I don't know enough about code generation to offer confident recommendations! I mean I really liked Sorav Bansal's dissertation, Peephole Superoptimization, and in recent years there's been a bunch of noise about using SMT solvers. But what's the mainstream? What are the standard techniques, and what are their strengths and weaknesses? I have very little idea.

Still, I don't think it's fair to say without qualification, "Code generation is much harder." Very simple code generation can be done by pasting together canned code fragments (the original meaning of "compiler") and occasionally computing and encoding a jump offset. A very simple code generator like the one in StoneKnifeForth https://github.com/kragen/stoneknifeforth is simpler than the parser needs to be for many popular languages. However, at least with my limited knowledge, it appears to me that parsing is a relatively closed-ended problem — sure, you can work hard to improve your error detection and recovery, and to give more useful error messages, but you're apparently going to get very little return for even enormous efforts at that. Optimization, on the other hand, which is part of code generation, is potentially arbitrarily complex, and you can keep getting good returns on your efforts for quite a long time.

So I would say that the easiest code generation is usually easier than the easiest parsing, unless you have the liberty to choose your language to make it easier to parse. But the hardest code generation is much, much harder than the hardest parsing. (Again, unless you're parsing a language deliberately designed to be difficult!)