Fact-Free Learning

Aragonès, Enriqueta; Gilboa, Itzhak; Postlewaite, Andrew; Schmeidler, David

doi:10.1257/000282805775014308

Cited by 108 publications

(80 citation statements)

References 11 publications

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“…16 Our model thus gives a crude but compact way to address the "accuracy versus simplicity" trade-off in cognitive processing. See Enriqueta Aragones et al (2005).…”

Section: E Calibration Of the Modelmentioning

confidence: 99%

Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model

Gabaix

Laibson

Moloche

et al. 2006

American Economic Review

488

152

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Decision-making requires cognitive operations, including information acquisition and information processing. Economists assume that agents act as if they were choosing these (costly) operations optimally. But models of optimal cognition pose significant conceptual challenges. Such models are generally intractable. Only very simple settings admit analytic solutions. Moreover, even computational (i.e., numerical) tractability fails as the complexity of the problem increases. In addition, models of optimal cognition suffer from the infinite regress problem: if cognition is costly, then optimizing cognition is also costly, leading one to optimize the optimization, and so on ad infinitum (John Conlisk, 1996;Barton L. Lipman, 1991;Herbert Simon, 1955).Instead of trying to model optimal cognition, we study a partially myopic and tractable alternative. The directed cognition model uses approximate option-value calculations to direct cognition to mental activities with high shadow values (Gabaix and Laibson, 2005). The current paper applies the directed cognition model to a problem of information acquisition, or search. In this context, the model assumes the following iterative search structure: At each decision point, agents act as if their next set of search operations were their last opportunity for search.Such decision-making, although partially myopic, nevertheless helps agents focus on information that is likely to be useful and ignore information that is likely to be redundant. The directed cognition model is also tractable. The model can be computationally solved in highly complex settings. The model does not suffer from the curse of dimensionality or the infinite regress problem.The current paper experimentally evaluates the directed cognition model. We find that laboratory behavior matches the predictions of the directed cognition algorithm. We begin with a relatively simple choice problem for which it is possible to compute optimal choices, and show that the directed cognition model outperforms rationality. We then turn to a complex (and

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“…16 Our model thus gives a crude but compact way to address the "accuracy versus simplicity" trade-off in cognitive processing. See Enriqueta Aragones et al (2005).…”

Section: E Calibration Of the Modelmentioning

confidence: 99%

Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model

Gabaix

Laibson

Moloche

et al. 2006

American Economic Review

488

152

View full text Add to dashboard Cite

show abstract

“…In general, it is accepted that the discovery of linkages among decisions is an NP-hard problem (Schaefer 1999;Ethiraj and Levinthal 2004a;Aragones et al 2005). As intra-module linkages (see footnote 13) become sparse, the number of alternative configurations that imitators would need to explore will skyrocket and thus render impractical any efforts at independently discovering the linkages.…”

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confidence: 99%

The Dual Role of Modularity: Innovation and Imitation

2008

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Modularity has been heralded as an organizational and technical architecture that enhances incremental and modular innovation. Less attention has been paid to the possible implications of modular architectures for imitation. To understand the implications of modular designs for competitive advantage, one must consider the dual impact of modularity on innovation and imitation jointly. In an attempt to do so, we set up three alternative structures that vary in the extent of modularity and hence in the extent of design complexity: nonmodular, modular, and nearly modular designs. In each structure, we examine the trade-offs between innovation benefits and imitation deterrence. The results of our computational experiments indicate that modularization enables performance gains through innovation but, at the same time, sets the stage for those gains to be eroded through imitation. In contrast, performance differences between the leaders and imitators persist in the nearly modular and the nonmodular structures. Overall, we find that design complexity poses a significant trade-off between innovation benefits (i.e., generating superior strategies that create performance differences) and imitation deterrence (i.e., preserving the performance differences). We also examine the robustness of our results to variations in imitation accuracy. In addition to documenting the overall robustness of our principal finding, the ancillary analyses provide a more nuanced rendering of the relationship between the architecture of complexity and imitation efforts. examples in the Auto Industry, both of which sowed the seeds for this paper. We owe a special thanks to the Associate Editor and the two anonymous reviewers who provided extraordinarily detailed and informed set of comments that improved the quality of this paper. We also thank Carliss Baldwin for her thoughtful and provocative feedback on this research. The first author thanks the Michael R. and Mary Kay Hallman fellowship at the University of Michigan for financial support. We are solely responsible for all errors and omissions. 1Electronic copy available at: http://ssrn.com/abstract=978293 Electronic copy of this paper is available at: http://ssrn.com/abstract=978293 Management Insight StatementWhat makes competitive advantage enduring and prevents its imitation is a central question in strategy research. In this paper, we investigate how and why complexity deters imitation efforts. We argue that design complexity captures the ease of making localized changes without affecting the whole organization. Based on this idea of complexity we identify three organizational structural types: fully modular, nearly modular and non-modular. The three designs differ in the extent to which they encapsulate interdependencies. We show that the potential for incremental innovation in an organization increases when one moves from non-modular to modular structures. In contrast, the potential for an organization to deter imitation decreases from non-modular to modular structures. We elabor...

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“…I will simply assume that people do disagree (though, see Aragones, Gilboa, Postlewaite, and Schmeidler (2005) as to why this can be rational). That is, some people are more optimistic about mean returns than others.…”

Section: E Relative Utility and Heterogeneous Beliefsmentioning

confidence: 99%

Risk and Return in General: Theory and Evidence

Falkenstein¹

2009

SSRN Journal

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To the degree risk is not diversifiable, someone must hold it, and standard utility theory suggests those who do hold it should be compensated via a risk premium relative to risk-free alternatives. Yet it is striking that a first approximation to risk via volatility or beta against the market return generates no positive risk premiums. Consider that assets such as houses have characteristics that require compensation, such as crime or bad schools, and these factors are abstract in a sense, yet their effects eminently measurable and consistent with intuition (Black 1999;Tita, Petras and Greenbaum 2006). Risk, meanwhile, has devolved into the financial

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Fact-Free Learning

Cited by 108 publications

References 11 publications

Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model

Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model

The Dual Role of Modularity: Innovation and Imitation

Risk and Return in General: Theory and Evidence

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