El sistema multifondos de pensiones colombiano bajo las nuevas teorías del comportamiento financiero

En Colombia, después de casi dos décadas de la creación del régimen de cuentas privadas, se implementó una reforma donde se pasa de un sistema con un unico fondo a uno multifondos. Este tipo de reformas se vienen implementando en diferentes paises europeos y de Latino America. A la luz de las teorías clásicas dicha reforma trae mejoras en el bienestar de los individuos; sin embargo, la literatura sobre las nuevas teorías del comportamiento sugiere que los individuos no siempre toman decisiones que están de acuerdo con los supuestos de las teorías clásicas. Este trabajo estudia esta reforma en Colombia bajo algunas de las teorías del comportamiento financiero. Se encuentra que aún cuando el afiliado se quede en la opción default , o actúe con aversión a la pérdida, va a obtener valores en sus cuentas privadas mayores a las que obtendría con un sistema de un único fondo.

El sistema multifondos de pensiones colombiano bajo las nuevas teorías del comportamiento financiero

En Colombia, después de casi dos décadas de la creación del régimen de cuentas privadas, se implementó una reforma donde se pasa de un sistema con un único fondo a uno multifondos. Este tipo de reformas se vienen implementando en diferentes países europeos y de Latino América. A la luz de las teorías clásicas dicha reforma trae mejoras en el bienestar de los individuos; sin embargo, la literatura sobre las nuevas teorías del comportamiento sugiere que los individuos no siempre toman decisiones que están de acuerdo con los supuestos de las teorías clásicas. Este trabajo estudia esta reforma en Colombia bajo algunas de las teorías del comportamiento financiero. Se encuentra que aún cuando el afiliado se quede en la opción default , o actúe con aversión a la pérdida, va a obtener valores en sus cuentas privadas mayores a las que obtendría con un sistema de un único fondo.

Hierarchical Prediction Machines and Big Data Analytics

An emerging consensus in cognitive science views the biological brain as a hierarchically-organized predictive processing system. This is a system in which higher-order regions are continuously attempting to predict the activity of lower-order regions at a variety of (increasingly abstract) spatial and temporal scales. The brain is thus revealed as a hierarchical prediction machine that is constantly engaged in the effort to predict the flow of information originating from the sensory surfaces. Such a view seems to afford a great deal of explanatory leverage when it comes to a broad swathe of seemingly disparate psychological phenomena (e.g., learning, memory, perception, action, emotion, planning, reason, imagination, and conscious experience). In the most positive case, the predictive processing story seems to provide our first glimpse at what a unified (computationally-tractable and neurobiological plausible) account of human psychology might look like. This obviously marks out one reason why such models should be the focus of current empirical and theoretical attention. Another reason, however, is rooted in the potential of such models to advance the current state-of-the-art in machine intelligence and machine learning. Interestingly, the vision of the brain as a hierarchical prediction machine is one that establishes contact with work that goes under the heading of 'deep learning'. Deep learning systems thus often attempt to make use of predictive processing schemes and (increasingly abstract) generative models as a means of supporting the analysis of large data sets. But are such computational systems sufficient (by themselves) to provide a route to general human-level analytic capabilities? I will argue that they are not and that closer attention to a broader range of forces and factors (many of which are not confined to the neural realm) may be required to understand what it is that gives human cognition its distinctive (and largely unique) flavour. The vision that emerges is one of 'homomimetic deep learning systems', systems that situate a hierarchically-organized predictive processing core within a larger nexus of developmental, behavioural, symbolic, technological and social influences. Relative to that vision, I suggest that we should see the Web as a form of 'cognitive ecology', one that is as much involved with the transformation of machine intelligence as it is with the progressive reshaping of our own cognitive capabilities.

La ambigüedad, las creencias y los estereotipos que rodean a lo que hoy en día se conoce como terrorismo: Una revisión de literatura

El terrorismo en la actualidad es considerado como uno de los conceptos más controversiales en los campos social, académico y político. El término se empieza a utilizar después de la Revolución Francesa, pero recientemente, a raíz de los atentados del 11 de septiembre de 2001, ha tomado suma relevancia y ha motivado numerosas investigaciones para tratar de entender qué es terrorismo. Aunque a la fecha existen varias revisiones sistemáticas, este trabajo tiene como propósito revisar, agrupar y concretar diferentes teorías y conceptos formulados por los autores que han trabajado sobre el concepto de “terrorismo” con el fin de entender las implicaciones de su utilización en el discurso, y cómo esto afecta la dinámica interna de las sociedades en relación con la violencia, las creencias, los estereotipos entre otros elementos. Para lograrlo, se revisaron 56 artículos, publicados entre los años 1985 y 2013; 10 fuentes secundarias entre noticias y artículos de periódicos correspondientes a los años 1995-2013 y 10 estudios estadísticos cuyos resultados nos aportan a la comprensión del tema en cuestión. La búsqueda se limitó al desarrollo histórico del terrorismo, sus diferentes dimensiones y el concepto social de la realidad de terrorismo. Los hallazgos demuestran que la palabra “terrorismo” constituye un concepto que como tal es un vehículo lingüístico que puede ser utilizado con fines, estratégicos movilizando al público conforme a través del discurso e intereses políticos, destacando la necesidad de estudiar las implicaciones psicológicas y sociales de su uso.

