We introduce and analyze a model in which agents observe sequences of signals about the state of the world, some of which are ambiguous and open to interpretation. Instead of using Bayes' rule on the whole sequence, our decision makers use Bayes' rule in an iterative way: first to interpret each...

We introduce a model in which agents observe signals about the state of the world, and some signals are open to interpretation. Our decision makers first interpret each signal based on their current belief and then form a posterior on the sequence of interpreted signals. This ‘double...

We present a two-armed bandit model of decision making under uncertainty where the expected return to investing in the "risky arm'' increases when choosing that arm and decreases when choosing the "safe'' arm. These dynamics are natural in applications such as human capital development, job...

We introduce and analyze a model in which agents observe sequences of signals about the state of the world, some of which are ambiguous and open to interpretation. Instead of using Bayes' rule on the whole sequence, our decision makers use Bayes' rule in an iterative way: first to interpret each...

There is growing concern that improving the academic skills of disadvantaged youth is too difficult and costly, so policymakers should instead focus either on vocationally oriented instruction for teens or else on early childhood education. Yet this conclusion may be premature given that so few...

Domestic attempts to use financial incentives for teachers to increase student achievement have been ineffective. In this paper, we demonstrate that exploiting the power of loss aversion--teachers are paid in advance and asked to give back the money if their students do not improve...