I realize I’m terribly late to this party. I’m not even fashionably late, I’m “you arrived just as the caterers were cleaning up and the hostess had taken off her shoes” late. I’ve been busy (as, I think, I’ve amply covered).
However, I really must say a word or two about Reinhart and Rogoff.
For those who don’t follow economics or kinda remember they heard about it but aren’t sure what the big hullabaloo is, I recommend you google it; look for the Economist, the Guardian, and the Atlantic non-editorial resources to start. There’s a few. Then you can go off to the editorials for dessert. For those who don’t want to google, here’s the Twitter version: Two economists present a work in which they suggest that there is a deep drop off in economic performance without austerity measures. Essentially they said that when debt is high, growth slows to a grinding halt; the graph they presented roughly resembled the cliffs of Dover.
And it was wrong.
Because of an Excel spreadsheet formula error.
Normally this wouldn’t be awful. Anyone, and I do mean anyone, who has used Excel to convey data (or volumes of analysis) has made that spreadsheet error, and it can be as simple as not properly conveying a Sum formula, or as complex as messing up your Vlookup in your nested IF statement. Excel has been bastardized over the years into an analytics function (by courtesy of default in that it’s on nearly every machine) that it really can’t fully accommodate without failsafes; EVERYONE makes an Excel error.
Reinhart and Rogoff’s mistake is NOT that they made a spreadsheet formula error. And, contrary to the article above I linked to, it’s only partially that they did not peer review.
It was governments’ (plural, many, varied) mistake to use it to shape policy.
Lookit, suppose I told you that, according to my Excel spreadsheet, you were very likely to die from dehydration if you didn’t eradicate all but 0.4 grams of salt per day from your diet. For perspective, the average diet has about 5 times that. You would very rightly look to other studies, other data, other sources of information. You’d poll your neighbors. You’d check with friends. You’d do your due diligence before you used my say-so, no matter how shiny my Excel spreadsheet, or even how shiny my MD would be (this is fiction, after all). Plenty of people are told by their doctor to lose 10lbs because it will make a difference in the long run, and plenty of people seem to blithely ignore it because they don’t have corresponding (personal, attributable, anecdotal) data.
So why, why, why did any government, financial body, fiscal institution leap on the screeching panic train when R&R’s study hit? Why did no one look to a 2nd opinion, a different study; why didn’t they check the data for themselves before subjecting their economies to the fiscal equivalent of a rectal exam?
I have been in data now for 15 years. It’s not a long time in the scheme of things, but it’s something I’m known to be passionate about. I can go on and on about how data works, or doesn’t; what you can derive from it; how data *is* integrity if done right. Any form of analytic reporting that is worth its salt has been tested, peer-reviewed, and validated against two or three other methods before it is used in a practical space. At Expedia, at one point, I managed 500 ad-hoc requests per month, and each of those was eyeballed against existing reporting and a decent sense-check before being used to cut deals (or not).
Now, please understand: R&R screwed up. And, apart from their formula error, they insist the outcome is the same (and it is, but it’s the equivalent of saying “ok it’s not a steep drop off anymore, more of a speedbump, but still it’s a delta!!”). This is the foible of the data monkey; again, something we’ve all been prey to. But not all of us have done it to the culpability of large (and small) governments, and most of us have learned to admit when we’re wrong. That is the crux of it: if no one is perfect, no data is perfect, to pretend yours is against evidence to the contrary is specious at best and negligent at worst.
I argue though that the more egregious mistake is to *follow* that data without validation. To quote Ben Kenobi: “Who’s more foolish, the fool, or the fool that follows him?”