> That is, most economic discussions are based on terms that aren't meaningful in any practical way. I see a lot of economists poking at the metrics with their pencils and talking theory while waving their arms around wildly.

Actually, the problem is that people infer terms to mean things that they don't mean, oftentimes because the terminology is (regrettably) overloaded, even when the technical meaning is very precise and limited. Understandably, people interpret these terms literally, which sometimes leads to conclusions that seem paradoxical or impractical[1].

Remember that economics is really just the study of choices: choices in the small (microeconomics) or choices in the large (macroeconomics). Choices may involve money, but money is not inherent in economics - it just so happens that there are many advantages to a monetary system, which is why most economies develop some form of currency, and which is also why many (but not all!) economists deal with money. Even though it uses similar terminology, macroeconomics is fundamentally different[2] from microeconomics at its core. One is the study of individual decisions on a small scale, and the other is the study of the non-random patterns of many independent decisions.

GDP is not the perfect measure of what it's meant to gauge (macroeconomic economic 'health', which is itself a problematic term). GDP systematically overestimates the health of oil-backed economies with huge wealth disparities, for example. That said, there's no metric that's much better for the general case - all have similar systematic flaws in some way.

Furthermore, GDP has the advantage that it's completely unambiguously defined. That doesn't mean it can be measured perfectly, but having an unambiguous definition is a key step. When you start talking about these contrived indices (the 'happiness' index, the 'corruption' index, etc.), you get the problem that there's little underlying justification for the way that the model is constructed, so even if the end results are useful for a particular domain-specific application, they don't generalize well. GDP, on the other hand, can be derived quite easily from first principles, so it generalizes very nicely. Furthermore, GDP happens to correlate very well with most things that we would classify as 'good' (quality of life, corruption, happiness, etc.), so it's a nice proxy for these intangible 'goods' (no pun intended), which are more difficult to measure precisely.

So back to your question: maybe the measurements themselves are rigged - that just gets at the question of who is actually doing the analysis. But the construction of the model is no more 'rigged' than any other model. You just have to be careful to know that, like all models, its application is still very limited, even if it's one that we happen to use quite frequently.

As George Box says, 'All models are wrong, but some models are useful'. GDP is 'wrong', but it also happens to be by far the most useful way of describing the patterns choices on a large scale.

[1] This is by no means specific to economics: it happens in statistics as well, and (to a lesser extent) in computer science.

[2] That is to say, they aren't mutually exclusive, but they are based on completely separate assumptions, so principles from the small do not necessarily carry over into the large scale.