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Farmer and farm worker illnesses and deaths from COVID-19 and impacts on agricultural output

That’s the title of a new paper I’ve coauthored with Ranveer Chandra that was just released by the journal PLOS ONE. The paper builds off the Purdue Food and Agricultural Vulnerability Index dashboard we released last spring, but the paper includes estimates for COVID-19 cases and deaths for different types of farm workers and includes estimates of aggregate economic effects to the agricultural sector. Here’s the abstract:

Farmers and farm workers are critical to the secure supply of food, yet this population is potentially at high risk to acquire COVID-19. This study estimates the prevalence of COVID-19 among farmers and farmworkers in the United States by coupling county-level data on the number of farm workers relative to the general population with data on confirmed COVID-19 cases and deaths. In the 13 month period since the start of the pandemic (from March 1, 2020 to March 31, 2021), the estimated cumulative number of COVID-19 cases (deaths) was 329,031 (6,166) among agricultural producers, 170,137 (2,969) among hired agricultural workers, 202,902 (3,812) among unpaid agricultural workers, and 27,223 (459) among migrant agricultural workers. The cases amount to 9.55%, 9.31%, 9.39%, and 9.01% of all U.S. agricultural producers, hired workers, unpaid workers, and migrant workers, respectively. The COVID-19 incidence rate is significantly higher in counties with more agricultural workers; a 1% increase in the number of hired agricultural workers in a county is associated with a 0.04% increase in the number of COVID-19 cases per person and 0.07% increase in deaths per person. Although estimated new cases among farm workers exhibit similar trends to that of the general population, the correlation between the two is sometimes negative, highlighting the need to monitor this particular population that tends to live in more rural areas. Reduction in labor availability from COVID-19 is estimated to reduce U.S. agricultural output by about $309 million.

A couple key graphs are below.

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And,

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COVID-related papers

A year after the onset of the pandemic, research on impacts of COVID-19 on food and agricultural markets continues. Below are some links to some papers I’ve co-authored that have been recently released.

Unscrambling U.S. egg supply chains amid COVID-19 with Trey Malone and Aleks Schaefer in Food Policy.

Abstract: This article investigates how the shift from food-away-from-home and towards food-at-home at the onset of the COVID-19 pandemic affected the U.S. egg industry. We find that the pandemic increased retail and farm-gate prices for table eggs by approximately 141% and 182%, respectively. In contrast, prices for breaking stock eggs—which are primarily used in foodservice and restaurants—fell by 67%. On April 3, 2020, the FDA responded by issuing temporary exemptions from certain food safety standards for breaking stock egg producers seeking to sell into the retail table egg market. We find that this regulatory change rapidly pushed retail, farm-gate, and breaking stock prices towards their long-run pre-pandemic equilibrium dynamics. The pandemic reduced premiums for credence attributes, including cage-free, vegetarian-fed, and organic eggs, by as much as 34%. These premiums did not fully recover following the return to more “normal” price dynamics, possibly signaling that willingness-to-pay for animal welfare and environmental sustainability have fallen as consumers seek to meet basic needs during the pandemic. Finally, in spite of widespread claims of price gouging, we do not find that the pandemic (or the subsequent FDA regulatory changes) had a meaningful impact on the marketing margin for table eggs sold at grocery stores.

Meat Demand Monitor during COVID-19 with Glynn and Shauna Tonsor in Animals.

Abstract: Meat products represent a significant share of US consumer food expenditures. The COVID-19 pandemic directly impacted both demand and supply of US beef and pork products for a prolonged period, resulting in a myriad of economic impacts. The complex disruptions create significant challenges in isolating and inferring consumer-demand changes from lagged secondary data. Thus, we turn to novel household-level data from a continuous consumer tracking survey, the Meat Demand Monitor, launched in February 2020, just before the US pandemic. We find diverse impacts across US households related to “hoarding” behavior and financial confidence over the course of the pandemic. Combined, these insights extend our understanding of pandemic impacts on US consumers and provide a timely example of knowledge enabled by ongoing and targeted household-level data collection and analysis.

