Bounded Rationality and Limited Datasets: Testable Implications, Identifiability, and Out-of-Sample Prediction
AbstractTheories of bounded rationality are typically characterized over an exhaustive data set. This paper aims to operationalize some leading theories when the available data is limited, as is the case in most practical settings. How does one tell if observed choices are consistent with a theory of bounded rationality if the data is incomplete? What information can be identified about preferences? How can out-of-sample predictions be made? Our approach is contrasted with earlier attempts to examine bounded rationality theories on limited data, showing their notion of consistency is inappropriate for identifiability and out-of-sample prediction.
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Bibliographic InfoPaper provided by Brown University, Department of Economics in its series Working Papers with number 2012-7.
Date of creation: 2012
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Postal: Department of Economics, Brown University, Providence, RI 02912
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-09-03 (All new papers)
- NEP-CBE-2012-09-03 (Cognitive & Behavioural Economics)
- NEP-FOR-2012-09-03 (Forecasting)
- NEP-UPT-2012-09-03 (Utility Models & Prospect Theory)
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