The cannabis industry has historically resisted widespread farm consolidation, perhaps due to its status as an unregulated, and illicit or semi-licit, activity. While the amount of cannabis produced in California is substantial , evidence from 2016 suggests that most outdoor cannabis was then produced on farms smaller than one acre . When Proposition 64 legalized non-medicinal cannabis in 2016, its size provisions explicitly acknowledged the state’s desire to see cannabis farms remain small . Initial regulations limited each permit to an area no greater than one acre and limited each entity to only one permit. Federal laws against cannabis have also encouraged small farms: Farmers with more than 99 plants potentially face federal minimum sentences of five years in prison . Local permitting may also favor smaller producers. Each jurisdiction in California can create its own permitting system, and possessing a local permit is a condition for obtaining a state permit. Most local jurisdictions place limitations on field sizes, and these limitations can encourage small-scale farming. While local permits may provide an avenue for local governments to protect small farmers , they also add another layer of regulation, potentially increasing entry costs. Beginning with California’s first attempt to implement a comprehensive regulatory system for the cultivation and distribution of legal cannabis, through the 2015 passage of the Medical Marijuana Regulation and Safety Act, stakeholders have expressed concerns that the permitting process privileges large farms over small. MacEwan et al. calculate that, due to the nature of regulatory costs, the type of small cannabis farmer prevalent in Northern California is the “least likely to participate in the regulated market.” Yet to date, empirical evidence on cannabis producers’ engagement with the formal market under the new regulatory framework has been lacking. In particular,hydroponic drain table there is a large evidence gap about the types of farms that participate in the regulated market and those that do not.
The gap exists partly because of a lack of public data about growers who have not applied for permits. We remedy that gap by combining information about farmers who have started the permit application process with a unique dataset of cannabis farms in Humboldt County in 2012 and 2016. Humboldt County is one of the largest cannabis producing regions in California and perhaps the world. Cannabis farming began there in the early 1960s, with rapid expansion following in the 1970s, and cannabis has been among the most valuable crops in the county at least since a proposition legalizing medical cannabis was approved by voters in 1996 . Recent studies suggest that at least 5,000 cannabis farms operate in Humboldt County . In the lead-up to the enactment of regulated cultivation of cannabis — which began for the medicinal market in 2016 and for the adult-use market in 2018 — the region experienced a cannabis boom, with the number of plants under cultivation increasing by 150% between 2012 and 2016 . This time of massive cannabis expansion is often referred to locally as the “green rush.” To track both permitted and unpermitted cannabis growers, we used data created by Butsic et al. . In their study, Butsic et al. hand-digitized cannabis farms using very high resolution satellite imagery. Cannabis production was measured in both 2012 and in 2016. Outdoor plants were counted and the number of plants inside greenhouses was estimated based on greenhouse size. Of the 1,724 farms in the dataset, 942 started producing cannabis between 2012 and 2016 and 782 produced at least some positive amount in both 2012 and 2016 . For permit data, we used publicly available data from the Humboldt County Planning Department, compiled from applications for commercial cannabis cultivation permits . We were able to combine the farm location data with the permit data based on the unique parcel identification that existed in both datasets. In total, applications were received for cultivation on 1,945 unique parcels. Of these, 533 were located within our study area .
We also include data describing farm/parcel characteristics. Locational variables such as distance to public roads and cities are used to proxy for transportation cost, while distances to endangered and threatened fish species habitat proxy for the environmental sensitivity of a site. Biophysical characteristics such as slope and presence of prime agricultural soils are used to describe the growing conditions of a site, while zoning designations are used to identify areas where growing cannabis is allowed . We also determined if a timber harvest plan had been associated with a parcel at any point since 1997. We include the quadratic term on farm size to increase the goodness of fit in our model and allow a more flexible relationship between farm size and permit application. The other covariates included in our regression are useful predictors of permit application, as they explain site-specific characteristics as well as proxy for potential land-use opportunities. They have been found to be significant predictors of farm location or farm abandonment . Importantly, these other covariates are primarily time-invariant or predetermined at the time growers decide whether to apply for permits. Specifically, we include variables of environmental sensitivity as proxies for potential challenges in obtaining approval from the Regional Water Quality Control Board. We include zoning information to help describe the other potential uses of the parcel if it were not being used for cannabis. Finally, we include a variable indicating if the area had ever had a timber harvest plan since 1997. We include this variable to see if past land use influences the likelihood of permit application. The average farm size in 2016 was 432 plants, with a median of 263 plants, a minimum of 14 and a maximum of 12,901 . Over 90% of farms produced fewer than 1,000 plants and fewer than 2% produced more than 2,000. Examining permit application rates by farm size reveals a distinct size gradient , as application rates increase substantially over farm-size categories. This pattern holds for both existing and new farms, but the rise is much sharper for the latter. Approximately 10% of small new farms apply for a permit, but rates jump to 61% and 50%, respectively, for the largest farm size groupings. We found a significant difference in size between farms that applied for a cannabis permit in 2016 relative to those that did not apply . The trend according to which larger farms applied for permits at higher rates held true regardless of production type .
