Farm stores, agritourism, and farm viability: An economic perspective on Oregon’s proposed farm store legislation

Posted on February 27, 2026 by Dan Bigelow

Oregon’s comprehensive land use regulations make it a national standard-bearer for farm and forest preservation. The centerpiece of this system is the adoption of urban growth boundaries, which set limits on where urban-scale development can occur. Outside these boundaries, privately owned farmland is under county jurisdiction, with much of it zoned for exclusive farm use (EFU) or mixed farm-forest (FF) use. Despite the name, a range of exempt or incidental non-farm uses, from farm dwellings and agritourism-oriented buildings to industrial facilities, have been permitted in these zones.

How the state should set guidelines for non-traditional use of these lands has long been a flashpoint in Oregon policy debates. Recently, the debate has centered around agritourism, which can encompass a range of activities, from u-pick apple orchards to hosting weddings, concerts and other events on farm properties.

One of the bills being considered in Oregon’s ongoing legislative short session is HB 4153, which seeks to clarify the legal use of farm stands on land zoned for exclusive farm use or mixed farm-forest use. The bill replaces the existing legal concept of a “farm stand” with new language centered around “farm stores”, and in doing so, effectively overhauls how income from agritourism and other activities on farmland is regulated.

Proponents of looser regulations around agritourism argue that allowing producers to diversify their income makes farms more financially resilient during difficult years (e.g., years with bad harvests or low commodity prices). They also argue that current rules, which regulate agritourism income directly, impose unrealistic and costly burdens on the local jurisdictions tasked with carrying them out. Opponents argue that vague, permissive legal definitions of allowable uses invite bad-faith interpretations, and that an expansive list of exempt non-farm uses represents a slippery slope that will gradually chip away at Oregon’s legacy of farm and forest preservation.    

Under current law, farms are unable to receive more than 25% of their total revenue from these sources. HB 4153 shifts the focus from income to the physical space occupied by structures used to facilitate this type of revenue, which represents a foundational change in how agritourism and related incidental uses are regulated.

The most recent version of HB 4153 lays out eligibility criteria based on tract size. Larger tracts face fewer restrictions, while tracts under 20 acres must demonstrate at least $10,000 in farm income over the previous two years. In all cases, the store structures are to occupy no more than 10,000 square feet of space.

Tract sizeLand used for farmingFarm income requirement
> 80 acres>= 45 acresNone
40-80 acres>= 25 acresNone
20-40 acres>= 15 acresNone
< 20 acres>= 10 acres>= $10,000 in pvs. two yrs.

Importantly, the bill, as currently written, treats farm stores as a “permitted use”, which essentially means that any store meeting the statutory criteria does not need discretionary county approval. Counties would have a more limited role in adopting “standards” related to things like parking and hours of operation, but would have minimal role in determining if an individual landowner can build a farm store. This is a notable contrast with how Oregon law treats agritourism events (e.g., festivals and weddings), which are subject to county authorization.      

The debate surrounding HB 4153 is contentious. One of the opposing arguments concerns the potential impacts on land values. I want to use the rest of this post to dive into what we know about how agritourism shapes farmland markets.  (For those without the time to read the rest of the post, I don’t find a strong link between agritourism growth and land price growth at the county level. But this may say as much about the limits of available data as it does about the underlying relationship.)

At a fundamental level, the value of farmland reflects the discounted stream (or present value) of income a landowner is expected to earn from it. A simplified version of this relationship is represented by the equation below. Anticipated income that will not be realized by the owner until a later date is discounted at some rate r.1 The fundamental land value equation involves two income sources: (1) annual returns (or profit) from the current use, agriculture (e.g., the net revenue from growing and selling crops and other farm outputs) and (2) anticipated returns from developing the land in the future at some hypothetical year t^{*}. For land that is remote and has little prospects of being developed soon (where t^{*} is usually many years away), (2) tends to be very small so the land value approaches what would be attributable to farm production only.

Current rules stipulate that no more than 25% of farm revenue come from agritourism or related non-farm activities. Assuming these rules are fully enforced, which is debatable, this effectively puts a cap on how these activities could affect land values. Using the above equation, if a farm that does not use agritourism starts offering hay rides in the fall to the full extent allowable under law, we can model this by multiplying (1) by 1.25. This is not a perfect analogy because land values reflect net revenues, whereas the current law regulates gross revenues (i.e., before costs are accounted for), so to do this accurately we’d have to account for differences in the costs of crop/livestock production versus hay rides.

HB 4153, as currently proposed, does not place any upper bound on how much could be earned from agritourism. If we assume that the establishment of an agritourism facility (i.e., a “farm store”) will take nothing away from what the operation would earn without agritourism, then agritourism can be thought of as boosting the net returns to the current use in a way that is proportional to agritourism profit. That is, by not restricting the revenue that could be earned from agritourism, this would raise the price of land that potential buyers of that land would pay, because the income they earn from it will be greater. It also increases the hypothetical net returns that could be earned from land in farm use because it preserves the option to invest in a farm store. This is the argument made by those who worry about agritourism raising land prices.

When we think about (1), the returns from farm production, we usually assume that landowners exert no influence over the price at which they can sell their output, which is determined by regional or global commodity markets. If we consider income from farm stores or agritourism, this assumption may not hold. If more and more operations adopt some form of agritourism, the size of the agritourism premium will start to degrade and the price will go down accordingly.

What do we actually know about how agritourism affects land prices? Unfortunately, very little. The reason is that data on agritourism adoption are not widely available. USDA collects information on agritourism practice use in the Census of Agriculture, but this tends to be quite limited, in that it doesn’t encompass all activities that might fall under the HB 4153 legislation. For example, a farm stand, where produce is sold directly to consumers, would not qualify as agritourism under the USDA definition. The USDA does track these direct-to-consumer sales separately, but these are also mixed in with other forms of direct sales, such as farmers markets.  

Nonetheless, there is potentially some value in looking at how agritourism growth, as reported in the Census, correlates with growth in land prices. The figure below splits Oregon counties into four groups based on whether they experienced above- or below-median growth in agritourism adoption (from the USDA Census) and in inflation-adjusted farmland prices over roughly the same recent period. Details on how these are calculated are in the figure note.

Note: The vertical axis represents the change in the percentage of farms participating in agritourism over the 2017 and 2022 USDA Censuses of Agriculture. The horizontal axis represents the percent change in inflation-adjusted acreage-weighted farmland prices over the 2015-2019 and 2020-2024 periods. Dashed lines represent median values across the 24 counties included in the plot (0.02 for agritourism growth and 22 for farmland price growth). *Denotes Jefferson County, for which the agritourism growth value is set to -2 to make the figure more readable. The true value for Jefferson County is -3.5. Counties with insufficient data are not included due to having fewer than 5 farmland sales in either of the 2015-2019 or 2020-2024 periods or not having an agritourism value reported in either the 2017 or 2022 Census. 

The figure does not reveal a clear correlation between land price growth and agritourism growth. Of the 24 counties with adequate data, the number of counties in each category are: 7 (high price-high agritourism; upper right quadrant), 5 (low price-high agritourism), 5 (high price-low agritourism), and 7 (low price-low agritourism). If we map the counties in these four categories, we again do not find an obvious pattern. Overall, this points to a weak positive correlation between recent changes in reported agritourism activity and land prices.

