Essays on decision sciences: exploring cognition, information processing, and complexity

This thesis provides three original contributions to the field of Decision Sciences. The first contribution explores the field of heuristics and biases. New variations of the Cognitive Reflection Test (CRT--a test to measure "the ability or disposition to resist reporting the response that first comes to mind"), are provided. The original CRT (S. Frederick [2005] Journal of Economic Perspectives, v. 19:4, pp.24-42) has items in which the response is immediate--and erroneous. It is shown that by merely varying the numerical parameters of the problems, large deviations in response are found. Not only the final results are affected by the proposed variations, but so is processing fluency. It seems that numbers' magnitudes serve as a cue to activate system-2 type reasoning. The second contribution explores Managerial Algorithmics Theory (M. Moldoveanu [2009] Strategic Management Journal, v. 30, pp. 737-763); an ambitious research program that states that managers display cognitive choices with a "preference towards solving problems of low computational complexity". An empirical test of this hypothesis is conducted, with results showing that this premise is not supported. A number of problems are designed with the intent of testing the predictions from managerial algorithmics against the predictions of cognitive psychology. The results demonstrate (once again) that framing effects profoundly affect choice, and (an original insight) that managers are unable to distinguish computational complexity problem classes. The third contribution explores a new approach to a computationally complex problem in marketing: the shelf space allocation problem (M-H Yang [2001] European Journal of Operational Research, v. 131, pp.107--118). A new representation for a genetic algorithm is developed, and computational experiments demonstrate its feasibility as a practical solution method. These studies lie at the interface of psychology and economics (with bounded rationality and the heuristics and biases programme), psychology, strategy, and computational complexity, and heuristics for computationally hard problems in management science.

Growth, structural change and technological capabilities Latin America in a comparative perspective

Countries differ in terms of technological capabilities and complexity of production structures. According to that, countries may follow different development strategies: one based on extracting rents from abundant endowments, such as labor or natural resources, and the other focused on creating rents through intangibles, basically innovation and knowledge accumulation. The present article studies international convergence and divergence, linking structural change with trade and growth through a North South Ricardian model. The analysis focuses on the asymmetries between Latin America and mature and catching up economies. Empirical evidence supports that a shift in the composition of the production structure in favor of R&D intensive sectors allows achieving higher rates of growth in the long term and increases the capacity to respond to demand changes. A virtuous export-led growth requires laggard countries to reduce the technological gap with respect to more advanced ones. Hence, abundance of factor endowments requires to be matched with technological capabilities development for countries to converge in the long term.