Catálogo de publicaciones - libros

This paper introduces methods, based on decomposable random combinatorial analysis, to model a large number of interacting agents. This paper also discusses a largely ignored possibility in the mainstream economic literature that hitherto unknown types of agents may enter the models at some future time. We apply the notion of holding times, and introduce the results of the one- and two-parameter inductive methods of Ewens, Pitman and Zabell to economic literature. More specifically, we use the notion of exchangeable random partitions of a finite set to produce a simple rule of sucession, that is, the expressions for the probabilties for entries by new or known types, conditional on the observed data. Then Ewens equilibrium distriution for the sizes of clusters is introduced, and its use to examine market behavior is sketched, especially when a few types of agents are dominant. We suggest that the approaches of this paper and the notion of holding times are relevant to agent-based simulations because holding times can be used to randomly select agents that “act” first.

This paper analyzes, via intensive use of simulation techniques, the effects of the introduction of direct exchange relationships through bilateral trades in a simple general equilibrium pure exchange economy. Agents are heterogeneous in their endowments and repeatedly match in random pairs bargaining on how to split the advantages of a trade; possibly they can agree to exchange at the known market clearing prices. Simulations of this evolutionary process show that while walrasian outcomes emerge in the interaction among people with similar outside opportunities, people of different groups converge to accept an equilibrium in which agents with the best outside opportunity extract the greater part of the surplus out of an exchange. On other hand the acceptance of market mediation (i.e. walrasian outcomes) is more probable when either the parties try to exploit too much from the opponent or when there is anonymity in the trading process. The results show evidence that the acceptance of decentralized, personalized contracting (apart from efficiency considerations) increases the probability of amplifying the asymmetries in the initial distribution beyond what is produced by the pure market mechanism.

We analyze an economy in which increasing returns to scale incentivate social aggregation in a population of heterogeneous boundedly rational agents; however these incentives are limited by the presence of imperfect information on others’ actions. We show by simulations that the equilibrium coalitional structure strongly depends on agents’ initial beliefs and on the characteristics of the individual learning process that is modeled by means of genetic algorithms. The most efficient coalition structure is reached starting from a very limited set of initial beliefs. Furthermore we find that (a) the overall efficiency is an increasing function of agents’ computational abilities; (b) an increase in the speed of the learning process can have ambiguous effects; (c) imitation can play a role only when computational abilities are limited.

In this paper we adopt a new macrodynamic tool, i.e. a system of non-linear difference equations describing the evolution over time of the first and second moments of the distribution of firms’ degrees of financial robustness captured by the ratio of the equity base to the capital stock - the equity ratio for short - which affects supply and capital accumulation decisions. For particular configurations of parameters the dynamic patterns of the average equity ratio and the variance generate irregular and asymmetric time series in which growth and fluctuations are jointly determined ( fluctuating growth ).

This paper deals with the aggregate effects of small, exogenous but idiosyncratic technological shocks on locally interacting firms. Its main purpose is to model a situation in which technological paradigms emerge through endogenous propagation and diffusion of information leading to an aggregate pattern. We develop a theoretical framework in which large technological correlations emerge due to localised interaction of single firms. The paper states some simple results on spill-over dynamics determined by firms trying to improve their current technology and thus generating new information through investment in R&D and through localised technological search. The first part shows that different growth regimes can arise from the general framework of interaction that we propose. The second part shows that an interesting regime characterised both by long run innovation growth and endogenous short run fluctuations emerges spontaneously.

The aim of this paper is to show that economic systems must be characterized by their possible singularities rather than by their regularities. Changes in parameters of a regular economy imply only small changes in the optimal choice of the agents, i.e. the economic system is structurally stable, and they are consistent with one another minor changes. But in a singular economy, small changes in parameters affect the choice of the agents in a relevant way. The equilibria, after and before the changes, are radically different states, i.e. the economic system is structurally unstable. Catastrophe theory and Morse theory are used here to characterize singular economies. These are classical theories in mathematics but nevertheless, they are new tools to help understand the behavior of an economic system. Also the approach of Negishi is followed, and this allows us to consider in a unified way economies with finitely or infinitely many goods.

This paper analyzes the structural relationships of the financial transactions represented in a Social Accounting Matrix (SAM) for the Mexican economy through a pretopological approach. Based on a simple binary relationship between incomes and expenditures of institutional accounts, the pretopology is used as a mathematical tool to get an insight into the economic structure represented by the SAM. Such an analysis can be useful to identify the set of relationships between several institutional accounts, ordered according to their influence or domination.

I present a neural network model for the spontaneous emergence of enterprises following a dynamic approach to firm formation in the tradition started by Adam Smith and further pursued by Joseph Schumpeter. I suggest that the “natural propensity to truck and barter” is the observable behaviour of self-interested economic actors who are continually exposed to and confronted with an environment complexity, which transcends their limited cognitive and computational capabilities. In their learning process they build networks of relations with other agents. It is this interaction among heterogeneous agents that often leads to the formation of successful organizations that completely solve the original problem. Firms can be seen simultaneously as the result of the entrepreneurs induction process, but also as the essential instrument for the elaboration of a solution to the problem. Increasing returns to scale and market size find in this framework a very natural representation. The role of competition for the nurturing of efficiency, and the issue of protection of infant industries can be tackled by this model.

Recent years have seen a proliferation of Multi-agent-based simulation (MABSS) models, in a growing range of domains, and using an increasing variety of software. In this article we compare some Agent Based environments anyone can download in Internet. The aim of this article is to discuss the general principles of each environment, and not to say which is the best or the worst one. The comparison is performed along several dimensions such as ease of learning, flexibility, available support, etc. It should also help the choice of a language by potential practitioners of agent-based economic. At the end of this article there’s a personal proposition about these environments of the author.