Sure it works for the lonely coder or small shops, but as soon as the project scale increases anything goes.
Managers will push for features over unit tests, no one will refactor code without taking a few days with the caveat not all places will be touched and the team atrition will bring in new devolpers forced to read implementation code to be sure how to properly call the functions/methods.
Advanced static typed languages with HM type inference are a better option for large scale development.
Hence it may be that is harder to get funding for other types of research.
Other issue is that dynamic languages fo their very nature make tooling harder problem to solve, hence less interesting for many researchers, pressed with delivering quick results.
For example, consider the exponentiation function. When we raise an Integer to a positive Integer (2^2), the result will always be a positive Integer. You would expect the type of such a function to be: Integer -> Integer -> Integer
Except, that's wrong. When we raise an Integer to a negative Integer (2^-2), the result will be some fractional value. If we want to retain full numeric precision, it'll have to be something like a Rational. So now your function's type signature is: Integer -> Integer -> Rational.
But that's also wrong. So what are we to do? Maybe positive and negative integers should be separate types? PositiveInt and NegativeInt, let's say. But then what about subtraction? Should it's type signature be: PositiveInt -> PositiveInt -> PositiveInt? What about 2 - 3? Whoops!
So, there's no way, with types alone, to simply and accurately encode all basic math operations. All you can do is throw a Domain Error when someone violates certain boundary conditions, and tell them to check their arguments before deciding which function to call.
...meanwhile, dynamic languages will happily return whatever type is most appropriate for the arguments given.
In a dynamic language, your mistake passes silently; the result you thought was an integer is actually a fraction, but your program carries on going. Maybe it turns it into a string and uses it as a file path, so something you thought was a simple filename has a slash in it. Maybe that breaks your security model. Pretty unlikely in this specific case, but that's how bugs happen.
What really interests me are languages like Julia or Dart, with their gradual typing, or Clojure and core.typed. You retain the flexibility and speed of development of a dynamic language, with the possibility of later adding type safety guarantees to your code without having to rewrite it from scratch.
How is this different? When you compile, your compiler will say "Hey, the requirements have changed, your code is wrong here, here, here, and here," and you modify those things, and you're done.
1- You wrote tests which start failing. You must now spend time changing them. You don't manage to avoid working in order fix your safety net (be it static type checking or your test suite).
2- You didn't write the right tests, and don't notice the change in behavior. The program later fails in production.
The big theoretical drawback is that you get an unbounded increase in program length. The reason is that programs in a typed language are proofs, and proof length cannot be bounded above by any computable function of proposition length.
The big practical drawback is that we just don't know how to explain proofs to a computer very well.
It can express that 2^2 is positive and an integer, that 2^-2 is positive and a rational, and that 2-3 is an integer but not necessarily positive.
I don't know. Haskell and OccamL, for one, are much, much faster than Python and Ruby.
Of course, there was no Ruby back then. The comparison was against C++, Ada, Awk (!?), something called "relational Lisp" and a variety of in-house languages. Haskell comes just after Lisp in development time, with a mind-boggling 8 hours! (No C++ times were reported... heh heh). The Haskell solution also got top marks in general, not just in development time. As a downside, some of the reviewers didn't understand it because they weren't well-versed in functional programming, and felt some of the Haskell code was "tricky".
(For all that, I agree with them though. Maybe the reason programming languages researchers think that is because it's true? Do you have reason to believe they're wrong?)