A Categorical Model of Cognition and Biased Decision Making
There is a wealth of research demonstrating that agents process information with the aid of categories. In this paper we study this phenomenon in two parts. First, we build a model of how experiences are sorted into categories and how categorization affects decision making. Second, in a series of results that partly characterize an optimal categorization, we show that specific biases emerge from categorization. For instance, types of experiences and objects that are less frequent in the population tend to be more coarsely categorized and lumped together. As a result, decision makers make less accurate predictions when confronted with such objects. This can result in discrimination against minority groups even when there is no malevolent taste for discrimination. However, such comparative statics are highly sensitive to the particular situation; optimal categorizations can change in surprising ways. For instance, increasing a group's population, holding all else constant, can lead a decision maker to make less accurate predictions about that group.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 8 (2008)
Issue (Month): 1 (February)
|Contact details of provider:|| Web page: http://www.degruyter.com |
|Order Information:||Web: http://www.degruyter.com/view/j/bejte|
When requesting a correction, please mention this item's handle: RePEc:bpj:bejtec:v:8:y:2008:i:1:n:6. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.