OSU Applied Economics Outreach Blog

On January 1^st, the Oregon agricultural overtime threshold dropped from 55 hours per week to 48 hours per week, as required by 2022 HB4002. Agricultural employees are now entitled to 1.5x pay for hours worked that exceed 48 hours in a week. On January 1^st, 2027, the overtime threshold will fall to 40 hours per week. Oregon follows California and Washington in implementing similar ag overtime policy, and those states are now fully phased in to a 40-hour per week threshold. There has been plenty written on this topic in the popular press but there hasn’t been much analysis of the impact of ag overtime on farm profitability or worker pay.

In this blog post, I share analysis that my OSU colleague Jeff Reimer and I recently completed on the impacts of agricultural overtime in Oregon using farm-level payroll data from Oregon dairy, cherry and nursery producers¹. We find that agricultural overtime will negatively affect farm profitability and, perhaps surprisingly, will decrease the weekly earnings of some farm workers. This analysis is valuable in large part because it is based on individual records of (anonymous) employee hours and wages that are not usually available to researchers.

How will labor costs change for farms?

Farm businesses face seasonal fluctuations in their labor needs, and these fluctuations differ by  commodity group. Using the provided payroll records from 2022 to 2024, we calculate the total number of hours for which each operation would have paid overtime under each of the three overtime thresholds (i.e. 55, 48, and 40 hours) had they been in place. Figure 1 shows the number of overtime hours by week for one of the cherry producers (Panel A), one of the dairy producers (Panel B), and one of the nursery producers (panel C). The seasonal fluctuation in labor demand that is apparent in the figure will be largely similar across operations in the same sector. The figure shows that cherry producers have a large spike in their labor needs during the harvest in June and July, but will have relatively few overtime hours the rest of the year. The dairy and nursery businesses, on the other hand, both have peak seasons (summer for dairy, early spring for nursery) but have employees working more than 40 hours per week in all seasons. Employees at dairy farms in particular tend to have a high average number of hours per week. As a result of these sector-specific patterns, the impact of new agricultural overtime laws will land differently on each farm type.

Figure 1. Overtime Hours by Week Under Different Overtime Thresholds (Jan. 2022 – Nov. 2024)

To estimate the financial cost of ag overtime to farms and the impact to the wages of individual workers, we use each employee’s actual wage rates and hours worked by week from 2022 to 2024. We calculate the gross wages that they would have earned during the period under a no-overtime scenario, as well as each of the three overtime thresholds outlined in Oregon House Bill 4002. Wages under the three overtime thresholds are calculated for all employees in all weeks and then converted to percentage increases relative to the no-overtime baseline wage. For example, an employee working 50 hours in a particular week and earning a base wage of $18 per hour would see a 0% increase in wages at the 55-hour threshold, a 2% increase in wages at the 48-hour threshold, and a 10% increase in wages at the 40-hour threshold.

The estimated percentage increases in labor costs are averaged across farms in each commodity group and are presented in table 1. Of the three agricultural sectors, the dairy employees work the highest number of hours per week over the course of the year and have the highest anticipated overtime costs at each threshold level, with total wages increasing approximately 7% and 12% under the 48 hour and 40-hour thresholds, respectively.

The cherry producers see a smaller increase in labor costs than the dairy farms, but a slightly larger increase than nursery crop producers. On average, the nursery crop producers included in this analysis would see an estimated increase in labor costs of slightly more than 4% under the 40-hour overtime threshold. It is important to note that all farming operations are unique, and differences in crop mix, farm size, and production factors such as weather may result in fluctuations in overtime hours from year to year and from one farm to the next.  

