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Reference Dependence and Random Attention

Matthew Kovach () and Elchin Suleymanov

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Abstract: We explore the ways that a reference point may direct attention. Utilizing a stochastic choice framework, we provide behavioral foundations for the Reference-Dependent Random Attention Model (RD-RAM). Our characterization result shows that preferences may be uniquely identified even when the attention process depends arbitrarily on both the menu and the reference point. The RD-RAM is able to capture rich behavioral patterns, including frequency reversals among non-status quo alternatives and choice overload. We also analyze specific attention processes, characterizing reference-dependent versions of several prominent models of stochastic consideration.

Date: 2021-06, Revised 2023-03
New Economics Papers: this item is included in nep-dcm, nep-mic and nep-upt
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Handle: RePEc:arx:papers:2106.13350