More to the point - who cares. All these languages are hopelessly slow. If performance matters do it in a performant language like C++, C or FORTRAN. If it does not matter - then it does not matter and so stop going on about it.
No, it does matter. A lot of scientific computation is one-time-use code. What one cares about is the amount of time to write, execute, and debug the code. If it will take you much less time to write the code in a high-level language (which is usually the reason people use high-level languages), it may very well be worth the 2x performance hit from Julia, or even the larger performance hits of MATLAB and R. Additionally, when the amount of time spent performing vector and matrix operations greatly exceeds the amount of time spent in the interpreter, most of these languages will be as fast as C.
I write MATLAB code that takes 5 minutes to run on a regular basis. If I were to write it in C, I would lose productivity, because it would take much more than 5 minutes longer to write. If I were to write it in Julia, it would probably take about the same amount of time to write, but I would hypothetically have the results in a few seconds. That matters.
