There is as yet no equivalent of R in applied econometrics. Therefore, the econometric community can still decide to go along the Python path.
That is Drs. Christine Choirat and Raffello Seri writing in the April issue of the Journal of Applied Econometrics. They have been kind enough to provide me with an ungated copy of their review, "Econometrics with Python." Mentioning the, quite frankly, redundant general programming functions and tools that had to be implemented for R, the authors make a nice case for Python as the programming language of choice for applied econometrics. The article provides a quick overview of some of the advantages of using Python and its many built-in libraries, extensions, and tools, gives some speed comparisons, and also mentions a few of the many tools out there in Python community for econometrics including RPy (RPy2 is now available), and of course NumPy and SciPy. Having spent the last week or more trying to master the basic syntax and usage of R, I very much sympathize with this position. The one complaint I hear most often from my fellow students is that Python is not an industry standard. I hope this can change and is changing, because it's much more of a pleasure to work with Python than the alternatives and that makes for increased productivity.