Food Consumption Behavior During the COVID-19 Pandemic with Lauren Chenarides, Carola Grebitus and Iryna Printezis in Agribusiness

Abstract: We conducted an online consumer survey in May 2020 in two major metropolitan areas in the United States to investigate food shopping behaviors and consumption during the pandemic lockdown caused by COVID‐19. The results of this study parallel many of the headlines in the popular press at the time. We found that about three‐quarters of respondents were simply buying the food they could get due to out of stock situations and about half the participants bought more food than usual. As a result of foodservice closures, consumers indicated purchasing more groceries than normal. Consumers attempted to avoid shopping in stores, relying heavily on grocery delivery and pick‐up services during the beginning of the pandemic when no clear rules were in place. Results show a 255% increase in the number of households that use grocery pickup as a shopping method and a 158% increase in households that utilize grocery delivery services. The spike in pickup and delivery program participation can be explained by consumers fearing COVID‐19 and feeling unsafe. Food consumption patterns for major food groups seemed to stay the same for the majority of participants, but a large share indicated that they had been snacking more since the beginning of the pandemic which was offset by a sharp decline in fast food consumption.

Who practices urban agriculture? An empirical analysis of participation before and during the COVID‐19 pandemic with Lauren Chenarides, Carola Grebitus and Iryna Printezis in Agribusiness

Abstract: Coronavirus disease‐2019 (COVID‐19) disrupted the food system motivating discussions about moving from a dependence on long food supply channels toward shorter local supply channels, including urban agriculture. This study examines two central questions regarding the adoption of urban agriculture practices at the household level during the COVID‐19 pandemic: whether the outbreak of the novel coronavirus elicited participation in urban agriculture (e.g., community growing and home growing) and what are the characteristics of individuals who participate. To answer these questions, we conducted two online surveys in Phoenix, AZ, and Detroit, MI. The first round occurred during 2017 and the second during the lock‐down in 2020. Using bivariate probit models, we find that (1) considerably fewer individuals participate in urban agriculture at community gardens compared to at‐home gardening; (2) participation overall is lower in 2020 compared to 2017; and (3) respondents in Detroit practice urban agriculture more than respondents in Phoenix. Across both cities, our results suggest that the continuity of individuals' participation in growing food at community gardens and home is fragile. Not all characteristics that determined who participated in community gardens before COVID‐19 are determining the likelihood to participate during the pandemic. In addition, growing food at home before COVID‐19 was practiced by larger households and employed respondents, yet, during the pandemic, we find that home‐growing was more likely when children were in the household and households were smaller and younger (Detroit), and younger and more educated (Phoenix). These findings suggest that many urban households' food‐growing practices may not yet be mainstream and that other barriers may exist that inhibit households' participation.

Food and Ag Sectors are Viewed Very Positively

I recently ran across this Gallup poll result from the fall. The main result is that the industries viewed most positively by the public are all related to food. Survey respondents were asked, “for each of the following business sectors in the United States, please say whether your overall view of it is very positive, somewhat positive, neutral, somewhat negative or very negative. How about …”

Farming and agriculture were on top, with 69% being positive and only 11% being negative, yielding a net positive of 58%. The next highest industries were both related to food: grocery and restaurants. Moreover, farming and agriculture gained 11 points in positive rating from the last time the Gallup ran the survey in 2019.

Over the weekend, I tweeted out the figure below, and it got a lot of attention. Many farmers get frustrated by consumers lack of knowledge about farm practices and technology, and many actors in the food and agricultural sectors often feel beleaguered by criticisms aimed at the industry. These poll results seem to suggest that, on the whole, food and farming are viewed quite positively. While there are certainly topics where consumer education and engagement will be useful, there seems little reason to have an overall defensive stance, and rather the results suggest a fair amount of social capital is built up that could be leveraged for the industries to take a leadership role.