Note: The map categories are the same as those used in the previous scatter plot. Counties with insufficient data had either fewer than 5 farmland sales in either of the 2015-2019 or 2020-2024 periods or did not have an agritourism value reported in either of the 2017 or 2022 Census years. 

We find a similar pattern if we look at the change in number of farms that use agritourism (instead of the percentage of farms), use self-reported farmland value estimates from the Census (instead of observed prices), or drop the minimum sales acreage threshold down to 5 acres (from 10 acres). The bottom line is that the data don’t reveal a strong link between agritourism growth and land price growth at the county level. That said, the Census paints an incomplete picture of what most would consider agritourism, so that caveat should be kept in mind. They also don’t rule out more localized effects.

Of the counties with relatively high land price growth in recent years, about half had high and low agritourism activity. That’s not to say that HB 4153, if passed, would have zero effect on land prices. The prices of land in operations that do invest in a profitable farm store should go up. And given how unaffordable land is in general, anything that makes it more expensive could be viewed negatively, especially if the “farm stores” that end up being approved have little connection to farming and other rural land uses. But on the flipside, there is certainly some appeal in allowing producers to diversify their revenue stream by providing products and experiences that local consumers are willing to pay for.

Overall, though, I would say I would lean towards being skeptical of HB 4153 having far-reaching effects on the market for land more broadly. For that to occur, we would also need to see some sort of speculative effect, where potential land buyers are willing to pay a meaningfully higher price for the option to build a farm store. Alternatively, we would need to see buyers paying a premium to locate near newly established farm stores, perhaps due to the potential for agglomeration benefits of creating a denser network of farm stores. But this cuts against one of the main criticisms of agritourism, which is that it generates nuisances (traffic, noise, crowds) that create conflicts with neighboring operations. In other words, the same features that might make nearby land more valuable to one type of buyer could make it less attractive to another.

One of the main takeaways here is that agritourism is an extremely data-scarce area. In order to track things like land market impacts, we need more and better data on the extent of agritourism activity around the state. Regardless of which, if any, version of HB 4153 ends up being passed, I would advocate for tracking the establishment of farm stores over time. Good data is the bedrock of good policy and we’re otherwise left with tenuous arguments built around hypothetical scenarios that may not apply.

Note: Farmland price data come from proprietary data purchased from Cotality. All agricultural sales used in the figures satisfy the following criteria: (1) exclusively made up of agricultural parcels (per Cotality’s land use codes, which are adapted from county records), (2) at least 10 and less than 10,000 total acres, (3) outside urban growth boundaries at the time of sale, (4) at least 50% of the land is class I-VI soils, (5) price is between $100 and $75k per acre, (6) land is primarily zoned for agricultural use (Note: Five counties, Gilliam, Grant, Lake, Morrow, and Umatilla, do not have detailed statewide zoning data. In order to retain farmland sales from these counties, I also include county land in zones labeled “non-public” in my working definition of agricultural zoning.), and (7) involves fewer than 10 individual taxlots.

  1. Similarly, if you were to receive a dollar today, it would be worth less to you than the promise of a dollar in the future (because you could invest the dollar given to you today in a risk-free investment vehicle, like a Treasury security, and earn some positive rate of return on it by next year). ↩︎
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Oregon’s Business Dynamics: An Analysis of Entries and Exits (2012–2022)

Posted on January 7, 2026 by Richard Acquah-Sarpong

Understanding the churn of businesses – the rate at which new establishments open (entries) and existing ones close (exits) – is crucial for gauging how active and adaptable an economy is. A key indicator is the entry/exit ratio, which is the number of new establishments divided by the number of closures in a given period. An entry/exit ratio above 1.0 signifies net growth in the number of businesses (more openings than closures), while a ratio below 1.0 indicates net decline. This dynamic is important because new businesses contribute to innovation and job creation, whereas closures can signal economic stress or structural changes.

In recent years, Oregon has experienced remarkable shifts in these dynamics. After several decades of relatively low startup activity, the past few years have seen a general and widespread increase in new business formation. According to the U.S. Census Bureau’s Business Formation Statistics, 2023 marked another record year for new business applications in both the U.S. and Oregon – a surprising boom emerging from the economic uncertainty of the 2020 pandemic recession.

This blog post examines Oregon’s business dynamics through three lenses – time, sector, and geography – using data from the 2022 National Establishments Time Series Database. I discuss the annual trends in business entries and exits from 2012 to 2022, compare entry/exit ratios across industries, and map the ratio across Oregon’s counties.

Entry and Exit Trends Over Time (2012–2022)

Figure 1: Annual establishment entries (blue) and exits (red) in Oregon (2012–2022)
Data source: 2022 National Establishment Time-Series Database

Figure 1 illustrates Oregon’s annual business entries and exits over the past decade. The early 2010s show Oregon still recovering from the Great Recession’s aftermath – from 2012 through about 2014, exits outnumbered entries. From 2015 onward, Oregon experienced a sustained period in which new establishments consistently outpaced business closures. The COVID-19 pandemic in 2020 briefly disrupted this trajectory, resulting in a slight decline in the number of new establishments. This mirrors a national trend where, after the initial pandemic shock, the U.S. saw a wave of new business applications, with 2021–2022 far exceeding historical levels. According to data from the Bureau of Labor Statistics (BLS) Business Employment Dynamics, Oregon added around 18,950 new private payroll businesses in 2022, while roughly 16,600 businesses closed that year. Oregon posted the fastest growth in new establishments of any state in 2023, according to recent data released by the Bureau of Labor Statistics, Business Employment Dynamics.

Which Sectors Are Driving Growth?

The dynamics vary widely across industries. Figure 2 presents entry/exit ratios for Oregon’s major sectors over the period 2012–2022, illustrating which industries experienced net growth in establishments and which experienced net losses. Nearly all service industries in Oregon have ratios well above 1.0, indicating that far more establishments opened than closed in those sectors during the 2012–2022 period. The industry with the largest net gain is Public Administration. This sector comprises government establishments that perform legislative, judicial, and administrative functions for federal, state, tribal, and local governments. Roughly 2.8 new public-sector establishments opened for every one that closed during that time frame.

Figure 2: Entry/exit ratios by industry
Data source: 2022 National Establishment Time-Series Database

Among other industries, there is robust net expansion in areas like Administrative & Support Services (e.g., temp agencies, janitorial and waste management firms), Real Estate & Rental, Educational Services, Accommodation & Food Services, Health Care & Social Assistance, Arts, Entertainment \& Recreation, Transportation & Warehousing, and Professional & Technical Services. These sectors all exhibit entry/exit ratios of approximately 1.5 or higher (meaning 50% more openings than closures). For example, Oregon’s Hospitality sector (Accommodation & Food) shows about 1.79, reflecting the boom in eating and drinking places and hotels. In recent years, the fastest growth in new business formation nationally has been in industries like retail, food services, transportation, and professional services, each seeing roughly a 60% increase in new business applications just from 2019 to 2023.

