Much of our industry’s economic analysis is based on data from USDA or farm management associations, such as Farm Business Farm Management (FBFM) in Illinois. While this data is diligently collected, it could offer a misleading picture.
USDA data usability is diluted by political definitions of seemingly obvious terms like "farm" or "rural." FBFM data is not, in my opinion, statistically robust for the entire farm population. However, they are the best we have, which we use to justify unwarranted conclusions. To be representative would require random sampling of the farmer population. FBFM cooperators are self-selected. This is similar to Internet polls, which are derived only from people who use the Internet and like to answer polls.
Another fault is what economists call survivorship bias. Basically, it’s the failure to include information from farms that fail along with those that succeed. The problem is similar to scientists combatting disease without the ability to perform autopsies.
Farmers intuitively sense this blind spot. Consider the intensity with which we pored over the Stamp and Rosentreter case studies covered here in Top Producer. Often, we searched for moral failings to account for the flameout, but many of us came away with mixed emotions.
Without examining the failures, we don’t know how they are different from the winners. In fact, we often find that those who fail are more like winners than we expect.
When a farm business ends, its data is no longer collected. Like mutual funds, where this problem first arose, immediately dropping failed operations makes the industry appear more prosperous on average. If we examined those farms up until that point, what would we find? This question is seldom asked because gathering that kind of data is harder than simply parsing the year-end results.
Investors have come to realize that survivorship bias inflates the results, just like when the "slow" students are absent on test day. Similarly, there are holes in our understanding of what makes a farm successful.
As financier Nassim Taleb explains in his best seller, "Fooled by Randomness," we mistake chance results for business practice far too often. Our pages of advice consistently feature talented and resourceful farmers. But such attributes will not guarantee good results. My own chilling experience is that many who have left the scene were better farmers than me.
The Lucky Survive. I’m not saying the spreadsheets are wrong and the advice useless. However, both academia and the media give too little credit to random good fortune. Moreover, our industry might be more prone to this bias than others.
Take out a plat book and try to recall who used to farm where and why they aren’t anymore. In my township, the implications of such an analysis are unnerving: have wealthy, cooperative, long-lived landlords; avoid serious family illnesses; have sons; stay married; choose generous siblings (better yet, no siblings); marry inside the community and avoid weather extremes. In short, be lucky.
It doesn’t stop there. Studies of nonsurvivors have shown unlucky people tend to be narrowly focused and more anxious, thinking success is more common than it is. Seemingly lucky people look for advice on what not to do by studying failures, instead of copying successful models.
The story is told of World War II aeronautical engineers who concluded from bullet holes on main bodies of returning aircraft that those areas needed to be beefed up. Then it occurred to them that these were surviving aircraft, and the holes meant those areas could take a hit. It was the other areas that needed more protection. Not seeing the casualty aircraft made that realization less intuitive.
- February 2014