It's rather the degree to which Python is dynamic that makes it slow. PyPy could be considered an implicit JIT compiler for Python, yet it is still far slower than Julia. The level of magic you can apply to Python objects that the interpreter/compiler must support is just a different league than Julia. I'd be interested if someone could compare to JS.
In the case of python it's clear that the heavy reliance on c extensions is a blessing and a curse: it's kept python relevant in communities like science even though it isn't very fast. However one of the lessons of Graal seems to be that such extensions can seriously prohibit improving performance, since they are opaque to JITs.
