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Published April 4, 2019 | Submitted + Accepted Version
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The cost of information


We develop an axiomatic theory of information acquisition that captures the idea of constant marginal costs in information production: the cost of generating two independent signals is the sum of their costs, and generating a signal with probability half costs half its original cost. Together with a monotonicity and a continuity conditions, these axioms determine the cost of a signal up to a vector of parameters. These parameters have a clear economic interpretation and determine the difficulty of distinguishing states. We argue that this cost function is a versatile modeling tool that leads to more realistic predictions than mutual information.

Additional Information

We thank Kim Border, Ben Brooks, Simone Cerreia-Vioglio, Tommaso Denti, Federico Echenique, Drew Fudenberg, Ed Green, Adam Kapor, Massimo Marinacci, Jeffrey Mensch, Filip Matejka, Stephen Morris, and Doron Ravid for their comments. All errors and omissions are our own. Omer Tamuz was supported by a grant from the Simons Foundation (#419427).

Attached Files

Accepted Version - cost_of_information.pdf

Submitted - 1812.04211.pdf


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October 20, 2023