A few sectors in Oregon have entry/exit ratios around or below 1.0, indicating net stagnation or contraction in the number of establishments over the 2012–2022 period. Several Manufacturing categories fall into this group: for instance, Manufacturing of Wood/Paper/Chemicals (ratio 1.02) and Manufacturing of Metals/Machinery/Electronics (1.00) both saw the same number of closures as openings. This is consistent with the long-run challenges for manufacturing – automation, globalization, and industry consolidation – which have led to fewer total factories and mills even as output in some areas rises.

Regional Variations: Entry/Exit Ratio by County

Figure 3 below highlights substantial variation in entry/exit ratios across Oregon. Many rural counties exhibit relatively low ratios. The pattern is more mixed across urban counties. Counties in the northern part of the state, particularly along and just south of the Columbia River, tend to have higher entry/exit ratios.

Figure 3: County-level variation in entry/exit ratios (2012–2022)
Data source: 2022 National Establishment Time-Series Database

Conclusion

Oregon’s trend in establishment entries and exits from 2012 to 2022 shows a surge in net business growth, but with significant variation across sectors and counties. Overall, the economy seems to be tilting toward services and innovation. The high entry/exit ratios in education, health, professional services, hospitality, and tech-related fields emphasize the growth of a service-driven economy. These sectors often benefit from population growth, changing consumer preferences, and lower barriers to entry (e.g., it’s easier to start a food cart than a lumber mill). In contrast, the few sectors with stagnant or declining establishment numbers tend to be capital-intensive industries or those facing long-run decline.

Policymakers should continue to nurture this entrepreneurial momentum. That means maintaining support for small businesses and startups through programs such as technical assistance and startup incubators, accessible financing (microloans, venture capital), and a reasonable regulatory climate that doesn’t pose undue barriers to entry. However, a good policy approach must also recognize the nuances behind the numbers. High entry counts are encouraging, but not all new businesses survive, and not all create substantial employment. In fact, evidence shows that a large share of job growth comes from the expansion of existing firms rather than new firm births.

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A recent snapshot of the land market for grass seed production in the Willamette Valley (Revised)

Posted on December 26, 2025 by Dan Bigelow

Revision: I encountered an error in the previous version of this post that affected the percentage changes shown in the maps in Figures 3 and 4. The error led to an understatement of the 2013-2019 average rent values. Basically, the USDA did not conduct a rent survey in 2015 and 2018, so there are only five years of valid rents during this period. In the previous versions of the figures, I had mistakenly taken the average rent over this period over 7 years instead of 5, which led to the 2013-2019 rental rates being artificially lower than they were in reality. Note that this only affected the percentage changes in rents and cap rates between 2013-2019 and 2020-2025, and not the main takeaways regarding land prices or the more recent 2020-2025 rents and cap rates. However, I regret the error and apologize to readers and audience members at the Oregon Seed Growers League meeting.

Earlier this month, I had the privilege of giving a presentation at the annual meeting of the Oregon Seed Growers League. My talk focused on the land market for seed growers in the Willamette Valley. In this post, I’m going to give a brief recap of what I presented at the meeting.

Grass seed is one of Oregon’s primary agricultural outputs, routinely ranking among the most valuable farm commodities produced in the state. Most of Oregon’s grass seed production occurs in the Willamette Valley, with the Grande Ronde Valley in Northeast Oregon also contributing to the state’s leading position in the seed industry.

After a boom during the Covid-19 pandemic, when many homeowners invested in their yards, the seed industry has grappled with a number of economic challenges. First, as the demand stemming from the pandemic died down, there was a significant oversupply of seed being brought to market, which pushed farm gate prices down. At the same time, a strong dollar made it difficult to market the crop overseas, in China, or to Canada. International trade conditions were not helped, at least in the near term, by the recent rounds of tariffs negotiations. Among other things, the costs of key inputs, including labor and fertilizer, have also risen substantially in recent years, squeezing already-thin profit margins.

The price of land for seed growers has not gotten any cheaper in recent years. Figure 1 plots the average price of an acre of land in grass seed/sod production using both a 12-month rolling average (in grey) and a smoothed trend line (in black dashes). Note that I classified parcels by land use with the USDA’s Cropland Data Layer, which combines grass seed and sod (or turf grass) into a single category, and retained all sales of at least 20 acres and where at least 25% of the land showed a grass seed/sod cover in any year. Turf grass production is a distinct, smaller industry, so I’m reasonably confident the numbers I show largely represent grass seed operations.

Between 2000 and 2025, the price of seed land doubled in inflation-adjusted terms, from $7-8,000/acre to about $15,000/acre.  The average price of land spiked during the pandemic before softening and then beginning to rise again slowly over the past year.

Figure 1: Price per acre of grass seed land in the Willamette Valley, 2000-2025
Note: The grey line is a 12-month rolling average of the per-acre price. The black dashed line is a smoothed version of the same trend line.
Source: Author’s calculations using real estate price data from Cotality.

Figure 2 shows average land prices by county for 2020-2025, with numeric labels representing the percentage change from the 2013-2019 period. Average current prices are highest in Washington and Clackamas, which is at least partly attributable to their close proximity to the Portland Metro area. Recent prices are at least $10,000/acre in all counties, however. The highest growth rates have occurred in Polk (38.9%) and Linn (37.5%), with Yamhill and Washington also seeing growth rates in excess of 30%.

Figure 2: Price per acre of grass seed land in the Willamette Valley
Note: Color shading corresponds to 2020-2025 average price, numeric labels refer to % changes since 2013-2019.
Source: Author’s calculations using real estate price data from Cotality.

Most of the parcels in the sample are for irrigated land, which sells for a premium compared to dryland. Cash rents are commonly used as an estimate of the net returns accruing to farmland owners. Although I do not have information on cash rents for seed operations, I approximated the typical seed cash rent using county-level irrigated and non-irrigated rent data from the USDA’s National Agricultural Statistics Service. For example, if the county’s irrigated rent is $200/acre and the non-irrigated rent is $100/acre, and 75% of the seed land sales are irrigated, the average seed rent is 0.75(200) + 0.25(100) = $175/acre.

According to this measure, current rents range from over $100/acre to nearly $350/acre (Figure 3). Rents have increased in all but one county between 2013-19 and 2020-25 (Figure 3). The exception is Benton, where rents have essentially remained flat. Current rents range from over $100/acre to nearly $350/acre. Yamhill stands out, with an average rent increase of more than 30%, while Polk, Marion, and Linn have registered per-acre rent gains of more than 10%.

Figure 3: Cash rent per acre for cropland in the Willamette Valley
Note: Color shading corresponds to 2020-2025 average rent. Numeric labels refer to % changes since 2013-2019. The rents referred to here are a weighted average of irrigated and non-irrigated rents from USDA-NASS with weights corresponding to the percentage of grass seed land sales with irrigation.
Source: Author’s calculations using cash rent data from USDA-NASS.

Putting this all together, Figure 4 shows the ratio of average rents to land prices over the same periods. This ratio is known as the farmland capitalization rate (or cap rate), and it can be a useful measure of the profitability of investing in land. Higher cap rates indicate a faster payback period for a land investment. Recent cap rates range from 0.9 to 2.1%, with the highest being in Linn, Marion, and Yamhill. Because land prices have risen faster than rents in most counties, cap rates have generally gone down. The two counties where rent growth has outpaced land price growth – Marion and Yamhill – have seen relatively small percentage gains in cap rates. For four of the eight counties, however, cap rates have decreased by double digits in percentage terms.