Table 1. Estimated percentage increase in labor costs at each overtime threshold, by sector

The estimated percentage increases in labor expense that we estimate for each overtime threshold should not be confused with the percentage impact to net farm income. Since crop and livestock enterprises vary in terms of labor intensity and net profit margins, an equal percentage increase in labor costs will impact some farms more substantially than others. For example, based on a 2022 Oregon State University crop budget for sweet cherry production, a 10% increase in costs associated with pruning and harvest labor would amount to an additional cost of $380 per acre, representing a 30% reduction in net income to cherry production (Thompson and Seavert, 2022). That is, a small percentage increase in labor costs can have a large impact on the profitability (and financial sustainability) of farm businesses.

How will overtime legislation impact the pay of individual workers?

Increasing earnings for workers is a key goal of agricultural overtime legislation. Although workers that receive overtime pay of 1.5 times their base wage rate are likely to see an increase in their average hourly wage, it does not necessarily follow that the total earnings will be higher for individual workers under the new rules. With agricultural overtime laws in place, farm managers have a strong incentive to organize work schedules in a way that minimizes overtime costs, and this may include reducing the hours per week that an employee works. In fact, data on farm worker employment from the Bureau of Labor Statistics (BLS) show that the average number of hours worked per week per employee has fallen in California relative to the nationwide averages, just as their ag overtime policy phased in (USDA-NASS, 2024; Figure 2).

Figure 2. Average Hours Worked Per Week by Farm Workers

Among the Oregon farms that have provided both 2022 and 2023 payroll data for use in our analysis, some have shifted work schedules to reduce overtime pay. Table 2 shows the impact of the 55-hour overtime threshold on employees of one of the Oregon dairy farms that provided data. This table shows five employees that: 1) averaged more than 55 hours of work per week in 2022, 2) were paid hourly in each year, and 3) were employed by the farm for the full two-year period. Each of these employees worked fewer hours in 2023 and earned less in total wages in 2023 than in 2022, despite the higher average hourly wage earned as a result of overtime pay. This result is consistent with the conclusions of Hill (2023) and Hill and Tanabe (2023), which used the National Agricultural Workers Survey to show that average weekly earnings fell for many employees following implementation of agricultural overtime in California.

Table 2. Average Weekly Wages and Hours Worked for Five Individual Employees in 2022 and 2023

Not all farm managers that contributed data for this analysis reduced the number of overtime hours that their staff worked in 2023 and 2024, though the pressure to minimize costs has led them to take other steps. Some operations have reduced year-end bonuses, or report feeling less pressure to increase the base-wage rates of employees that now earn overtime pay. Some operations have few workers that exceed 55-hour work weeks and have not yet made adjustments, but anticipate the need to make substantial changes to comply with the 48-hour threshold that started on January 1, 2025.

Farms will face strong pressure to minimize labor costs for their own financial survival, while also feeling pressure to provide enough work to retain their skilled, and often long-term employees. Producers of dairy and nursery crops face significant competition from low-cost states without agricultural overtime laws and will be unable to pass on cost increases to consumers. The cherry industry is concentrated in states that also have ag overtime laws, which presents a more level playing field, but the industry as a whole is already struggling with profitability challenges. On the employee side, we should expect some farm workers to seek second jobs, which may be with other farms, or outside of agriculture. In any case, this is likely to be a period of disruption in Oregon agriculture.

1. We thank the farm owners that generously shared data with us for this analysis. Funding for this work was provided by Columbia Gorge Fruit Growers, the Oregon Association of Nurseries, the Oregon Dairy Farmers Association, the Oregon Farm Bureau, and the Agricultural Experiment Station of Oregon State University. ↩︎

References:

Hill, A. and T. Tanabe. 2023. Potential Impacts of Overtime Laws for US Crop Workers. Choices, 38(2).

Hill, A. 2023. California’s Overtime Law for Agricultural Workers: What Happened to Worker Hours and Pay? ARE Update. Vol. 27, No. 1.

Thompson, A, and C. Seavert. 2022. Enterprise Budget: Cherries, Sweet, Fresh Market. Oregon State University. AEB 0069.

