| Popis: |
This thesis is devoted to the problem of information collection from theoretical and experimental perspectives. In Chapter 2, I characterize the unique optimal learning strategy when there are two information sources, three possible states of the world, and learning is modeled as a search process. The optimal strategy consists of two phases. During the first phase, only beliefs about the state and the quality of information sources matter for the optimal choice between these sources. During the second phase, this choice also depends on how much the agent values different types of information. The information sources are substitutes when each individual source is likely to reveal the state eventually, and they are complements otherwise. In Chapter 3, co-authored with Li Song, we conducted an experiment which demonstrates that even in a simple four person circle network people appear to fail to account for possible repetition of information they receive. Moreover, we show that this phenomenon can be partially attributed to rational considerations, which take into account other people’s deviations from optimal behavior. In Chapter 4, co-authored with Marcelo A. Fernández,we model overconfidence as if a decision maker perceives information as being more precise than it actually is. We show that the effect of overconfidence on the quality of the final decision is shaped by three forces, overestimating the precision of future information, overestimating the precision of past information and overestimating the amount of information to be collected in the future. The first force pushes an overconfident decision maker to collect more information, while the second and the third forces work in the other direction. |
