decreasing economic mobility. The basic framework presented in this paper is meant as a stepping stone to further research, where our evidence is used to deepen our understanding of the real-world counterparts of such problems. The advantage of our model is that it combines simplicity that is inherent to model economies with a similarly simple observable counterpart (namely the game environment where real agents interact). By matching the dynamics of the game economy we can thus easily verify that our behavioral assumptions are good approximations to reality.
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