We use a unique dataset from a Singaporean taxi fleet consisting of 6,663 drivers with 23 months of daily work routines to test if taxi drivers exhibit learning by doing (LBD). We find strong evidence of LBD. Next, we document the channels of learning: drivers learn the most through technology...

We study optimal manipulation of a Bayesian learner through adaptive provisioning of information. The problem is motivated by settings in which a firm can disseminate possibly biased information at a cost, to influence the public's belief about a hidden parameter related to the firm's payoffs....

This paper systematically analyzes and enriches the observational learning paradigm of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992). Our contributions fall into three categories. First, we develop what we consider to be the right analytic framework for informational herding...

This paper explores rational social learning in which everyone only sees unordered random samples from the action history. In this model, herds need not occur when the distant past can be sampled. If private signal strengths are unbounded and the past is not over-sampled -- not forever affected...

In the social learning model of Banerjee [1] and Bikhchandani, Hirshleifer and Welch [2] individuals take actions sequentially after observing the history of actions taken by the predecessors and an informative private signal. If the state of the world is changing stochastically over time during...