Figure 4: Capitalization rates for grass seed land in the Willamette Valley
Note: Color shading corresponds to the 2020-2025 average cap rate. Numeric labels refer to % changes since 2013-2019. Cap rate = rent/price using rents from Figure 3 and prices from Figure 2.
Source: Author’s calculations using cash rent data from USDA-NASS and real estate price data from Cotality.

Taking a wider view, current cap rates are quite small from an investment portfolio perspective, even for farmland. The cap rates I came up with are also slightly overstated because I did not adjust the rents for property taxes paid by the landowner. Between 2000 and 2025, the 10-year Treasury rate averaged about 3% and are currently above 4%. Treasuries are seen as a relatively safe investment asset and are about as close as you can get to a risk-free rate of return. To the extent that the rent estimates I showed are an accurate measure of average net farm income, the implication is that current farm income alone is not sufficient justification to purchase land.

Why then would anyone buy land? In addition to the prestige and intrinsic value associated with owning land, it may also bring additional streams of farm-related income (e.g., agritourism activities). Prospective buyers may also be betting on continued future appreciation, relying on off-farm income, using land as an inflation hedge, or, in the case of more experienced producers, seeking better lending terms through down payments and collateral.

Despite the general downturn the industry has faced as of late, the continued upward trend in grass seed land prices represents a significant gain in net worth for established producers who already own their land.  For a beginning farmer trying to cash-flow a land purchase, however, the math doesn’t pencil out on farm income alone, which exemplifies the core affordability problem for producers looking to build and grow a profitable farm enterprise.

Note: Farmland price data come from proprietary data purchased from Cotality. I determined sales involving land used in grass-seed operations using the following criteria: (1) at least 20 acres sold, (2) not inside urban growth boundaries, (3) at least 50% of the land is class I-VI soils, (4) price is between $100 and $75k per acre, (5) land is primarily zoned for agricultural use, and (6) at least 25% of the land has a grass seed cover between 2009 and 2024. Irrigated land is determined using a combination of Oregon Water Resource Department’s water rights database and remote-sensing data from LANID.

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The cost of regulatory compliance in Oregon agriculture

Posted on November 20, 2025 by Tim Delbridge

This week, colleagues Ashley Thompson (OSU-MCAREC), Mike McCullough (Cal Poly Agribusiness), and I published an article through OSU Extension on the regulatory costs faced by Oregon tree fruit growers.  In this project1, we carried out in-depth interviews with pear and cherry producers about the expenses that they incur to comply with state and federal regulations.

With work like this there is an understandable tendency to focus on the numbers – we estimate that the growers we interviewed spend between $250 and $700 per acre on regulatory compliance each year – but the value of this work is more than just a tabulation of costs. These expenses, such as the time that it takes to maintain records for food safety compliance or to participate in employee safety trainings, rarely make it into widely used enterprise budgets that estimate the profitability of crop and livestock production. Farmers themselves don’t typically have records of their regulatory costs because these expenses get classified as labor, or overhead; or, if the farm owner is doing the work, don’t get recorded at all.

The result is that neither the policy makers (who are working to maximize the public good by protecting the environment, workers, and the public) nor farmers are sure if they are making efficient decisions. My hope is that this article and our outreach efforts help farmers manage regulatory requirements in a cost-effective way that supports their long-term financial sustainability. I also hope that this report provides policy makers with a clearer picture of the costs incurred by Oregon’s agricultural sector to remain in compliance with existing regulation.

There is much more in the full article, so I encourage you to take a look. As always, feel free to reach out with questions or for more discussion.

tim.delbridge@oregonstate.edu

  1. Funding was provided for this project by the Oregon Department of Agriculture through the Specialty Crop Block Grant. ↩︎
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Comparing the latest USDA land value estimates with observed land prices

Posted on November 4, 2025 by Dan Bigelow

The U.S. Department of Agriculture (USDA) recently released its 2025 state-level data on farmland values. These estimates come from a survey in which producers are asked to report how much their land would sell for in a market transaction. As I describe in a recent OSU Extension article, the 2025 estimates indicate a small 0.4% real (inflation-adjusted) decline in farm real estate values overall, which measure the value of land and farm-related buildings combined. This amounts to the lowest annual rate of growth since 2013. Although it might be tempting to read it as evidence that Oregon’s farmland market may be stabilizing, it’s important to emphasize that the USDA’s values capture producer perceptions, or self-assessments, rather than observable market outcomes.

A while back I wrote a post that compared the self-reported USDA survey estimates to observed farmland prices. With newer data now available, this seems like a good opportunity to revisit that analysis and dig a bit deeper into why survey estimates differ from market prices. (Side note: Over the coming month or so, I’m expecting to receive another update that will allow our sales database to reflect sales through most of 2025.)

In general, market prices run considerably higher than survey estimates in a given year. This sometimes leads people to dismiss the USDA estimates as inaccurately capturing land market conditions. The estimates, however, come from surveys of producers, who, if anyone, should be well-informed about current market conditions. And it turns out that producers are actually pretty good at estimating the value of their land once we consider the population the USDA survey aims to capture.

Figure 1 plots the per-acre farm real estate (land and buildings) value from USDA for 2000-2025 against farmland prices over roughly the same period. The price trend, shown in light grey, represents a rolling 12-month average, updated monthly from January 2000 to July 2024 (the most recent month of sales data available). The smoothed black dashed line uses the same price data but makes it easier to distinguish the overall trend from month-to-month noise. This initial price trend uses 18,577 farmland sales at least 10 acres in size.

Figure 1: Trends in USDA land value estimates versus farmland sales, including all sales of at least 10 acres.
Figure 1: USDA land value estimates plotted against observed farm real estate sales prices (10+ acres). Total sales sample size = 18,577.

Across the 2000-2024 period, average market prices are $3,700 higher than the corresponding USDA survey estimate. Notably, this gap has widened in recent years, with the average difference being about $4,400 since 2019.

Although there are many small-acreage sales of farmland, involving 10 acres or less, these tend to inflate the overall price level because of the “small parcel premium” I’ve discussed before. When we raise the minimum sale area to 20 acres (Figure 2), we lose about 23% of the sales but the average gap between prices and survey estimates narrows to $2,800. Raising the threshold to 40 acres, which removes another 27% of the original 10+ acre sales sample, narrows the gap further to $1,700.

Figure 2: Trends in USDA land value estimates versus farmland sales, including all sales of at least 20 acres.
Figure 2: USDA land value estimates plotted against observed farm real estate sales prices (20+ acres). Total sales sample size = 14,253.
Figure 3: Trends in USDA land value estimates versus farmland sales, including all sales of at least 40 acres.
Figure 3: USDA land value estimates plotted against observed farm real estate sales prices (40+ acres). Total sales sample size = 9,450.

With a 100-acre threshold (Figure 4), we’re working with 23% of the initial sales sample, and the farmland price trend closely matches the USDA trend, at least in terms of its scale. On average, market prices are now just $284 greater than the USDA estimate, with several years where the USDA values actually exceed market prices. With the exception of the year or so, where the sales data are still incomplete, both measures of land value paint a consistent picture. I’m reluctant to read too much into the 2024 price spike until we have another year of complete sales data.

