Separating predicted randomness from residual behavior

Jose Apesteguia and Miguel Ballester

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: We propose a novel measure of goodness of fit for stochastic choice models: that is, the maximal fraction of data that can be reconciled with the model. The procedure is to separate the data into two parts: one generated by the best specification of the model and another representing residual behavior. We claim that the three elements involved in a separation are instrumental to understanding the data. We show how to apply our approach to any stochastic choice model and then study the case of four well-known models, each capturing a different notion of randomness. We illustrate our results with an experimental dataset.

Keywords: Goodness of fit; Stochastic Choice; Residual Behavior (search for similar items in EconPapers)
JEL-codes: C91 D81 G12 G20 G41 (search for similar items in EconPapers)
Date: 2020-02
New Economics Papers: this item is included in nep-ecm and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://econ-papers.upf.edu/papers/1757.pdf Whole Paper (application/pdf)

Related works:
Journal Article: Separating Predicted Randomness from Residual Behavior (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:1757

Access Statistics for this paper

More papers in Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra
Bibliographic data for series maintained by ( this e-mail address is bad, please contact ).