Shallowness may lead to shorter path for information propagation from leafs to the root representation, and makes the representation learning more easy due to the reduction of errors in the propagation process.
leftbranching tree LSTM has a quite similar structure with linear LSTM, and it can be viewed as a linear LSTM-on-LSTM structure.