The size differences are proportionally similar for both greenhouse and outdoor plants, so we do not find evidence that the relationship between farm size and permit application is solely driven by production method. Our regression models confirm that this result is robust to controlling for other covariates. In all our regression specifications, the coefficient on the total number of plants in 2016 is positive and statistically significant at the 1% level. The effect size of the number of plants indicates that, controlling for parcel characteristics, an increase of 100 plants increases the probability of applying for a permit by 2.4% , with the slope of the relationship declining for extremely large farms . The overall marginal effect is similar for existing and new farms, , though the declining marginal effect for very large farms is driven by new farms , and is robust to the inclusion of watershed fixed effects . The pattern also holds for size in 2012. Restricting the sample to existing farms, an increase of 100 plants in 2012 increases the probability of application by 3.1%.We first categorize growth of existing farms according to the proportionate change in plants produced between 2012 and 2016. The “declining production” group consists of farms that shrank by more than 5% ; “minimal change” farms experienced between −5% and 5% growth ; “moderate growth” farms grew between 5% and 50% and “high growth” farms grew by more than 50% . Within the sample of existing farms, there is a clear gradient of application rates with respect to growth between 2012 and 2016 . The farms least likely to apply are those that declined in size, followed by those with minimal growth. Application rates for existing farms that grew moderately jump to over 40%,rolling benches hydroponics with high growth farms the most likely to apply. Note that across all expansion rates for existing farms, application rates are significantly higher than the average rate for new farms. Statistical tests confirm this trend. Existing farms that applied for permits displayed a mean expansion of 212 plants between 2012 and 2016, while the mean expansion for farms that did not apply was 130 plants . This difference of 82 plants is significant at the 1% level. Our regression results also find expansion associated with permit application . In column 6, an increase of 100 plants among existing growers is associated with a 1.5% higher probability of applying for a permit, with the result positive and statistically significant at the 1% level. farms than existing farms . However, new farms are far less likely to apply for permits than existing farms. The univariate comparison shows that, on average, a new farm was 22% less likely to apply for a permit than a farm that already existed in 2012. Our regression results indicate that this relationship is robust to controlling for associated covariates, including farm size. The coefficient on new farms is statistically significant and negative in all regression specifications.
Controlling for other factors, new farms are approximately 7.3% less likely than existing farms to apply for a permit, with the magnitude of the effect slightly reduced when relying only on within-watershed variation . Small new farms are very unlikely to apply for a permit, even in comparison with existing farms of similar size . Regression results indicate that farms which have not applied for permits tend to be located further north, closer to both cities and the coast and further away from roads . They are also more likely to be located on prime agricultural soils, which is a listed requirement for obtaining a permit. However, there seems to be no effect associated with flat terrain or agricultural zones, which are also requirements for permits. These results suggest that siting criteria in the permit ordinance do not appear to be positive independent drivers of application decisions. In contrast, farms that did apply for permits tend to be located closer to streams and chinook salmon habitat, even as permit eligibility requires the use of non-diversionary water sources . Applying farms are also more likely to be located in forest recreation or timber production zones and to have been transacted at least once since 2015. They also tend be located on larger parcels. However, from comparing the results in columns and , it is clear that a number of regression outcomes between permit applications and parcel characteristics are not robust to the inclusion of watershed fixed effects. This suggests the existence of underlying geographic drivers which might influence these relationships.Cannabis has been profitably produced in California, primarily on small farms, for decades . As cannabis becomes increasingly legal, production practices have become more standardized, and many small farms fear that the increased regulatory costs associated with formalization will force them to either shut down or remain on the black market . Here, we use empirical data on farm location and permit status to investigate differences between cannabis farms that applied for permits to produce in the legal market and those that did not. We find strong evidence that farms with more plants are more likely to apply for permits than farms that grow fewer plants. This is consistent with the argument that increased formalization disfavors small-scale farms . A potential implication of this trend is that continued cannabis expansion in California may disproportionately favor the establishment of large farms, despite measures seemingly designed to prevent this outcome. Small cannabis farms may face challenges similar to those faced by small farms producing other crops — and if small farms are valued, additional policy solutions are required. While our results point toward a robust positive relationship between size and permit application , we cannot definitively attribute the cause to either the fixed cost of initial application or ongoing costs associated with regulatory compliance.