What can employment data tell us about the meat processing industry in the Pacific Northwest?

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Tim Delbridge

[updated 3/19/24]

Along with colleagues at Oregon State (NMPAN, OSU Clark Meat Science Center) and Blue Mountain Community College, I am a part of a USDA-NIFA funded project that aims to strengthen the development of the meat processing workforce in the Pacific Northwest. A lot of attention has been focused lately on the organization of the meat supply chain, and how regulatory structure and market concentration at the processing level affects market access for small scale beef producers and the resiliency of this part of the food system. This is an issue that impacts consumers, producers, and ultimately, the economies of rural communities. 

While our larger workforce development project involves some teaching infrastructure and curriculum design, I’ve been exploring the challenges that small-scale processors face in hiring and retaining staff, and how the experience of meat processing firms relates to broader economic trends. In this blog post, I’m going to provide some background on labor within the meat processing sector in Oregon, Washington, and Idaho that I shared at the Northwest Meat Processing Association annual meeting last Friday, and discuss in more detail how the available employment data provide insights into the challenges that our project seeks to address.

The exploratory analysis presented in this post is based on a combination of data, including the Oregon Quarterly Census of Employment and Wages (QCEW) and unemployment insurance records managed by the great team at the Oregon Employment Department (OED), and individual wage record data managed by the US Bureau of Labor Statistics (BLS). These data and results are not official OED or BLS releases and are intended for exploratory research only. There are five key conclusions I’d like to share.

1. The number of meat processors and meat processing employees has been rising in recent years, and this growth has largely come from small firms. Figure 1 shows the number of meat processing firms in Oregon by year, with firms with 10 or fewer employees represented by the darker color in the stacked bar chart. The yellow line shows the number of total meat processing employees in the state and shows significant growth in the last 15 years.

Figure 2 shows the upward trend in meat processing employment at the regional level. The increase in Oregon is matched by similar increases in Idaho and Washington, and closely mirrors the rate of growth in the overall labor force in the Pacific Northwest.

2. Meat processing wages have risen significantly in recent years. Figure 3 shows the average hourly wage rate paid by Oregon meat processing firms, along with hourly wages by firms in commercial and residential construction. This figure highlights the fact that not only have wages been increasing rapidly in many industries in recent years, but meat processing wages have “caught up” to those in industries that often compete for workers. The fastest wage increase in meat processing occurred in 2020 during the height of the Covid pandemic, and did not come back down after serious infections declined in number and supply chains recovered.

3. Retention seems to have gotten harder. Despite the higher pay, the meat processing industry in the Pacific Northwest has been able to retain fewer of the employees that leave their jobs. Based on individual employment histories contained in the BLS wage records, figure 4 shows the industry retention rates for two cohorts, those leaving their jobs in 2013 and those leaving in 2018. Among employees separating from their employers in 2013 (represented by the dashed lines), between 54% and 60% were working in meat processing in the PNW two years later. Among those that left their jobs in 2018 (solid lines), between 45% and 50% were still working in meat processing after two years. Again, while some of this may have been caused by the Covid pandemic, these workers did not return to the industry.

4. When employees leave their meat processing employers, they appear to do so for higher hourly pay, though they might not earn more in total wages. Figure 5, also based on the individual wage records managed by the BLS, shows that workers that left their meat processing employers generally tended to earn higher hourly wages in the same quarter in the subsequent year. This shouldn’t be surprising, as higher pay is a common reason to take a new job. However, figure 6 shows that overall wages go down, on average, after leaving meat processing. This seems to suggest that many employees are leaving the industry for higher paying jobs in which they work fewer hours.

[Note: From what I’ve heard from my colleagues in NMPAN and the NWMPA, this conclusion runs counter to the experience of many small scale processors. It is important to point out that a close look shows that the average hours worked before leaving a meat processing employer are high (close to full time) and well above the average hours worked by employees at small processors (see figure 7). Moreover, the BLS queried these data for the 4th quarter of each year, which is a particularly busy time for the industry. Further analysis is needed to determine if this trend holds for firms of all size and if results would look similar in all seasons, or if these averages are dominated by employees leaving large meat processors and numbers are skewed by big fourth quarter pay checks.]

5. All size classes show seasonality in terms of hours per worker per week, though workers for larger firms work more hours on average. The third and fourth quarters of the year (July through December) are traditionally the busiest times for meat processors. Figure 7 shows that in these quarters, the hours worked per employee are higher than in quarter 1 and 2, and that this holds for small, medium, and large meat processing firms. Interestingly, workers for larger firms tend to work more hours in all quarters than those at smaller firms. This likely indicates that small-scale processors rely more on part-time workers, and/or that they struggle to keep volume high enough in Q1 and Q2 to fully employ their staff, thereby contributing to retention challenges.

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