Microeconomic theory, behavioural economics, experimental economics

I studied the optimal task ordering when the agent is forced to complete two tasks with distinct complexity levels.

Each task is modelled as an optimal stopping problem where the agent makes a binary choice after sequential sampling of Brownian signals to match the state.

In the presence of the secondary task, the agent makes faster and less accurate decisions for the first task to alleviate the delay in receiving the subsequent payoff.

When the payoff is symmetric and tasks are solved sequentially, I showed that it is optimal to start with the more difficult task when at least one task is hard and switching to start with the easier task when both tasks are relatively easy. The results have rich behavioural implications and managerial significance.