Essays on misperception in information economics

Abstract

In Chapter 1, we study social learning in finite populations—typical of many real-world decision-making environments, including small organizations and local communities—where agents learn the underlying state via private signals and by observing a random sample of others’ actions over time. This differs significantly from the infinite case, where the impact of an individual on others is negligible. In a finite situation, the mutual interaction becomes quite intricate: the behavior of a given agent influences the inference of others, subsequently affecting their behaviors, which in turn affects the likelihood of observing that behavior in the future. Our findings indicate that when there are infinite agents, they can eventually discern the true state. However, should the agents in finite groups ignore finitude and simply apply the law of large numbers, they may collectively herd towards an incorrect state, despite the potential for accurate learning through exclusive reliance on their own signals. This phenomenon can be attributed to the increasing importance agents place on the actions of others as time progresses, at the expense of their private information. Additional information on others' behavior may do harm to learning efficiency.

Perceptions of upward mobility, as a reflection of individuals’ hope and confidence in the future, can deviate from reality and, through behavioral choices, influence the actual trajectory of social mobility. Chapter 2 develops a dynamic cognitive evolution model and, using data from the 2008–2018 China General Social Survey (CGSS) and macroeconomic indicators, investigates the formation mechanisms of subjective perceptions of upward mobility and their policy implications. We find that perceptions of upward mobility in China exhibit a systematic optimism bias and an inverted V-shaped fluctuation. These dynamics are jointly driven by the learning effect, which pushes perceptions toward the true mobility level, and the growth effect, which may amplify perception bias. Growth expectation can trigger a "mobility illusion" mechanism, increasing mobility perceptions by an average of 15.5% during periods of economic expansion (prior to 2011). Our analysis further highlights the role of information sources: digital media enhances the learning effect by improving the efficiency of public information dissemination, while neighborhood social networks weaken it due to the homogeneity of private information. Counterfactual analysis further demonstrate that forward-looking policies, such as conservative growth targets, improve perceptions through mobility illusion mechanism, while overly ambitious targets, if unmet, reduce optimism.