This is not something unique to BERT but actually an artefact from the original Transformer. I remember reading about it in their paper but before that paper, tying input and output embeddings was proposed in Press and Wolf (2017) 3. From the abstract:

Finally, we show that weight tying can reduce the size of neural translation models to less than half of their original size without harming their performance.