Cows, Corn, and Consolidation: Is More Farm Diversity a Good Thing?
University of Wisconsin--Stout
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Our research centered on the economic and environmental impacts of farm consolidation and crop diversity. I’ll admit, it sounds pretty dull. But I actually had a blast working on it this summer with my partner Lily and mentor Chris. Even in the moments when we were bored out of our minds downloading data tables (@ USDA please make your website better) and the moments when we all just wanted to smash our computers on the floor, I never lost interest in the overall goal. Maybe that’s just because Chris and Lily helped keep things interesting with their awesome selves. But I think it also had something to do with the fact that the questions we were asking were way more intricate and detailed than I had originally assumed they would be. For example: how do you measure crop diversity? By acres? By sales? By number of operations? We ended up just going with all of the above. But it’s the mini questions like that which ultimately held my interest and got me invested in the research. There are also a lot of people interested in these questions, which is why we began studying it in the first place. For several decades now, Wisconsin farms have been falling in number and growing in size. When you look just at the average acres per farm it may not look like it’s been increasing, but that’s because it’s the distribution of small, medium, and large farms that’s been changing. Over time, there’s been a gradual shift away from medium-sized farms and towards extremely large and extremely small farms. This has been accompanied by a shift towards decreased crop and animal diversity as we see more enormous monocrop farms. So it only makes sense that people would want to know how this dramatic shift is affecting their local economies and environments. We started our research by assembling data from 5 different Censuses of Agriculture dating between 1997 and 2017. After that, we created what’s known as a diversity index, which we then applied to each county in Wisconsin. A diversity index is essentially a formula that spits out one number that describes the overall diversity of a given county. After writing the codes for our indexes, all we had to do was input the numbers from the Ag Census, such as acres of maple syrup grown in Dunn County and number of operations growing pumpkins in Adams County. The formula then provided us with an easy way to compare the crop diversity of different counties. To compare the farm consolidation of different counties, we calculated the percent of farms in a given county that are classified as large. For this, we just used the standard USDA definition of a large farm: any farm that grosses $500,000+ annually. Using these numerical measures of diversity and consolidation, we analyzed their effects on counties’ Supplemental Nutrition Assistance Program (SNAP) enrollment and unemployment rate. Ultimately, what we found was that the having more large farms in a county was correlated with higher SNAP enrollment and a higher unemployment rate, so an overall worse economy. On the other hand, having more crop diversity was correlated with lower SNAP enrollment and a lower unemployment rate, so an overall better economy. The exception to these general trends was dairy farms. We found that having more dairy cows per dairy farm was correlated with a very slight but still significant decrease in the unemployment rate. This seems to suggest that large crop farms are the farms driving the correlation between large operations and worse local economies. Possibly the most shocking thing we found in our analysis was more directly related to water quality. We found that an increase of only 1% in the percentage of farms that are large is correlated with a 14% decrease in river quality. It’s one of those things that takes a second to fully take in. Which I know because so far eight or ten people have asked me to repeat that statistic at least three times. It’s important to note that in our analysis we controlled for outside factors that influence an individual county’s SNAP enrollment, unemployment rate, and river quality. So, for example, if one county gains a Swiss Miss factory that provides jobs and helps lower unemployment, our analysis considers that and separates the effects of the Swiss Miss factory from the effects of farm consolidation and crop diversity. Beyond just the research, the LAKES program was an amazing experience. We had a blast and learned a lot, and they’re not even bribing us to say that.
Economics and Mathematics major at Indiana University