USDA-NASS. 2024. Farm Labor. Available at: https://usda.library.cornell.edu/concern/ publications/x920fw89s?locale=en

Rising food prices seem to be on everyone’s mind these days. Consumers are frustrated that prices have not come down from pandemic levels, even after the reasons for those cost increases seem to have abated. Food price inflation has slowed this year according to official CPI numbers, but consumers still perceive prices to be increasing quickly. The proposed merger between Kroger and Albertsons highlights the growing concentration in the food retail sector, and the proposal has generated concern among the public as well as federal regulators. Here in Oregon, the merger would result in the sale of 60 Kroger stores to C&S Wholesale Grocers. In the last week, the issue was further elevated when food prices were brought up by the Kamala Harris campaign and the idea of a federal ban on price gouging was floated.

Since I spend most of my time working on issues related to farm production and profitability in Oregon, for me, the discussion of food prices always leads back to the relationship between the prices that consumers face at the grocery store and the prices that Oregon farmers and ranchers receive for their products. The ‘price spread’ is the difference between what consumers pay at the store and what farmers receive. This gap covers the costs of processing, shipping, marketing, and any profits made along the way. An increase in the price spread could be caused by an increase in the cost of shipping, increased labor costs among processors, increased cost of regulatory compliance, or an increase in the profits generated by processors and retailers.

The degree to which retail prices filter down to the farm sector also depends on market power and concentration at the processing and retail levels. For example, if a competitive meat processing market became a monopoly overnight, we would expect the price spread for meat to increase because the processor would be able to charge higher prices while passing relatively little on to beef producers.

This blog post will use historical beef price data to discuss the changes in the retail-farmgate price spreads and farm share of the retail food dollar over time. Beef is a good example because cattle production is spread across many small beef producers, processing is concentrated largely in the hands of four very large firms, and recent increases in meat prices are often a source of consumer complaint. While this type of simple analysis cannot identify the specific reason for a change in the farm-retail price spread in a given quarter or year, it can reveal the degree to which food expenditures are captured by supply chain steps downstream from the farm. It can also be helpful when thinking about the impact that further consolidation might have on the food prices and farm profitability.

These figures, based on USDA-ERS meat price data, show the price spreads and farm share of the food dollar for beef. Price spreads for other commodities are available here. For the beef industry in particular, the value captured by processing, distribution, and retail has increased by a factor of 15 over the past 5 decades. The farm share of the retail beef dollar has fallen from 65% to about 45%, dipping below 35% during the pandemic. Although it is difficult to generalize, these charts can help us put the current discussion about market power and food prices into perspective.

I think there are three main conclusions to make.

1. The Covid years were very difficult for some sectors. Meat processing provides a perfect example of a Covid-related capacity constraint that temporarily changed the relationship between producers and processors and led to high retail prices (see Lusk et al., 2021 for more detail). As meat processing facilities reduced throughput because workers were sick or to comply with health and safety protocol, the volume of meat being processed fell, driving down average farmgate prices. In other agricultural sectors, shipping costs, input prices, and labor costs increased rapidly, and the processors/distributors share of the food dollar increased.
2. In the case of beef at least, the farm share of the food dollar has recovered in the last year or two as the pandemic has faded and supply chains have normalized. Cattle inventories are currently at historically low levels and many beef processors are struggling to maintain their desired production volumes. This should not be taken as a conclusion that there is not significant market power in meat processing, but the market dynamics currently give beef producers a stronger hand in the market. We may see price spreads adjust downward again as cattle inventories return to more typical levels.
3. The farm share of the food dollar will look different for commodities like beef, milk, and potatoes than it will for highly processed foods. Intuitively, the supply chain costs for highly processed foods are much higher than for “whole” foods. As diets have incorporated more highly processed foods, farm revenues have increased at a slower rate than food sales. It remains an open question whether or not the farm share of the overall food dollar will shrink further, or if we have reached a point of stabilization.

