Resumen:
En esta charla abordaré la pregunta sobre qué tanto los modelos basados en agente pueden ser usados para el análisis causal. En particular, primero, discutiré tres diferentes formas de comprender la causalidad y, entonces, me basaré en un modelo basado en agentes específico para mostrar que: (1) el modelamiento basado en agentes permite implementar una comprensión manipulacionista y generativa de la causalidad; (2) bajo ciertas condiciones, las conexiones causales establecidas in silico (vía computador) son informativas de las conexiones causales en el mundo real.
 
Abstract:
In this talk, I address the question of the extent to which agent-based modeling can be used for causal analysis. In particular, first, I discus three different understandings of causality and, then, I build on a specific sociological agent-based model to show that: 1/ agent-based modeling does allow to implement a manipulationist and a generative understanding of causation; 2/ under certain conditions, causal connections established in silico are informative of causal connections in the real world.
 
Referencias (Descargables en PDF):
Goldthorpe, J. (2001). Causation, statistics, and sociology. European Sociological Review, 17 (1): 1–20. 
Manzo G. (2007) “Variables, mechanisms, and simulations: can the three methods be synthesized? A critical analysis of the literature”, Revue Française de Sociologie, 48 (Supplement: An Annual English Selection), 35-71.
Manzo G. (2011). “Educational Choices and Social Interactions: A Formal Model and A Computational Test”, Comparative Social Research, 30, 47-100.
Manzo G. (2011). “Relative Deprivation in Silico: Agent-based Models and Causality in Analytical Sociology”, in P. Demeulenaere (ed.), Analytical Sociology and Social Mechanisms, Cambridge, Cambridge University Press, ch. 13, 266-308.