Figure 4: Trends in USDA land value estimates versus farmland sales, including all sales of at least 100 acres.
Figure 4: USDA land value estimates plotted against observed farm real estate sales prices (100+ acres). Total sales sample size = 4,227.

So why do the USDA values better reflect market prices for larger acreages? The reason is that the survey asks producers to report the market value of all land in their operation, not the market value of an individual 10-, 20-, or 40-acre parcel. According to the most recent USDA Census data from 2022, the average farm size in Oregon is 430 acres, though this varies widely from under 100 acres in some Willamette Valley counties to over 3,000 acres in parts of eastern Oregon. Excluding Clackamas County (38 acres), no other Oregon county has an average farm size under 40 acres. Put differently, although half of all sales involve parcels with a total area between 10 and 40 acres, the total amount of farmland on farms of that size represents a tiny fraction of Oregon’s farmland base, which is what the survey aims to capture.

Thus, the USDA survey estimates are best thought of as capturing, on average, what whole farms would be worth in a single market transaction. Farmland markets are thin to begin with, and there are very few actual sales that involve the types of acreage the USDA survey is designed to capture. In this sense, the survey estimates are hypothetical on two fronts: (1) they capture producer perceptions, as opposed to actual market prices, and (2) they represent sales that occur rarely in practice. It is worth keeping these two points in mind the next time you see what appear to be low land value estimates coming from the USDA survey.   

Notes: Farmland price data come from a database of agricultural property transactions I developed using CoreLogic’s proprietary nationwide property transactions database. The 1999-2024 agricultural property sales used in this analysis are: (1) exclusively made up of 10 or fewer agricultural parcels (per CoreLogic’s land use codes), (2) between 10 and 4,000 total acres in size, (3) priced between $100 and $75,000/acre, (4) outside urban growth boundaries, (5) have at least 25% of the parcel area zoned exclusive farm use, farm-forest, marginal farmland, or non-public, and (6) have at least 50% of the parcel area in non-irrigated land capability classes 1-6.

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A Watershed Moment for Groundwater in Oregon

Posted on October 23, 2025 by jaegerw

By William Jaeger

Managing water resources sustainably is an enormous challenge facing societies today, and groundwater systems are particularly difficult because they are hidden below ground and are thus poorly understood. Many communities worldwide are dependent on groundwater for agricultural, municipal, and domestic uses, and they support aquatic habitats and other groundwater‐dependent ecosystems (GDEs). Yet groundwater systems continue to be depleted, imposing rising costs on rural communities, farmers, the environment, and public welfare generally. This critical resource provides water to 90% of water supply systems in the U.S. and many of these have become depleted in the last few decades (New York Times, 2023). Declining groundwater levels in the western U.S. threaten drinking water, residential wells, agricultural productivity, environmental flows, groundwater-dependent ecosystems, and they have caused land subsidence resulting in damaged infrastructure and losses in property values.

In Oregon there has been an increase in the number of basins experiencing serious groundwater problems, as reflected in their being designated by the state as “areas of concern”, “significant concern”, “yield-limited”, and “groundwater restricted areas,” as in the map below for 2021.

The Groundwater Act of 1955 gives the state the right to control all sources of water supply, and identifies three primary groundwater policy goals: i) to protect existing water rights (according to seniority under the prior appropriations doctrine), ii) to maintain reasonably stable groundwater levels, and iii) to preserve the public welfare, safety and health. Despite these mandates, there are a number of critical groundwater areas in the state where reasonably stable groundwater are not being maintained. For example, in Cow Valley which was the first basin to be designated a critical groundwater area in 1959, groundwater levels have continued to decline. So why is Oregon failing to fulfill its stated groundwater objectives?

Source: B. Scandella and J. Iverson, Oregon Groundwater Resource Concerns Report (2021)

There appear to be four factors that combine to make current approaches to groundwater management in Oregon problematic and ineffective.

The first factor is the long delay that commonly occurs between the time when groundwater pumping has exceeded sustainable rates and the time when the evidence of declining groundwater levels is evident (as much as 20 years later in some cases). This problem is somewhat unavoidable given the complex hydrology of groundwater that it is hidden below ground.

The second factor involves the corrective mechanisms under Oregon water law intended to regulate groundwater use. The seniority system under the prior appropriations doctrine was originally developed for surface water, and that is what Oregon and most western states use to allocate surface water: water users have a seniority ranking or “priority date” which gives senior water rights priority over junior rights when shortages occur. Water use is easily observable, and so too is interference between junior and senior water right holders. When there is not enough water for all users, junior water rights are shutoff in a matter of days or weeks to allow senior water right holders to divert their permitted amounts. The rules trigger timely reductions in water use, and they are transparent, predictable, and enforceable.

But in 1955 Oregon chose to apply this same prior appropriations seniority system for groundwater. The problems with this should be obvious: interference between and among users can take a long time to arise, it is not directly observable, interference in a given basin can involve hundreds or thousands of wells, and the impact of one well on another cannot be proved to a legal standard.

Hence, the system for regulating demand when it exceeds supply is unworkable. There is effectively no enforcement of the groundwater seniority system, and as a result no regular, transparent, predictable means of maintaining stable groundwater levels as required by law.

Third, the mandate to maintain reasonably stable groundwater levels is ambiguously defined. There is no requirement or guidelines about the length of time regulators can take to correct a situation when groundwater levels are observed to be declining, nor about what levels of groundwater stocks need to be maintained. Currently regulators can take decades to stabilize groundwater under the law, and ultimately at levels so low that they deny access to water for many senior water right holders, deplete surface water rights, degrade groundwater-dependent ecosystems, and fail to preserve the public welfare. The rules also provide no clear benchmarks or basis for holding authorities responsible for fulfilling their mandates.

Fourth, given the absence of regular, timely corrective mechanisms like those for surface water rights, the state has created several ad hoc designations for problematic groundwater basins (e.g., critical groundwater areas, groundwater limited areas), an approach that is reactive rather than predictive or proactive. These designations initiate processes that have been described as “arduous, contentious, and costly undertakings.” Moreover, they do not trigger programmed corrections, but can instead create openings for lobbying, negotiation and delays that may prioritize the interests of some water right holders over others in ways unrelated to their seniority. 

Taken together these factors leave Oregon’s groundwater systems vulnerable to overappropriation and depletion. Indeed, the current situation in the Harney Basin is an unfortunate example of this, and a cautionary illustration of the harms and injustices that can be inflicted on many parties involved as a result. In the Harney Basin, permitted groundwater pumping rates exceeded sustainable levels in the early 1990s (see figure below), but the impact on groundwater levels was not generally recognized until about 2015 at which point permitted pumping was nearly double sustainable levels. This led to multi-faceted, multilayered efforts to better understand the situation and to find a solution agreeable to stakeholders in the basin.