Further Reading: This is a huge topic and there is a lot of academic literature that has addressed food prices, market power, and the consolidation in the modern food system. A few interesting academic works and other resources are below:

• Ma et al., 2017: An article about market power in grocery, which reminds us that market power can also exist at the neighborhood level.
• Howard, P. H. 2016. Phil Howards book “Concentration and Power in the Food System: Who Controls What We Eat?” is not an economic approach to this topic, but he presents an interesting viewpoint and does rigorous work. There are some excellent figures.
• Raw data on retail food prices, rather than agricultural commodities are managed by the Bureau of Labor Statistics. They can be found here.

I spent most of last week traveling in Eastern Oregon to speak with livestock producers, and the subject of Pasture, Rangeland, Forage (PRF) insurance came up in conversation. It is clear that PRF has become increasingly popular, and may even be impacting land prices and lease arrangements for grazing land. In this blog post I will discuss some basic information about the PRF insurance product and share participation and loss ratio outcomes for Oregon. Later in the post, I link to a spreadsheet that contains more detailed county level data on PRF participation, premiums, and payments.

The PRF insurance program is designed to help livestock producers manage the risk of poor forage production. It is essentially a rainfall “index insurance”, meaning that neither the insurance premiums nor the insurance payouts (known as “indemnities”) depend on the management or production outcomes of the individual producer. Rather, the premiums and payouts of the PRF program are based on monthly rainfall totals in a specified grid location. This type of index insurance has the advantage of low administration costs, as farm-level yields and losses do not need to be verified before payouts are made. The drawback is that the forage production on individual pastures may not be highly correlated with the rainfall index for the larger grid, which weakens the effectiveness of PRF as a risk management tool for individual ranches.

Livestock producers are eligible to insure at coverage levels up to 90% of the expected precipitation amount and must choose how to distribute their coverage over the calendar year. Like other USDA crop insurance programs, PRF premiums are subsidized, with the subsidy percentage based on the coverage level chosen by the producer. For more detailed explanation of the purchase process, and for information on national PRF outcomes, please see this excellent article by Jay Parsons, John Hewlett, and Jeff Tranel.

PRF Insurance has become increasingly popular in Oregon. Figure 1 shows the number of acres insured under PRF from 2016 to 2024. Insured acreage has grown rapidly in the state, with roughly 17 million acres insured. There has been similar participation growth at the national level, with nearly 300 million acres insured in 2023 (USDA-RMA, 2024).

Producers that buy coverage under the PRF program will receive payments if the precipitation index is below the trigger level for the specified months. Given that recent years have been drier than average in much of the state, a large percentage of purchased PRF policies have resulted in indemnity payments. Figure 2 shows the average “producer loss ratio” for PRF coverage in each county in 2022. The producer loss ratio is defined as the insurance indemnity divided by the net premium paid by the producer (i.e. premium less the premium subsidy). For example, in Union County, the producer loss ratio is 2.26, meaning that for each dollar that the producer paid in PRF premiums, they received an average of $2.26 back in indemnity payments. This is close to the Oregon average producer loss ratio since 2016. A spreadsheet with county level PRF outcomes from 2016 to 2023 can be found here.

Because the PRF insurance is based on a rainfall index, the payouts are correlated with drought conditions. Figure 3 shows the drought monitor map for October 11, 2022. While not a perfect match, we can see that the areas in drought are more likely to receive higher payouts from PRF coverage.

Crop insurance is often viewed as a gamble, with farmers and ranchers wondering if the decision to insure will pay off. Looking at the map of producer loss ratios alongside the drought monitor map is a good reminder that this program is designed to reduce the financial risk posed by low rainfall and reduced forage production. A “good year” for forage is more likely to be a “bad year” for PRF insurance, and vice versa. Livestock producers should carefully consider how a year of poor pasture conditions will affect their revenues, and whether PRF insurance could help protect them from these outcomes. Also worth considering is that in Oregon and in the U.S. as a whole, in each year since 2016 producers have received more than they’ve paid in premiums.