Global adoption of porcine reproductive and respiratory syndrome–resistant pigs will have significant economic and market impacts

That’s the title of a new article I’ve published in the American Journal of Veterinary Research.

A couple months ago, the FDA approved the use of genetic engineering to gene edit pigs to make them resistant to a disease that has ravaged the industry for decades: porcine reproductive and respiratory syndrome (PRRS). Pork producers have a number of key questions and concerns about the new technology. One fear is that the technology will “flood the market” with pork and depress prices. Another concern is that consumers will reject the new technology, resulting in lower consumer willingness-to-pay for pork or trade barriers placed on countries that adopt. This paper addresses both concerns.

I constructed an economic model to calculate the potential economic impacts of the release of PRRS-resistant pigs using data on PRRS-prevalence rates and data pigs-per-sow-per-year and mortality rates of pigs in different PRRS health statuses, provided by the Pig Improvement Company (PIC) which is commercializing the PRRS-resistant pig. More specifically, a model linking hog supply to consumer pork demand in 6 global regions, Canada, China, Japan, Mexico, the US, and the rest of the world, was constructed and parametrized using pork production and trade statistics, published supply and demand elasticities, PRRS prevalence rates, and productivity metrics by PRRS health status. The model projects changes in pork prices, production, trade, and producer profits in each country. I model a scenario in which global adoption of PRRS-resistant pigs increases over a 10 year period, with PRRS-resistant pigs ultimately reaching 70% of the swine herd in adopting countries by the 10th year.

Consistent with many producers’ concerns, I find that adoption of PRRS-resistant pigs is projected to increase pork production and reduce pork prices. However, it is also the case that the increase in pork productivity and the concomitant reduction in marginal costs of pork production are sufficient to increase pork producer profitability despite lower prices. The new technology allows producers to sell more pork at a higher net margin. Net margins rise because although pork prices fall, marginal costs fall even more.

The results also suggest that although demand reduction and trade barriers can offset some of the benefits of the technology, it all depends on the magnitudes. For example, even in an extreme scenario where retail consumers’ willingness to pay for pork from locations adopting PRRS-resistant pigs falls by 10% in every location after initial adoption (i.e., before any productivity gains are fully realized), the demand reduction initially has a detrimental effect on profitability in most locations up until about year 5, when the beneficial productivity effects of additional adoption of PRRS-resistant pigs begins to outpace the effects of the 10% reduction in willingness to pay.

From the abstract:

“In the baseline scenario (70% adoption over 12 years), assuming no change in pork demand or additional cost of swine genetics, the marginal cost of production declines and pork prices fall while pork production increases in adopting countries by 11% in China to 7% in the US and Canada, and pork production falls in nonadopting countries. In the 15th year after initial adoption, profits for pork producers increase, ranging from $33/head in China to $15/head in Canada relative to preadoption baseline. Producers in the rest of the world, who are assumed not to adopt, are less profitable.”

There is a lot more in the paper, including discussions on additional benefits, risks, and costs of the technology.

Food Fight

I was excited to see that my colleague, Richard Sexton, a Distinguished Professor at UC Davis, has a new book hitting the shelves next month: Food Fight: Misguided Policies, Supply Challenges, and the Impending Struggle to Feed a Hungry World. Richard is one of the most respected agricultural economists in the world, and has consistently produced some of the most interesting and impactful work in the area of agricultural market structure and market power. His new book is well worth a read, and even where you disagree with is assessment on certain food policies, you’ll benefit from engaging with is arguments. Here is the publisher’s description:

“Society’s most basic challenge is arguably to produce and distribute enough food for its citizens. In 2023, 733 million people faced hunger and 2.3 billion were moderately or severely food insecure. Feeding a growing world population is becoming more difficult in the face of climate change, pest resistance to traditional treatments, and misguided government policies that limit how much food ends up on our plates. Policies to support biofuels, organic agriculture, local foods, and small farms and to oppose genetically modified foods all reduce food production on existing land. This leads to higher food prices, increased carbon emissions, and less natural habitat as cropland expands. Food Fight documents the challenges to adequately feeding the world in the twenty-first century and illustrates the ways in which contemporary food policies in the United States, Europe, and beyond imperil food security. Richard J. Sexton provides a window into the world of modern agriculture and food supply chains. He separates the wheat from the chaff to distinguish policies that will limit, or expand, the global food supply, and he explains how we can construct a food system that forestalls future hunger and environmental degradation..”