These efforts included a research project I led over the past five years to develop a hydro-economic computer model of the Harney Basin’s groundwater situation. Collaborating with colleagues at OSU and with US Geological Survey hydrologists, a three dimensional dynamic model simulated different scenarios to better understand the past and current situation and also to evaluate possible future solutions (see this reference listed below). In addition to groundwater decline causing rising costs and lower well yields for irrigators, many domestic wells have gone dry, and springs and lowland flows contribution to the Malheur Wildlife Refuge have declined by one-third. Our study concluded that there are no low-cost ways to stabilize groundwater in the basin. Irrigation pumping needs to be reduced by about 43%.

The basin designations of “serious concern” described as “arduous, contentious, and costly undertakings” have certainly been that in the case of the Harney Basin. As of today, after hundreds of hours of meetings and negotiations, two competing proposals are under review by the Oregon Water Resources Department, both call for a slow, 30-year phase-in of limitations on pumping beginning in 2028 and concluding in 2058. This slow pace will mean years of continued declines in groundwater levels, additional domestic wells going dry, and additional reductions to springs and lowland flows serving groundwater-dependent ecosystems. Many irrigators will suffer reduced well yields, higher pumping costs, and reduced farmland values. And, despite the long phase-in of the regulations, neither proposal will actually stabilize the groundwater system according to our model results.

The situations in the Harney Basin and in other Oregon basins make clear the need for a change in the rules governing groundwater. There are easy-to-describe alternatives that would make timely groundwater management adaptive and predictable so that the objectives of protecting existing water rights, maintaining reasonably stable groundwater levels, and preserving the public welfare, safety and health can be fulfilled. Now would be a good time for Oregon’s leaders to take action.

References

Cook, Emily Cureton, Race to the bottom: how big business took over Oregon’s first protected aquifer. OPB, March 16, 2022.

Jaeger, W. K., Antle, J., Gingerich, S. B., & Bigelow, D. (2024). Advancing sustainable groundwater management with a hydro‐economic system model: Investigations in the Harney Basin, Oregon. Water Resources Research, 60(11).

New York times, America Is Using Up Its Groundwater Like There’s No Tomorrow. August 28, 2023. https://www.nytimes.com/interactive/2023/08/28/climate/groundwater-drying-climate-change.html

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How have wildfires affected the value of agricultural land in Oregon?

Posted on August 25, 2025 by Kenneth Annan

By Kenneth Annan and Dan Bigelow

Disclaimer: This post presents an updated version of a paper I presented at the 2025 AAEA Conference. The results are preliminary and have not been peer-reviewed.          

Wildfires pose environmental, health, and economic threats throughout the United States (US). Their frequency and intensity have grown in recent years, particularly in the western United States. Over the last two decades, the total area damaged by wildfires each year has increased, with western states consistently having the highest percentage of burned acreage. In the context of Oregon, between 1984 to 2024 there were approximately 1,155 fires that burned at least 1,000 acres. Collectively, Oregon’s fires over this period have burned a total area of 16.4 million acres (Figure 1). Wildfire activity increased noticeably after 2000 compared to earlier years, with most of the larger fires occurring after 2011. Most of the wildfires are concentrated in the eastern half of the Oregon due to its relatively dry climate which makes it more susceptible to burning.  

Figure 1. Oregon’s wildfires have become larger in recent years
Source: Monitoring Trends in Burn Severity (MTBS) database. Note that the MTBS only tracks wildfires that are at least 1,000 acres in size.  

Oregon’s diverse agricultural sector offers a unique opportunity to study the impact of wildfires on land value across different agricultural uses. Wildfire impacts have been identified for other land uses, such as forestland and residential property values, while agricultural land markets have received relatively little attention in comparison. In a research paper presented at a recent conference, we examine how wildfires between 2000 and 2021 affected the price of agricultural land in Oregon. To do this, we collect all agricultural sales that took place within five years of a wildfire and compare before/after price changes between parcels that are close to wildfires (within 2km) with those located further away (2-10km). The basic idea is that by examining price changes over time in both areas and controlling for other factors that influence farmland prices (e.g., soil productivity and urban area proximity), we can isolate the impact of recent wildfire proximity on agricultural land values. To the extent that wildfires affect the future income that landowners would expect to earn from the land, they should be reflected in land prices.

 The main results indicate that, after a wildfire, farmland located within 2km of a fire tends to sell for 22% to 34% less than land 2-10km away. Based on the sample average price of an acre of farmland sold between 2000 and 2023 ($2,801), this translates to a loss of $616 to $952 per acre. Our statistical models also show that larger wildfires tend to cause more severe negative impacts. Specifically, we find that very large fires, defined as those that burn more than 35,000 or 70,000 acres, reduce farmland prices by about 45% and 54%, respectively, which translates to a loss of up to $1,513 per acre.

When comparing wildfire impacts across different farmland categories, the most pronounced negative impacts are observed for pasture and grassland, where we estimate an average land-price impact of about -27% per acre. The effects we find for cropland are still negative but are smaller and noisier (i.e., have a larger margin of error), which is potentially due to the relatively small number of cropland sales near wildfires. These findings indicate that impacts on land used for grazing are driving the overall statewide results. Grazing land has been highlighted as being susceptible to wildfire in other contexts, such as Texas.

Our findings provide a clearer picture of how wildfires are changing the agricultural land market due to the perceived risks of nearby fires. Wildfires affect agriculture directly and indirectly through downwind and downstream channels (e.g., direct crop burning, livestock harm, reductions in soil health, and health impacts on farm workers). Although we do not isolate these different individual pathways, the land-price impacts we estimate can be thought of as reflecting the total effect of wildfire proximity on future land-related net income.

Of course, wildfires also have severe impacts on human health and communities, among other things. However, to date, impacts on agriculture have received relatively little attention. As wildfires become more prevalent and intense, particularly in the western United States, it is important to evaluate their impacts on different sectors of the economy. The better we understand how wildfire risk affects different aspects of the economy and environment, the more we can develop smarter policies, better land management decisions, and a more resilient future for Oregon agriculture. Our preliminary findings highlight how agricultural land markets in Oregon have responded to wildfire risk perceptions and provide a framework for quantifying the impacts of  both future and more recent catastrophic wildfires, such as those that took place in Oregon in 2024.     

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New OSU Extension study links wolf presence to livestock revenue losses and increased costs

Posted on July 25, 2025 by Tim Delbridge

By Tim Delbridge

Earlier this month, David Bohnert and I published a new peer-reviewed article through OSU Extension on the economic impact of wolf depredation on Oregon livestock producers. Coincidentally, this came out just after the Governor Kotek signed Senate Bill 777, which authorizes increased compensation for livestock producers that lose animals to wolf attacks. The new legislation allows for compensation up to 5X the market value of the calves, yearlings, goats, and sheep, and up to 3X the market value of other cattle.

The rationale behind this payment multiplier is that total economic losses to livestock producers far exceed the direct financial loss of the killed animals. Other impacts facing ranches that are under wolf pressure, such as smaller (and less valuable) calves, reduced pregnancy rates, and added labor costs associated with wolf management and deterrence, are often more significant than the value of animals killed by wolves. Ultimately, the additional funding required to pay for the new compensation structure was not included by the Ways & Means Committee, creating some uncertainty about how compensation will be provided.

