Workers earn higher wages in cities vs. rural areas. This gap could arise because cities make workers more productive, or it could be the result of a non-random selection of workers into cities based on their ability and their endogenous history of career choices. To untangle these issues, this paper estimates a dynamic programming model, which embeds the choice of residing in a city or rural area within a model of career choices over time. After controlling for all the sources of selection and endogeneity, the estimates indicate that a given worker does earn more in the city for white-collar work, but not for blue-collar work. In addition, city work experience is found to be worth more than rural work experience in the rural area for white-collar work, but not for blue-collar work. These results support the interpretation that cities make white-collar workers more productive and suggest that workers may consider moving to the city not only in terms of locational choice, but also as a form of human capital investment.

We report experimental results from long sequences of decisions in environments that are theoretically prone to severe information cascades. Observed behaviour is much different—information cascades are ephemeral. We study the implications of a theoretical model based on quantal response equilibrium, in which the observed cascade formation/collapse/formation cycles arise as equilibrium phenomena. Consecutive cascades may reverse states, and usually such a reversal is self-correcting: the cascade switches to the correct state. These implications are supported by the data. We extend the model to allow for base rate neglect and find strong evidence for overweighting of private information. The estimated belief trajectories indicate fast and efficient learning dynamics.