In many economic scenarios, people face incomplete information about the payoff relevant states of the world, and they may resort to different tests (e.g., analysts, medical diagnoses, or psychic octopuses) to obtain information to reduce the risk exposure. This paper studies how do people evaluate and choose tests. Are they able to avoid useless ones (quacks) and identify genuinely useful ones (experts)? Are they over-paying for quacks and under-paying for experts, and why? I develop a novel experiment wherein people face structured and rich choice sets of expert and quack tests and choose their favorite ones through a graphic coloring task. I find that people do fail to distinguish experts and quacks on a large scale, and they are over-paying for quacks but accurately paying for experts. These results are not driven by the standard explanations suggested in the literature, including failures in belief updating and action best-responding, heuristics, and intrinsic preference over certain information characteristics. Instead, I show that the main culprit for these anomalies is the lack of contingent reasoning in information processing. This new channel underlies many decision problems in behavioral economics and game theory and may provide new explanations for the confound in these fields.
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