Our analysis on the economic impact of wolf depredation supports the idea that indirect costs faced by livestock producers are significantly higher than the value of confirmed and probable livestock kills. The novel aspect of this Extension publication is that we conducted an electronic survey of livestock producers who were asked to pinpoint the location of their grazing land and answer questions about wolf impact for that specific site. This allowed us to tie producer responses about wolf pressure and economic impact to the spatial wolf activity maps that are maintained by the Oregon Department of Fish and Wildlife (ODFW).

Figure 1. Areas of known wolf activity (red) and approximate location of survey responses (blue).

We found that producers managing livestock within ODFW-defined “Area of Known Wolf Activity” (AKWA) tended to report more significant wolf pressure, and that the financial impact was also higher in these areas. On grazing lands further away from ODFW AKWAs, producers reported fewer problems with wolves and lower financial costs. Although some livestock producers have been frustrated by the process that ODFW uses to officially confirm wolf presence in an area, and some argue that the true number of wolves is significantly higher than the ODFW minimum wolf populations, the strong correlation between ODFW wolf-activity maps and producer reports of wolf pressure shows the value of ODFW data collection and monitoring work.

Table 1. Response options for the survey question ‘How severe is the wolf pressure at this grazing location?’
Survey question textNumber of respondentsAverage distance to nearest AKWA* (miles)Average reported wolf management cost per cow
“There are no wolves that affect this area.”510.8$0.00
“There are wolves, but they don’t impact us much.”41.9$0.07
“Moderately heavy”112.2$13.75
“Heavy pressure, but not as bad as some ranchers deal with”73.0$20.52
“Extremely heavy”60.2$111.85

In terms of dollar values, the survey results indicated significant additional management costs and revenue reductions among Oregon ranches that experience wolf pressure. Cattle producers that reported “Extremely heavy” wolf pressure cited increased management costs of roughly $100 per cow, mostly related to additional labor time. These producers tended to be located in the defined AKWAs or just outside the boundaries. The increased management costs tend to fall off sharply within a couple of miles from defined AKWA boundaries.

Based on survey responses and existing literature on the physiological effects of wolf pressure on cattle, we estimate that revenue losses range between $135 and $200 per cow for producers experiencing heavy wolf pressure. This range would be even higher under the record-high prices for beef in today’s market.

Please explore the full publication for additional detail and narrative case studies on specific livestock producer experiences with wolves. This is an area of continuing work with active research projects across the Western US and within Oregon.

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Are farmland conservation easements associated with greater farm investment?

Posted on July 10, 2025 by Dan Bigelow

In this post, I’m going to present an overview of a recently published paper on the relationship between farmland conservation easements and farm investment. Before I dive into the paper, I first want to provide a brief overview of how conservation easements work.

Farmland conservation easements

Conservation easements provide a way for private landowners to permanently prevent their land from being developed. Under an easement, landowners voluntarily forego the right to put their land to certain uses (typically development for housing and similar uses) in exchange for compensation. An easement represents property rights that are permanently given up by the landowner. Once the easement is put in place, the surrendered property rights are usually held by a land trust. The details vary, but easements on farmland typically allow the land to continue to be used for agricultural production.

The value of the easement determines how much landowners are compensated for giving up their development rights. The easement value is determined by an outside appraiser, who will compare recent sales of similarly productive land parcels that are subject to different degrees of urban influence (or parcels that already have conservation easements). This can be thought of as the hypothetical difference in sale price for the same parcel with and without the easement. Essentially, the easement value is the price associated with the right to develop the land if that could be sold separately from the land itself.

Landowner compensation generally takes one of two forms. First, the easement can be purchased outright, with landowners receiving full cash compensation for permanently relinquishing their development rights. In acquiring an easement this way, land trusts can sometimes leverage matching funds from the U.S. Department of Agriculture’s Agricultural Land Easement (ALE) program. However, acquiring easements this way is not always feasible because most land trusts are relatively small entities constrained by limited budgets.

For most landowners, an outright purchase is the preferred form of compensation. The main alternative comes from the US income tax code. As a result of rules passed in 1976, conservation easements are considered charitable donations, meaning that the value of an easement can be deducted from the landowner’s federal income taxes. A more recent tweak to this rule in 2006 allows qualifying farm producers to deduct up to 100% of the easement value over a carryover period of 15 years. For example, if the easement is worth $1.5 million and the landowner earns $100,000 per year, they will effectively pay no federal income tax for 15 years. In addition, some states offer additional incentives through state income tax deductions (e.g., Oregon) or credits (e.g., Colorado).  

Why would landowners put an easement on their land?

There are different motivations landowners might have for using easements. One reason is that they may simply want to prevent their land from being developed in the future. Easements provide a permanent guarantee that this type of land-use conversion won’t happen. Farm succession planning can also come into play, especially concerning estate taxes levied by state governments, as the easement reduces the property’s market value and hence the tax responsibilities of any heirs. The same generally doesn’t apply to federal estate taxes because of rules that limit estate taxes on land that will remain in agricultural production.

In a recently published paper (ungated version), Conner McCollum (a former graduate student I worked with at Montana State) and I explore a third potential motivation. Specifically, we study if easements might be used to finance farm-related investments. The underlying premise of our analysis revolves around the way that modern agricultural lending institutions operate.

Producers often use their land as collateral to obtain loans for farm-related investments. However, land collateral is generally not appraised at its full market value. Due to concerns about default risk, lenders typically exclude the land’s non-agricultural (e.g., development) value from appraisals. If this weren’t the case, using an easement to finance farm investments would be harder to justify from an investment standpoint. Why would a landowner permanently give up a property right through an easement when they could just borrow against its value to make the same investment? In this sense, future development returns that are capitalized into the value of farmland are not “liquid” because the only way they can be accessed by the landowner is if they sell the land. Importantly, the idea that easements are used to finance farm investment has been found in a number of smaller-scale surveys but had not been borne out with observational data.

In the paper, we first document a negative county-level correlation between the fraction of agricultural market value borrowed against and different measures of development pressure (past land conversion and population density). This means that landowners in areas where future development is more likely borrow less, relative to the market value of their land, than those in more rural areas. 

We then turn to our main objective of measuring the county-level correlation between past easement activity and current farm investment. In line with the survey work referenced above, we document precise statistical relationships between easement activity and:

  1. an increase in land ownership by producers, alongside a decrease in total land rent expenses,
  2. greater use of machinery (tractors), and
  3. a weaker but positive association with increased labor use.

These relationships hold up under a variety of tweaks to our research design (e.g., removing potential outliers and controlling for different factors that might affect investment).

Of course, the paper has its limitations. First, we rely on imperfect observational data sources (including the Census of Agriculture and the National Conservation Easement Database). We also cannot attach causality to the relationships we estimate. That is, we can’t say with certainty that the easements themselves are the reason why counties with more easements see greater investment.

Policy implications

When it comes to conservation easements, Oregon tends to lag behind other states. This is generally chalked up to our state’s strong system of land use regulations that potentially limit how future development potential is priced into land outside of urban growth boundaries. However, that is not to say that development outside of UGBs doesn’t happen. Recent efforts to promote easements in Oregon have been bolstered by the Oregon Agricultural Heritage Program (OAHP), which provides state funds that can be used to leverage matching funds from the USDA’s ALE program. The first two rounds of the program funded 9 easements covering 12,252 acres of farmland across the state. Although the $2 million in OAHP funding recently approved by the legislature falls well short of the $17.3 million requested, the program seems to be growing in popularity and has broad statewide support.