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The slowdown in agricultural productivity growth and its causes

Agricultural productivity growth sounds rather boring and arcane, but it is perhaps the most important concept related to the health of the food and agricultural economy. At a basic level productivity growth occurs when the growth in all agricultural outputs exceeds the growth in use of all inputs. Crop yields are a partial measure of productivity growth - it measures one output (e.g., corn bushels) divided by one input (acres of land), but what economists really focus on is TOTAL factor productivity growth (all outputs and all inputs). Total factor productivity growth is intricately linked to sustainability, farm profitability, farm labor, consumer food prices, and more.

Phil Pardey and Julian Alston have written a new paper entitled “Unpacking the Agricultural Black Box: The Rise and Fall of American Farm Productivity Growth” that was just released by the Journal of Economic History. If you read one paper on trends and causes of agricultural productivity growth in the United States, this should probably be it. It is packed full of interesting data and discussion.

The key phenomenon they identify and attempt to explain is the following:

... we present robust and compelling evidence of a structural slowing of productivity growth in U.S. agriculture, following a mid-century surge ... [R]ather than a constant rate of productivity growth the data are more consistent with a “big wave” surge in productivity growth peaking in the 1960s; a secular pattern in U.S. agricultural productivity similar to what others have found with reference to the economy as a whole, but with different timing

Pardey and Alston provide a number of interesting figures related to these phenomena; here is one related to adoption of different technologies over time.

Source: Pardey and Alston, Journal of Economic History, 2021

Source: Pardey and Alston, Journal of Economic History, 2021

Here is a bit from their conclusions:

At issue in many minds is whether anything like the rapid growth in measured farm productivity during the third quarter of the twentieth century could be recaptured in the coming decades. Was this productivity surge (and the subsequent slowdown) a one-time phenomenon, or something that can be repeated with new waves of innovation in genetics, informatics, and robotics, which can save on costs of labor (which remain stubbornly large as a share of total costs) or other increasingly scarce inputs—especially land and water? More concisely: What might have accounted for the surge and slowdown in American farm productivity?

To address these questions, we examined three alternative (albeit related and not entirely mutually exclusive) explanations for the surge slowdown phenomenon.

Those three explanations are:

  • A decline in investments in agricultural research and development and the slowing growth in knowledge stocks;

  • A “big wave of technological progress through the middle of the century contributed to a sustained burst of faster-than-normal productivity growth throughout the third quarter of that century” (see the figure above); and

  • “the dynamics of the structural transformation of the U.S. farm economy and the role of asset fixity” … “This structural transformation involved a one-time shift, to reduce the number of farmers and the total farm labor force by two-thirds or more”

Do read the whole thing.

Where are people most sensitive to changes in the price of bacon?

Whether trying to understand the impact of taxes, animal welfare regulations, or meat packing plant shutdowns, we need an elasticity of demand for pork. The elasticity of demand tell us how the quantity of pork consumers want to buy changes with the price of pork. Given the importance of such questions, it probably isn’t surprising to learn that there are many studies aiming to measure elasticties of demand. These studies typically focus on THE elasticity of demand for pork - a single aggregate number. However, these aggregate assessments likely mask a great deal of heterogeneity across markets and different products.

In some new research with Glynn Tonsor, done for the National Pork Board, we utilized grocery store scanner data from 51 U.S. retail markets for 6 different pork products to estimate 51*6 = 306 market- and product-specific own-price elasticity estimates. Our data also enables us to observe differences in consumer purchasing and spending patterns across the country.

There are so many interesting results, it’s hard to succinctly summarize. Here are a few highlights.

First, consider variation in bacon purchases across four markets over time. Of the four locations in the figure below, per-capita bacon purchases tend to be highest in Phoenix and lowest in LA (it is worth noting that bacon prices tend to be much higher in LA than Phoenix). The impact of the initial COVID-19 disruptions is also apparent in the data.

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There is wide variation in price sensitivity across location and pork product. The figure below summarizes the distribution of price elasticities over the 51 markets for the six pork products

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Want to know how your locale ranks in terms of consumption, prices, or elasticity? Check out the full report.