My degree was in economics (though I didn’t stay in the field and moved into information security instead). Econ 101 is basically a bunch of thought experiments that are designed to get people thinking about very broad economic concepts, but it’s all very, very abstract and largely doesn’t apply to anything connected to reality.

In higher levels, it starts to resemble reality, though my professors constantly reinforced the lesson that there are multiple ways to interpret data and that no matter how complicated you make the model you’re using, it’s still a massive oversimplification of the real world.

Unfortunately, people take intro micro/macro and think that’s what economists actually think when in reality they’re essentially learning about the very, very general oversimplifications. The amount of math it takes to start going through the actual models gets overwhelming, and it’s unlikely a first or second year undergrad would be able to handle it unless they’d already taken calc 1 and 2, and ideally some additional statistics classes.

There’s also been a massive shift in the last decade from theoretical models to much harder quantitative experimentation, so the field as a whole is trying to be less theory-driven and more data-driven. I sometimes wish I’d found the math more enjoyable, because it’s been very exciting to see some of the results coming from experimentation.