In parts of applied math for business, there are lot of talks and papers of the form "Problem X: A Y Approach".
That seems to suggest that there is something really promising about Y. Instead, more appropriate would be "Solving Problem X". If Y was involved, then fine; if not, still fine; that Y was involved really doesn't mean much.
Then also in computing there are talks and papers of the form "Problem X via Programming Tools A and B". So, for the part "A and B", can substitute Python and Julia, Fortran, C and C++, C# and C, C# and C++, C# and Visual Basic, Common Lisp, anything Turing equivalent, etc.
To me Quantitative Economic Modeling is a big enough subject and quite challenging. That some of the computing was done in Python and Julia instead of C, C++, C#, Fortran, Algol, Folderol, etc. strikes me as nearly irrelevant. That is, I see nothing about Python and Julia that promises especially good results on the main challenges of the very challenging problem of Quantitative Economic Modeling.
Where am I going wrong?