I think this line of research is important because it highlights how conservation policy can be a win-win for both environmental conservation organizations and farming advocates, two groups that are not always on the same page. Environmental groups are often concerned with long-term land conservation goals. Farm advocates, on the other hand, are often concerned with property rights being stripped away without just compensation. If agricultural conservation easements actually promote farm investment, they have the dual benefits of conserving land and improving the resilience and vitality of farming communities in urbanizing areas.

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Farmland loss and land development: More on the misuse of statistics from the Census of Agriculture

Posted on June 10, 2025 by Dan Bigelow

During last week’s hearing for the Oregon Senate Committee on Natural Resources and Wildfire, Kelly Howsley-Glover (President, The Association of County Planning Directors) cited some of my blog posts concerning how to interpret the decrease in Oregon’s farmland reported in the 2022 USDA Census of Agriculture. The 2022 Census numbers show a decrease in farmland of 667 thousand acres between 2017 and 2022. On the surface, this seems like an alarming change, as it represents a loss of 4.18% of the 2017 farmland area. Although this most states lost farmland since the prior Census, the rate of farmland loss for Oregon is about double the national rate. Upon its release, the national Census statistics were cited as a cause for concern by some of the most influential people in US farm policy, including former Ag Secretary Tom Vilsack and American Farm Bureau Foundation President Zippy Duvall.

To be sure, a 4% loss in farmland over a five-year period is an alarming change. Farmland loss tends to be taken as a synonym for farmland conversion, where agricultural land is irreversibly developed for things like housing. It’s easy to read too much into these trends, and the widespread media coverage they receive doesn’t help, but the fact is that the loss of farmland accounted for in the Census is not the same as that land actually being lost forever to development. Instead, it’s a statistical loss pertaining to the land that’s tracked by the Census, which has been subject to declining response rates over the past decade. More importantly, it doesn’t match the pattern revealed in any other data source I’m aware of. On a more practical level, Oregon has a severe shortage of housing, which seems hard to square with the idea that we’ve been losing farmland at a rate of over 100 thousand acres per year.

Figure 1 shows the total amount of new land developed in Oregon in five-year increments from several different data sources. Although each measure comes from an entirely different source, they collectively paint a picture that should put to rest any notion that the Census farmland trend is indicative of land development. Below the figure I explain how each source is measured, along with its high-level pros and cons for this type of analysis.

First, note that I put Oregon’s Census-reported farmland loss (in thousands of acres) in parentheses under the years on the x-axis. Large farmland losses have been reported for Oregon in each of the past five Census years. The loss of 667,000 acres in 2022 is actually the second-highest loss reported over the past 25 years, with 681,000 acres in 2007 being the largest. In all but a few cases, the total amount of land developed in Oregon is less than 20% of the of the reported farmland loss. When we account for the fact that most land development in Oregon occurs on forestland, the fraction of farmland lost to development would be even smaller.

Note: The HISDAC-US periods are 1995-00, 2000-05, etc., and were matched to the nearest Ag Census period.
  • NRI (National Resources Inventory): The NRI is conducted by the USDA’s Natural Resources Conservation Service in cooperation with Iowa State University. It is based on a stratified sample of over 300,000 land segments (representing over 800,000 individual sample points) throughout the United States. Land use information comes from a combination of detailed satellite and aerial imagery and local knowledge from county NRCS and Farm Service Agency offices. Importantly, the NRI is designed to capture land use (as opposed to land cover) and has tracked the same plots of land since 1982.  I’ve shown this elsewhere, but the NRI indicates a steady decline in land conversion throughout Oregon since 1997. The 2022 version is supposed to be released in Fall of 2025.
    • NLCD (National Land Cover Database): The NLCD is a produced by the U.S. Geological Survey’s Earth Resources Observation and Science Center. USGS personnel use NASA’s Landsat (Land Satellite) images to develop annual maps of the US divided into 30m-resolution pixels (about 0.22 acres in size). As the name indicates, the NLCD tracks land cover, which does not always correspond with how land is used. For example, there may be houses that are obscured by surrounding trees and thus won’t be picked up in the satellite image. Similarly, forests that are harvested will appear from space as grassland or shrubland, which obviously misses how the land is actually used. The general trend shown in in the figure is similar in direction to the NRI, but less extreme and with a higher total area of development.
    • HISDAC-US (Historical Settlement Data Compilation): HISDAC-US is a relatively new database developed a few years ago by geographers at the University of Colorado. It divides the US into a 250m grid (about 15 acres per grid cell) and then consults local county assessment records (and other supplemental records) for the year when individual buildings were constructed across the US. The HISDAC-US data can also be thought of as representing land use, as they represent actual buildings that have been constructed. A downside is that not all buildings have recorded construction years, especially older ones. This limitation should be minimized by focusing on a relatively recent period, but it is worth keeping in mind. In 2020, the most recent year available, about 57% of all buildings in Oregon have construction year information.

    The plot is showing the HISDAC built-up area (BUA), which is the area of Oregon covered by 15-acre grid cells where at least one building is present, so if there’s one building in the cell (even if it’s a barn), the entire 15 acres is considered developed, which might exaggerate the total amount of development in more rural, low-density areas. That likely contributes to the large amounts of development shown earlier in the figure, which still represent at most 25% of Census-reported farmland loss, but the rate falls off dramatically in more recent periods.

    Despite the large differences in how total land development is measured across these three sources, which again includes all land developed (not just farmland), they collectively suggest that farmland loss reported in the Ag Census should not be confused with land development.

    So, what did happen to farmland between 2017 and 2022? Ideally, we could look to something like the NRI, but that isn’t currently available for 2022. Between 2012 and 2017 (Figure 2), when the Census showed Oregon losing 339 thousand acres of farmland, the NRI shows that most of the actual land-use change for agricultural land was due to moving between cropland, pasture, and range, with about 0.4% (63 thousand acres) being converted out of these three categories. Most of the agricultural land that changed use went into forest or “other” rural land, like farmsteads and farm buildings, and about 11 thousand acres were developed.

    If we look at the 2017-22 change in the satellite-based NLCD land cover data (Figure 3), 95% of the 2017 cropland remained that way in 2022, as did 91% of pasture/hay. Most of the land-cover changes for two categories were movements to and from each other or movements into grassland or shrubland. Agricultural land, especially in eastern Oregon, is sometimes misclassified in the NLCD as grassland or shrubland. These categories also retained 88 and 92% of their 2017 area, with most of the remainder representing changes across the two categories or, in the case of shrubland, movements into forest cover.

    As I’ve said before, the Census is a valuable resource when it is used correctly. The statistics that come out of the Census are cited widely and can inform policymaking at all levels. It provides important information on all sorts of things about farms and ranches throughout the US, but it is not a definitive source of land use information. The main issue is that it does not provide repeated information on the same farms over time, which contributes to misleadingly large statistics concerning farmland loss. To that end, it would be helpful if the USDA were to provide supplemental information on the same farms that responded to the previous Census. This would give both policymakers and the general public some context on how to square the data with reality.

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