We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task's complexity is determined by its composition of cognitive operations. Complexity emerges as the inverse of the total factor productivity of thinking about a task. It increases in the number of importance-weighted components and decreases in the degree to which the effect of one or few components on the optimal action dominates. Higher complexity generates larger decision errors and behavioral attenuation to variation in problem parameters. The model applies both to continuous and discrete choice. We develop a theory-guided experimental methodology for measuring subjective perceptions of complexity that is simple and portable. A series of experiments test and confirm the central predictions of our model for perceptions of complexity, behavioral attenuation, and decision errors. We provide a template for applying the framework to core economic decision domains, and then develop several applications including the complexity of static consumption choice with one or several interacting goods, consumption over time, the tax system, forecasting, and discrete choice between goods.
Authors
Related Organizations
- Acknowledgements & Disclosure
- For excellent research assistance we thank Dustin Fichmann, Lilian Hartmann and especially Constantin Schesch, and for helpful comments Emmanuel Chemla, Alex Imas, Emir Kamenica, David Laibson, Luba Petersen, Indira Puri, Matthew Rabin, Philippe Schlenker, Simeon Schudy, Bennett Smith-Worthington, Dmitry Taubinsky, Richard Thaler, Mike Woodford, Leeat Yariv, and seminar participants at various seminars. This research was approved by Harvard IRB (IRB17-2035). Gabaix gratefully acknowledges financial support from the Sloan Foundation and Ferrante Economics Research Fund. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
- DOI
- https://doi.org/10.3386/w33109
- Pages
- 94
- Published in
- United States of America
Table of Contents
- NBER WORKING PAPER SERIES 1
- THE COMPLEXITY OF ECONOMIC DECISIONS 1
- Xavier Gabaix Thomas Graeber 1
- Working Paper 33109 httpwww.nber.orgpapersw33109 1
- NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge MA 02138 November 2024 1
- The Complexity of Economic Decisions Xavier Gabaix and Thomas Graeber NBER Working Paper No. 33109 November 2024 JEL No. C91 D03 D11 D14 D90 E03 2
- Xavier Gabaix Department of Economics Harvard University Littauer Center 1805 Cambridge St Cambridge MA 02138 and NBER xgabaixfas.harvard.edu 2
- Thomas Graeber Harvard Business School Harvard University tgraeberhbs.edu 2
- 1 Introduction 3
- 2 The Complexity of Decision Problems Basics 10
- 2.1 Cognitive production function 10
- 2.2 Complexity of a problem with one layer in the production 12
- 2.3 How complexity affects outcomes actions errors delibera- 18
- 2.4 Recursive complexity when the complexity of an action de- 20
- 3 Applications 20
- 3.1 Applying the model a users guide 21
- 3.2 The basic static theory of consumption 22
- 3.3 The complexity of life Complexity of consumption planning 27
- 3.4 Complexity of intertemporal consumption 28
- 4 Experimental Evidence on Complexity 30
- 4.1 A portable methodology for measuring subjective complexity 30
- 4.2 Experiment on intertemporal consumption 33
- 5 Complexity of Discrete Choice 40
- 5.1 Transposing our behavioral theory of continuous choice into 40
- 5.2 Complexity of discrete choice model Concrete measures 42
- 5.3 Complexity of discrete choice examples 44
- 6 Imperfect Metacognition Solving the Infinite Regress 47
- Problem 47
- 6.1 The metacognitive problem 47
- 6.2 How the infinite regress stops 48
- 6.3 How agents with limited metacognition differ Empirical pre- 48
- 7 Conclusion 49
- References 50
- A Appendix Some complements to the theory 57
- A.1 The model with sparsity 57
- A.2 Further predictions on actions vs complexity 59
- A.3 Multi-dimensional actions 60
- Table of contents 61
- B Appendix Review of Related Literature 63
- C Appendix Omitted proofs 68
- D Appendix Theory complements 76
- D.1 Endogenizing micro-complexity Complexity of a problem 76
- D.2 The mind as a cognitive economy 78
- D.3 Outside the interior region 79
- D.4 Interaction with learning 80
- D.5 First vs. second order complexity aversion 81
- D.6 Cognitive-risk adjusted certainty equivalent 82
- D.7 Complexity of forecasting 82
- D.8 Ex post simplification of decisions for instance to communi- 83
- D.9 Application Complexity of choosing between lotteries 84
- D.10 Application Complexity of choosing between different fi- 85
- E Appendix Complexity of basic arithmetic operations 86
- E.1 Complexity of a number 86
- E.2 Complexity of addition 87
- E.3 Complexity of subtraction 87
- E.4 Complexity of multiplication 88
- E.5 Complexity of the certainty equivalent in a gamble 88
- E.6 Complexity of a composite sum 89
- E.7 Complexity of choosing between two gambles. 89
- F Appendix Complements to the experimental part 89
- F.1 Survey design 89
- F.2 Calibration of utility 91
- F.3 Computation of model complexity 92
- F.4 Validating complexity elicitations 92
