UC Berkeley

In the first chapter, I develop a model of prospective memory, defined as the

capacity to recall actions to be carried out in the future. An agent faces some

task with stochastic cost ct , benefit b, and T periods until some exogenously

imposed deadline. The agent can only execute the task at time t if the task is

recalled in that period. The memory process exhibits the rehearsal property

that the probability of recall is lower if the task was forgotten in the recent

past. The agent sets a threshold cost each period based on her expectations

of whether she will recall and carry out the task in future periods. If the task

is recalled at time t, and the draw from the cost distribution is below this

threshold, the task is executed. We then introduce memory overconfidence

into the model, which we define as either overestimating the base likelihood

of recall in future periods or underestimating the effect of temporary forgetting

on subsequent recall. Memory overconfidence leads not only to inefficiently

low rates of task completion, but also to the prediction that the probability

of task completion may vary inversely with the length of time allocated to

completing the task. We discuss the interaction of these effects with present-biased preferences, and provide examples of economic scenarios where this

dynamic may be exploited by firms to the detriment of consumers.

In the second chapter, I introduce a new copula which simultaneously allows

fully-general correlation structures in the bulk of a multivariate distribution

and an arbitrarily high degree of dependence in the left tails. This is

ideally suited for modeling financial assets which may display moderate correlation in normal times, but which experience simultaneous left tail events,

such as during a financial crisis. The new copula is shown to be fully flexible

in the sense that the user can specify a desired structure for a sequence of

increasingly dire events in the left tail, while still retaining the same correlation

structure in the bulk. Finally, I illustrate the use of this copula with an

application to hedge fund returns.