Innovation in Gene Editing and Plant Breeding

Yesterday I had the privilege of moderating a panel discussion focused on gene editing hosted by the Farm Foundation. The main speakers included:

• Allen Van Deynze, Ph. D., Director, Seed Biotechnology Center and Associate Director, Plant Breeding Center, University of California, Davis

• Richard Lawrence, Ph.D., Head of Genome Editing, Yield, Disease, and Quality Research, Bayer Crop Science

• Fan-Li Chou, Ph. D., Senior Vice President, Scientific Affairs and Policy, American Seed Trade Association

• Alison Van Eenennaam, Ph.D., Professor of Cooperative Extension in Animal Biotechnology and Genomics, University of California, Davis

You can watch the presentations and discussion here or at the video link below.

Measuring changes in supply versus changes in demand

I just finished up a new working paper with Glynn Tonsor that shows how to determine the extent to which a change in price (or quantity) results from a change in supply and/or demand. For some time, Glynn has been reporting updated retail demand indices for meat products. In this new paper, we show how to calculate an analogous supply index, which might provide a useful way to determine how much productivity is changing over time. The basic idea is that we want a way to separate changes in quantity demanded (or supplied) versus a shift in the demand curve (or the supply curve). We also show how the two indicies can be used to determine changes in consumer and producer economic well-being over time.

Here’s the motivation:

“In 2015, per-capita beef consumption in the U.S. reached a record low of 54 lbs/person, falling almost 20% over the prior decade from 2005 to 2015 alone (USDA, Economic Research Service, 2020). Why? Some environmental, public health, and animal advocacy organizations heralded the decline as an indicator of their efforts to convince consumers to reduce their demand for beef; others argued, instead, the change was a result of supply-side factors such as drought and higher feed prices (e.g., Strom, 2017). Per-capita beef consumption subsequently rebounded, and in 2018 was almost 6% higher than in 2015. Dramatic fluctuations in corn, soybean, and wheat prices in the late 2000s through the mid-2010s led to similar heated debates about whether and to what extent price rises were due to demand (e.g., biofuel policy and rising incomes in China) or supply (e.g., drought in various regions of the world) factors (e.g., Abbot, Hurt, Tyner 2019; Carter, Rouser, and Smith, 2016; Hochman, Rajagopal, and Zilberman, 2010; Roberts and Schlenker, 2013). These cases highlight the challenge of interpreting market dynamics and the need for metrics that can decompose price or quantity changes to reveal underlying drivers and consequences.”

We calculate the supply and demand indicies for a number of agricultural markets and time periods. First, consider changes in supply and demand in the fed cattle market since the 1950s, as shown in the figure below. The demand index trended positively from 1950 through the mid 1970s. The demand index peaked at a value of 204 in 1976, and it hasn’t been as high since. Demand fell through the 1980s and early 1990s before rebounding. Since 2010, the demand index has been at values just below the 1970’s peak. The supply index trend was positive from 1950 up till about 2000, but has been stagnant except for the past couple decades. Nonetheless, the 2018 supply index value is the highest of the entire time period since 1950. The figure shows a significant drop in the supply index that began in 2013 and bottomed out in 2015, which is likely a result of drought in the great plains and from high feed prices. The fact that the supply index dropped during this period while the demand index remained relatively flat helps provide insight into the debate discussed in the quote above.

One can also calculate changes in producer and consumer surplus over time. The following figure calculates the year-to-year changes. On average, from 1980 to 2018, producer surplus increased $2.7 billion each year and consumer surplus increased $0.58 billion each year. Despite these averages, there is a high degree of year-to-year variability. The largest annual change in producer surplus was $34 billion from 2015 to 2016; the largest decline in producer surplus was -$28 billion from 2013 to 2014.

Here’s how changes in the supply index compare for the three main meat categories. Chicken supply shifts have far outpaced that for hogs or cattle. The 2018 chicken supply index value is 380, meaning chicken supply is (380-100) = 280% higher than in 1980. By contrast, hog and beef supply are only 66% and 28% higher, respectively, than in 1980. These differences are likely explained by differential productivity patterns in these sectors. The rise in hog productivity since 2000 corresponds with a time period over which the industry became increasingly vertically integrated, increasingly mirroring the broiler chicken sector. The much longer biological production lags in beef cattle (which range from two to three years from the time a breeding decision is made until harvest) and less integrated nature of the beef cattle industry help explain the smaller increases in the supply index in this sector as compared to pork and chicken. We also show, in the paper, that these supply indicies correlate in intuitive ways with changes in factors like feed prices, drought, and aggregate U.S. agricultural total factor productivity.