Aplicaciones Organizacionales de TREC en el modelo RET

Las aplicaciones organizacionales de modelos psicológicos son una realidad frecuente en la práctica profesional. Sin embargo es frecuente que los soportes teóricos no sean elaborados de forma expresiva, debido al pragmatismo del entorno organizacional. Esta situación es visible al considerar el lenguaje, la estructura y el soporte teórico recogido en las publicaciones de psicólogos dirigidos al público de las empresas (el management). No obstante, las propuestas teóricas psicológicas en el campo del desarrollo, el desarrollo humano, la respuesta emocional, el aprendizaje en adultos y la cognición entre otros soportan modelos aplicados y desarrollos pragmáticos específicos. Así ocurre en el caso de TREC, que reconoce como los obstáculos emocionales relacionados con sobredemandas influyen negativamente en la comunicación y los vínculos que soportan el liderazgo en entorno organizacional. Diferentes aportes desde la inteligencia emocional permitirán entender y conectar la relación de estas teorías.

The relative success of recognition-based inference in multichoice decisions

The utility of an "ecologically rational" recognition-based decision rule in multichoice decision problems is analyzed, varying the type of judgment required (greater or lesser). The maximum size and range of a counterintuitive advantage associated with recognition-based judgment (the "less-is-more effect") is identified for a range of cue validity values. Greater ranges of the less-is-more effect occur when participants are asked which is the greatest of to choices (m > 2) than which is the least. Less-is-more effects also have greater range for larger values of in. This implies that the classic two-altemative forced choice task, as studied by Goldstein and Gigerenzer (2002), may not be the most appropriate test case for less-is-more effects.

Contextual emergence of mental states from neurodynamics

The emergence of mental states from neural states by partitioning the neural phase space is analyzed in terms of symbolic dynamics. Well-defined mental states provide contexts inducing a criterion of structural stability for the neurodynamics that can be implemented by particular partitions. This leads to distinguished subshifts of finite type that are either cyclic or irreducible. Cyclic shifts correspond to asymptotically stable fixed points or limit tori whereas irreducible shifts are obtained from generating partitions of mixing hyperbolic systems. These stability criteria are applied to the discussion of neural correlates of consiousness, to the definition of macroscopic neural states, and to aspects of the symbol grounding problem. In particular, it is shown that compatible mental descriptions, topologically equivalent to the neurodynamical description, emerge if the partition of the neural phase space is generating. If this is not the case, mental descriptions are incompatible or complementary. Consequences of this result for an integration or unification of cognitive science or psychology, respectively, will be indicated.

Children’s understanding of counterfactual alternatives

This study examines how children integrate information about counterfactual alternatives in making judgments. Previous research in adults had shown that they make judgments on the basis of comparisons between factual events and counterfactual alternatives. We suggest that children adopt a summative strategy instead, where they focus on the presented outcomes, both real and counterfactual, and base their judgments on the overall affective quality of these outcomes. Results from a single experiment comparing adults’ and children’s responses to a counterfactual judgment task show that children do tend to use a summative strategy as opposed to the comparative strategy adopted by adults. These results were further supported by participants’ justifications of their judgments, which were alternative focused for the adults, but outcome focused for the children. The results are discussed in relation to complexity-based theories of the development of human reasoning.

Rich and famous: recognition-based judgment in the Sunday Times rich list

Recognition as a cue to judgment in a novel, multi-option domain (the Sunday Times Rich List) is explored. As in previous studies, participants were found to make use of name recognition as a cue to the presumed wealth of individuals. Names that were recognized were judged to be the richest name from amongst the set presented at above chance levels. This effect persisted across situations in which more than one name was recognized; recognition was used as an inclusion criterion for the sub-set of names to be considered the richest of the set presented. However, when the question was reversed, and a “poorest” judgment was required, use of recognition as an exclusion criterion was observed only when a single name was recognized. Reaction times when making these judgments also show a distinction between “richest” and “poorest” questions with recognition of none of the options taking the longest time to judge in the “richest” question condition and full recognition of all the names presented taking longest to judge in the “poorest” question condition. Implications for decision-making using simple heuristics are discussed.

Deciding the price of fame

Previous studies of ignorance-driven decision-making have either analyzed when ignorance should prove advantageous on theoretical grounds, or else they have examined whether human behavior is consistent with an ignorance driven inference strategy (e.g., the recognition heuristic). The current study merges these research goals by examining whether – under conditions where ignorance driven inference might be expected – the type of advantages theoretical analyses predict are evident in human performance data. A single experiment shows that, when asked to make relative wealth judgments, participants reliably use recognition as a basis for their judgments. Their wealth judgments under these conditions are reliably more accurate when some of the target names are unknown than when participants recognize all the names (the “less-is-more effect”). these data are robust against a number of variations on the size of the pool from which participants have to choose and the nature of the wealth judgment.