How does Proximal Policy Optimization deal with sparse reward

Question

In the original paper, the objective of PPO is as follows:. My question is, how does this objective behave in a sparse reward setting (i.e., reward is only given after a sequence of actions were taken)? In this case we don't have $\hat{A}_{t}$ defined for every $t$.