People say and do the darnedest things!
I'll let you assign your own "thumbs up" and "thumbs down" to the following gems. I imagine you can guess where I stand on each of them!
'But which is a bigger menace to society, laziness about data or laziness about theory? Theory-laziness is seductive because it's easy - mining for correlations isn't very mentally taxing. But data-laziness is seductive because it's hard - the more complicated and intricate a theory you make, the smarter it makes you feel, even if the theory sucks.
In the past, data-laziness was probably more of a threat to humanity. Since systematic data was scarce, people had a tendency to sit around and daydream about how stuff might work. But now that Big Data is getting bigger and computing power is cheap, theory-laziness seems to be becoming more of a menace. The lure of Big Data is that we can get all our ideas from mining for patterns, but A) we get a lot of false patterns that way, and B) the patterns insidiously and subtly suggest interpretations for themselves, and those interpretations are often wrong.'
(Noah Smith in his post, Which is Better, Data or Theory?)
'........ which raises the question "who should be teaching students econometrics?" Should it be someone like ****, who is basically an applied micro guy, or should it be an econometric theorist?'
(Frances Woolley, commenting on her own post)
'Developing statistical methods is hard and often frustrating work. One of the under appreciated rules in statistical methods development is what I call the 80/20 rule (maybe could even by the 90/10 rule). The basic idea is that the first reasonable thing you can do to a set of data often is 80% of the way to the optimal solution. Everything after that is working on getting the last 20%.'
(Jeff Leek, on the Simply Statistics blog)
'The micro stuff that people like myself and most of us do has contributed tremendously and continues to contribute. Our thoughts have had enormous influence. It just happens that macroeconomics, firstly, has been done terribly and, secondly, in terms of academic macroeconomics, these guys are absolutely useless, most of them. Ask your brother-in-law. I’m sure he thinks, as do 90% of us, that most of what the macro guys do in academia is just worthless rubbish. Worthless, useless, uninteresting rubbish, catering to a very few people in their own little cliques.'(Chris Auld, reputedly quoting someone else, in a blog post from 2011)
'The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.'
'So, we produce our papers, as if on a relentless production line. We cannot wait for inspiration; we must maintain our output. To do our jobs successfully, we need to acquire a fundamental academic skill that the scholars of old generally did not possess; modern academics must be able to keep writing and publishing even when they have nothing to say. ....'
(Michael Billig, as quoted by Timothy Taylor)