I think it has something to do with expectations.

When you study psychology you don’t expect to sit around and do math all the time.

When you study biology you don’t expect to sit around and do math all the time.

When you study economics (especially if you actually want to become and economist) you do expect to sit around and do math all the time.

For many biologists and social scientists statistics classes must seem like a chore that has little to do with what they actually want to do. For economists statistics is just another one of their math tools.

Agreed--that's how I was encouraged to think about statistics in my grad classes + research programs. They're tools for getting things done correctly, so they need to be understood thoroughly--no different than a given programming language.

I read a couple of papers on the backlash (even by expert economists) against the heavy emphasis on mathematics in economics, which, IIRC from the papers, began back in the 1940s. Basically, economists work hard producing mathematically coherent models that aren't applicable to the real world.

This is a good point, and it's a problem in theoretical economics. Some economic models abstract away some important real-world conditions.

My experience, though, is with applied macroeconomics. We'd derive models consistent with theory, then make sure we avoided a number of time series pitfalls (autocorrelation, mistaking cointegration for correlation, overspecifying a model) using a variety of statistical techniques.