Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science

The paper deals with the use of empirical data in social science agent-based models. Agent-based models are too often viewed just as highly abstract thought experiments conducted in artificial worlds, in which the purpose is to generate and not to test theoretical hypotheses in an empirical way. On the contrary, they should be viewed as models that need to be embedded into empirical data both to allow the calibration and the validation of their findings. As a consequence, the search for strategies to find and extract data from reality, and integrate agent-based models with other traditional empirical social science methods, such as qualitative, quantitative, experimental and participatory methods, becomes a fundamental step of the modelling process. The paper argues that the characteristics of the empirical target matter. According to characteristics of the target, ABMs can be differentiated into case-based models, typifications and theoretical abstractions. These differences pose different challenges for empirical data gathering, and imply the use of different validation strategies.Agent-Based Models, Empirical Calibration and Validation, Taxanomy of Models

Horizontal and Vertical Multiple Implementations in a Model of Industrial Districts

In this paper we discuss strategies concerning the implementation of an agent-based simulation of complex phenomena. The model we consider accounts for population decomposition and interaction in industrial districts. The approach we follow is twofold: on one hand, we implement progressively more complex models using different approaches (vertical multiple implementations); on the other hand, we replicate the agent-based simulation with different implementations using jESOF, JAS and plain C++ (horizontal multiple implementations). By using both different implementation approaches and a multiple implementation strategy, we highlight the benefits that arise when the same model is implemented on radically different simulation environments, comparing the advantages of multiple modeling implementations. Our findings provide some important suggestions in terms of model validation, showing how models of complex systems tend to be extremely sensitive to implementation details. Finally we point out how statistical techniques may be necessary when comparing different platform implementations of a single model.Replication of Models; Model Validation; Agent-Based Simulation

Agent-Based Models of Industrial Clusters and Districts

Agent-based models, an instance of the wider class of connectionist models, allow bottom-up simulations of organizations constituted byu a large number of interacting parts. Thus, geogrfaphical clusters of competing or collaborating firms constitute an obvious field of application. This contribution explains what agent-based models are, reviews applications in the field of industrial clusters and focuses on a simulator of infra- and inter-firm communications.Agent-based models, industrial clusters, industrial districts

Agent modelling of cluster formation processes in regional economic systems

The subject matter of this research is the processes of the spontaneous clustering in the regional economy. The purpose is the development and approbation of the modeling algorithm of these processes. The hypothesis: the processes of spontaneous clustering in the social and economic environment are supposed to proceed not linearly, but intermittently. The following methods are applied: agent imitating modeling with an application of FOREL and k-means algorithms. The modeling algorithm is realized in the Python 3 programming language. The course regularities of clustering processes in the region are revealed: 1) the clustering processes are intensifying, the production uniformity is increasing; 2) the increase of the level of production uniformity leads to the leveling of customer behavior; 3) the producers of high-differentiated production reduce the level of its differentiation or leave the cluster; 4) the stages of steady functioning are illustrative for clustering processes, their change is followed with arising of bifurcation points; 5) the activation of clustering processes in regional economy leads to the revenue increase of the cluster participants, each of producers and of consumers, and to the growth of synergetic effect values. These results testify the nonlinearity of processes of clustering and ambiguity of their effects. The following conclusions have been drawn: 1) a modeling of the processes of spontaneous clustering in regional economy has showed that they proceed not linearly, a steady progressive development is followed with leaps; 2) the clustering of regional economy leads to the growth of the efficiency indicators of activities of cluster-concerned entities; 3) initiation and activation of the clustering processes requires a certain environment

Diffusion entropy analysis on the scaling behavior of financial markets

In this paper the diffusion entropy technique is applied to investigate the scaling behavior of financial markets. The scaling behaviors of four representative stock markets, Dow Jones Industrial Average, Standard&Poor 500, Heng Seng Index, and Shang Hai Stock Synthetic Index, are almost the same; with the scale-invariance exponents all in the interval $[0.92, 0.95]$. These results provide a strong evidence of the existence of long-rang correlation in financial time series, thus several variance-based methods are restricted for detecting the scale-invariance properties of financial markets. In addition, a parsimonious percolation model for stock markets is proposed, of which the scaling behavior agrees with the real-life markets well.Comment: 5 pages, 3 figure

Driade space: an agent based simulation model for the analysis of the firm demography and the localization patterns in urban areas

An agent based model of firm mobility is presented in which diverse types of firms decide their geographical localization in function of some spatial variables. Although as much the regional economy as the geography have studied in depth the rules of localization of the companies, many of the complex behaviors that are observed in the reality are still, in great measure, unexplained. The simulation based on agents constitutes a new approach to the problem, allowing to integrate in the models of economy regional aspects of great relevance that, for its high complexity, could not be included in the analysis more than in qualitative terms. In the Driade Space model the demography of firms is considered in a wide sense: number of firms, entries and exits, distribution of sizes as well as the spatial density of firms. The entry of new companies in each period depends on the evolution of the market. The number of these is function of the profitability observed in the sector in the previous period and the height of the entry barriers. The companies are rational and they act on the variables within their reach in function of their objectives and of the limited information they have on the evolution of the market and the behavior of their competitors. This way, the companies in the moment of their entrance decide the localization they expect that will be more profitable considering their own characteristics while in the successive periods they decide on their investments and their production. The costs of the companies are not fixed; they depend not only on the production level and on the price of the used productive factors but also on the price of the land. The derived economies of the initial decision of localization are also considered. The characteristics of the territory where the firms are located are not static but rather evolve depending on the applied policies, demographic variables and the localization of the companies. Although the exits of the companies depend mainly on their profitability, they are also affected by random aspects. When the companies exit the market they leave a free space that can be covered by other companies favoring this way new entries. The model presented allows showing the endogenous rules of firm localization as well as the effects in the medium and the long term of the public policies.