Is there a formalization for the trade-off between the expressiveness and the speed of a programming language?
This is a really interesting problem and I don't think there are definitive answers. There are two important, and distinct dimensions to this problem.

What does expressivity actually mean? In the light of the
Church-Turing thesis, which states that all programming languages
are the same (can be compiled into each other). Nevertheless it
seems pretty clear that e.g. assembler programming is quite
different from programming in Python. There is a research field that
studies this. It was pioneered by (1), but much ink has been spilled
since.

In computational complexity theory speedup theorems show that for
any algorithm solving a problem, there is a faster algorithm  solving the same problem. Examples are
Blum's speedup theorem  and the linear speedup theorem. Basically, what those speedup theorems tell you is that you can
always speed up computers (Turing machines) a bit by adding more
powerful commands. In processors we went from 4 bit CPUs to 8 bit,
then 16 bit, the 32 bit and nowadays 64 bit.


Neither quite answers your question, I'm afraid!

(1)  M. Felleisen, On the Expressive Power of Programming Languages.