One of the useful aspects of the supply and demand indicies is that they can be applied for highly disaggregated geographic units. To illustrate, we calculated U.S. county-level supply indicies. Here are the changes in U.S. supply indicies in the past couple years relative to 2000. Perhaps surprisingly, many areas of Ohio, Indiana, and southern Illinois have experienced negative corn supply shocks in 2016-2018 relative to 2000. The expanded geographical area of U.S. corn production (e.g more acres in the Dakotas) over this period helped mitigate national corn market effects of the adverse Eastern Cornbelt supply shocks. Note that corn yields and total production have increased significantly in many of the red counties over time, and this illustrates the importance of calculating a supply index rather than just looking at yield or production. The supply index gives us a feel for how much more (or less) is produced in 2018 relative to what we would have expected if the level of technology, weather, etc. were the same as in the year 2000.

There is a lot more in the paper.

Malthusian Inversion

I’ve noticed several articles in the past few weeks talking about slowing or even falling population growth. This article in the Economist discussed the fact that South Korea’s fertility rate is now below replacement level (i.e., fewer babies are being born than there are parents), and their figure shows the strong negative correlation between income (or GDP) of a country and a country’s fertility rate. The richer we get, it seems the fewer babies we want or need. Then, came this opinion article in the New York Times a couple days ago about the “Chinese Population Crisis,” in which Ross Douthat argues, “Unlike most developed countries, China is growing old without first having grown rich.”

We’ve all probably been adequately exposed to the concerns and problems associated with over-population from the writings of Malthus to Ehrlich’s Population Bomb. Less well appreciated are the benefits and costs associated with a falling population. For one take on the potential concerns, see this 2013 piece by Kevin Kelly entitled the “Underpopulation Bomb.” He states the problem as follows:

“This is a world where every year there is a smaller audience than the year before, a smaller market for your goods or services, fewer workers to choose from, and a ballooning elder population that must be cared for. We’ve never seen this in modern times; our progress has always paralleled rising populations, bigger audiences, larger markets and bigger pools of workers. It’s hard to see how a declining yet aging population functions as an engine for increasing the standard of living every year.”

A smaller population would no doubt produce some benefits. Probably the most obvious benefit is that a smaller population would lessen human’s demands on our environment and natural resources. There is already evidence of this de-materialization. Check out Andrew McAfee’s book More from Less, where he argues that technology has led us past peak demand for many natural resources.

Among the adverse consequences, however, of falling population is likely to be downward pressure on farm incomes. The Malthusian concern implied a large population that was incapable of sufficiently feeding itself. For humanity writ large, this outcome would have been a tragedy. Farmers (or at least land owners), however, would have likely benefited from this dire outcome. More people demanding more food would have driven up food prices, land prices, and farm income. Innovation and productivity growth, fortunately, prevented the hunger problems that would have accompanied a rising population.

One crude way to see whether population growth is out-pacing the effect of innovation is to look at the long-term trend in food and agricultural prices. Here is a graph I created based on USDA data on three major commodity crop prices over time. The long-term trend is negative, suggesting innovation has outpaced the effects of population and income growth.

Lower prices seems bad for farmers, but if they are able to sell more output using fewer resources, they also benefit (see this paper by Alston for some discussion on the farmer benefits and costs from innovation). Still, it is probably safe to say that farmers and the agricultural sector have largely come to expect a rising world population to support demand growth and offset some of the downward pressure on prices. Population projections suggest that expectation may not hold out into the future.

Indeed, research by my Purdue colleagues Uris Baldos and Tom Hertel suggests the effects of population on crop prices is likely to be much lower than what we’ve experienced in the past. They consider the effect of three factors on crop prices and production: population, income, and innovation. From 1960 to 2006, their findings indicate that the effect of innovation pushed down crop prices more than rising income and population pushed up prices, leading to an overall fall in prices, consistent with the graph above. What do they predict for the future based on expected trends in innovation, population, and income? Falling prices. They predict that, going out to 2050, the price increasing effects of population will be about half what they were from 1960 to 2006. Thus, rather than the Malthusian population bomb, we seem to be heading to a sort of Malthusian inversion.

It’s also important to note that population growth will be unevenly distributed across the world. Data and projections from the United Nations show very different anticipated population trends in low-, middle-, and high-income countries. Here is a figure I created based on their data. In 1950, population was 45%, 70%, and 82% lower than it is today in high-, middle-, and low-income countries. By 2010, the UN is projecting population will be 3%, 23%, and 220% higher in high-, middle-, and low-income countries.

The implications for U.S. farmers are many fold. For one, demand growth (at least from population growth) is likely to occur outside this country, highlighting the importance of trade. Within the U.S., rising income, and demand for quality, may play an increasingly important role in supporting farm incomes in the years to come. Finally, flat or declining population, along with innovation, have the potential to have positive environmental outcomes, and it will important to think about appropriate farm policy in light of these trends.