Tuesday, February 26, 2008

It's not the seed, after all...

At least we can't prove it yet. Those darned economists and worse yet, econometricians are alla time forcing us to believe data and not our own eyes and memories.

It seems there is not enough evidence to convict on the charge of GM seed accelerating the trend line yield increases.
The regression models were re-estimated allowing separate trends before and after 1996. Panel B of Figure 2 shows the results of this analysis, which indicate that the trend in corn yields since 1996 changed by very small magnitudes: +0.2, 0.0, and +0.2 bushels per acre in Illinois, Indiana, and Iowa, respectively. At most, the models estimated that yield trends increased by about two-tenths of a bushel after adjusting for the effects of weather. Furthermore, none of the changes in trend were statistically significant. The sensitivity of the results was examined by also fixing the breakpoint at 1994, 1995, 1997, and 1998. The magnitude of the estimated change in trend yields was not sensitive to the alternative breakpoints[2]. In sum, the regression models did not indicate that a notable increase in trend yields for corn occurred in the mid-1990s.

How can we reconcile the lack of evidence for an increase in corn trend yields with the widespread perception that trend yields accelerated over the last decade? One possibility is that observers failed to recognize the impact of relatively favorable weather since the mid-1990s, and thereby, mistakenly attributed corn yield increases to technology. Figures 3, 4, and 5 show key weather variables for the three states over 1960-2007. The top panel in each figure shows total June-July precipitation and the bottom panel shows average July-August temperatures. The regression model results indicated that these were the most important precipitation and temperature variables for corn production in Illinois, Indiana, and Iowa. [More]
But wait - there are some caveats:
An alternative explanation for the regression results is that a shift to a higher trend in corn yields actually occurred in the last decade but there is not enough new data to detect the change. Two previous technological revolutions caused sharp jumps in trend yields (single cross hybrids in the late 1930s and nitrogen fertilizers in the late 1950s), so a shift would not be without historical precedent. As noted in the introduction, many farmers, crop experts, and seed companies credit biotechnology-driven improvements in seed genetics for recent corn yield increases.

Some experimental evidence provides support for the trend acceleration view. For example, Below et al. (2007) report that triple-stack corn varieties containing the bt-rootworm trait have a large yield advantage over non-bt varieties, as large as 50 bushels per acre. The authors note that yield advantages conferred by the rootworm trait are difficult to attribute entirely to rootworm control and hypothesize that the trait alters the corn plant's efficiency of nitrogen use. It is important to recognize that the experimental results reported by Below et al. are based on only one site (Urbana, Illinois) for one year (2007).
So, maybe it's just too early to have definitive data.

I'm not belittling this research or seed corn company assertions, but however this turns out it illustrates one major factor in competing successfully today: waiting for proof is a good way to get run over.

If triple-stack corn is yielding big yield boosts, those who wait for iron-clad confirmation will be history or at least runner-ups in land competition. If it is not, it certainly doesn't appear to be hurting yields much, so the major downside is only the difference in seed costs.

My hunch is it is hard to fool all the farmers every year, and I have found very few operators who do not subscribe to the GM-boost theory. Moreover, their evidence, however anecdotal often covers good years and bad, and is not masked by state averages.

I'll stick with the advantage of intuitive judgment on this one, even at the risk of being labeled foolish years from now when the definitive effect is teased out from a pile of variables. There is room to believe in the wisdom of crowds in situations like this.

Besides it's important to remember that if a lot of us don't take this approach the economists won't have enough data to prove we're wrong.

[Thanks, Paul]

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