Edgardo Bucciarelli

Understanding the Price Dynamics of a Real Market Using Simulations: The Dutch Auction of the Pescara Wholesale Fish Market

This paper aims to contribute towards the literature on artificial market modeling of real estate markets. Having the possibility to observe the Pescara wholesale fish market, we build an agent based simulation model to find out which buyers’ behavior is able to replicate its price dynamics. The present work differentiates itself from other works on perishable products because the market under investigation has a centralized structure organized as a Dutch auction instead of being based on bilateral trading. From this point of view the paper also contributes to understand the anomalies of price dynamics highlighted by the empirical papers on sequential auctions for art, wine and jewelry.

Building Artificial Economies: From Aggregate Data to Experimental Microstructure. A Methodological Survey

This paper suggests a methodological appraisal of the main improvements witnessed by the methodology based on the interplay between Experimental Economics (EE) and Agent-based Computational Economics (ACE) in the last 5–6 years. EE and ACE proved to be “natural allies” in that they complement each other: EE helps ACE in dealing with its “degree of freedom” problem and ACE helps EE in controlling and providing benchmarks for experimental subjects’ behavior. The paper discusses the role Evolutionary Computation plays in this bidirectional relationship.

Towards a Multi-Avatar Macroeconomic System

In this paper we provide a prototype Multi-Agent macroeconomic system where artificial agents’ behavioral rules are calibrated using human behaviors. The artificial representation of humans, i.e. “molded” avatars, derives from a two steps process. The first step consists in performing laboratory experiments in order to gather microeconomic data. The second relies on the use of data mining heuristic techniques on the experimental data which allow for the identification of the behavioral models that better approximate humans’ behaviors. The implementation of these techniques, which we call microeconomic calibration, leads to the identification of heterogeneous agents. We maintain that the Multi-Avatar systems which arise from the heterogeneous microeconomic calibrated agents give the possibility to improve the existing Agent-based models. The proposed approach will generate consequently more reliable policies evaluation tools. The model discussed in the paper is motivated by the investigation on the role of entrepreneurs’ financial decisions over the business cycle. This topic was addressed especially by Hyman Minsky since the Fifties and recently gained a new momentum in the scientific community after the onset of the financial crisis.

Modeling Firms Financial Behavior in an Evolving Economy by Using Artificial Intelligence

In this paper we investigate the dynamic behavior of firms capital structure. Differently from a number of existing studies, our aim is to tackle the issue by combining two approaches: experimental and computational economics. The main goal of this paper is in fact to build an artificial agent whose behavior mimics that of experimental agents. The paper shows how the heuristic approach could provide for a valid alternative micro-foundation for the financial decisions of entrepreneurs.

Looking for Regional Convergence: Evidence from the Italian Case with Multivariate Adaptive Regression Splines

This paper examines the role of data mining analysis in explaining the Italian regional dualism with the aim of suggesting economic policies to fill the existing socio-economic gaps. We analyze the 2004–2014 period exploiting the capacity of MARS model in finding relationships among data. In Italy, the presence of a North-South divide is well-known for decades and present for several social and economic aspects. Recent studies prove that strong differences exist also in the regional human capital. Thus, we search for the causes of the local differences, also considering the entrepreneurial vitality and the international trade leverage. Among several variables, MARS is useful in showing the actual determinants on which to intervene. This is possible by comparing regions grouped homogeneously into clusters using recent data. MARS results are used for policy suggestions with the aim of filling the income gap.

How Does Fairness Relate to Economic Decision-Making? An Experimental Investigation of Pro-Social Behavior

The role of fairness in economic decisions is currently at the center of numerous investigations highlighting pro-social preferences. In this paper, we focus on Amartya K. Sen’s concept of meta-ranking to study sets of preference orderings according to some fair principle. On the one hand, we propose a model based on a meta-utility function to explore different structures of preferences. On the other hand, we run an experimental economic game to test the role of meta-ranking, analyzing the results with a tensor-based method. The meta-ranking confirms the evidence of pro-social behavior in economic decision-making. This is consistent with the findings of the recent economic literature.

A Basic Model of Take-Off and Fertility Choices in the Economic Development Process

We present a simple model in which the transition from Malthusian stagnation to modern growth can occur. Agents are endowed with full control over their fertility but, differently from other studies, the degree of agents’ altruism which mainly affects fertility choices is allowed to change with the standard of living. We relate agents’ altruism to the marginal utility of consumption. The occurrence of take-off and the balanced growth path of the model are analyzed. Our model also provides for a potential explanation to the J-shaped relationship between natality rates and standard of living found by recent empirical studies.

Processing and Analysing Experimental Data Using a Tensor-Based Method: Evidence from an Ultimatum Game Study

This work investigates how newer economic behavioural research can be applied to human group behaviour and how it can be enriched using a relatively novel knowledge discovery approach. Based on an ultimatum game study conducted in the context of an extra-lab experiment, the authors propose a tensor-based method to analyse their experimental results and, therefore, to address a multi-dimensional approach. The authors prove that subjects do not behave as game theory would predict, but rather they basically prefer fair divisions of gains. This evidence confirms significant implications for theories addressing the evolution of, and the mechanisms underpinning, human group behaviour in economics, cognitive, and organizational studies.

Understanding Bruno de Finetti’s Decision Theory: A Basic Algorithm to Support Decision-Making Behaviour

The aim of this work is to present an algorithm inspired to Bruno de Finetti’s decision theory, limited to the version proposed by him in the essay “La probabilita: guida nel pensare e nell’agire” released in 1965. This work is focused on decision theory within the subjective theory of probability conceived by de Finetti. It opens with a brief overview of his theory of probability, followed by a methodological analysis functional to introduce the renowned de Finetti’s example model given for the solution of decision problems. Starting from this example, this work presents a mathematical generalization of the decision algorithm. Afterwards, a real decisional algorithm written in mathematical-style pseudo code is developed. Finally, some conclusive remarks are discussed along with possible future developments.

Designing and Programming a Graphical Interface to Evaluate Treatments in Economics Experiments

In this paper, we develop a graphical interface that allows to calculate the efficacy of one or more treatments before adopting an experimental economics design. The graphical interface is built with Java according to a model-based treatment design. The aim is twofold. We are first interested in designing treatments in order to increase their efficacy, evaluating how experimental factors can affect the treatment process design. The second aim is to enhance the internal and external validity of the experiment to be run. The general idea behind this research is to implement a Graphical Experimenter Interface (GEI) capable to support economists when deciding which experimental treatment design to adopt and thus which factors to include.