When we found the same retailer or a branch of the same retail chain elsewhere in the same county, we kept the retailer in the data set. If a retailer disappeared and then reappeared in a later round of data collection, we kept it in the data set. If a retailer re moved its online price list, or moved its only location outside the original seven counties, we removed it from the data set for that data collection round . Between January 2017 and August 2017, we ob served significant attrition from the initial group of 542 retailers in the October 2016 seven-county sample. By August 2017, 389 of the original 542 retailers remained in the data set. As shown in tables 2 and 3, average prices for these retailers changed little during this 11-month period. We call this “attrition” because the data collection method was consistent over this time period. In our 2018 rounds of data collection, we impose the additional condition that retailers must be licensed, thus changing the data collection method . Thus, for 2018 data collection rounds, the percentage of retailers dropping out of the data set from the original October 2016 sample of 542 retailers should not be thought of as “attrition.” Some retailers may have removed their online price lists from both Weedmaps and Leafly but continued to operate. Attrition from the initial 542 retailers thus should not be interpreted solely as a measure of how many cannabis retailers left the legal cannabis segment. In November 2017, while continuing to track the original group of retailers that had been listing prices on Weedmaps since October 2016,flood tables for greenhouse we also collected data from all other retailers listing prices on Weedmaps in all counties of California.
These included the 169 retailers that by that time remained from the original panel; 700 additional retailers that had newly listed retail prices in the seven original counties after October 2016 ; and 1,652 retailers in other counties, for a total of 2,521 retailers across California.In January 2018, mandatory licensing laws went into ef fect, thus rendering illegal under state law any cannabis retailer without a temporary license from the Bureau of Cannabis Control. We verified licensing status by cross-referencing all Weedmaps and Leafly listings in California with the publicly available lists of temporary licenses granted by the Bureau of Cannabis Control. If both a Weedmaps and a Leafly listing were found, we used the Weedmaps data and dropped the Leafly data. In computing averages for our last three data collection rounds , we calculated “legally marketed” minimum and maxi mum price averages at California cannabis retailers that listed prices on Weedmaps and that had obtained temporary licenses to sell cannabis in compliance with state regulations at the time of each data collection round. For comparative purposes, we also collected a sample of about 90 unlicensed retailers in 20 counties from Weedmaps or Leafly, distributed similarly to the licensed retailers. We chose these retailers from within a set of 20 representative counties, approximately in proportion to the relative populations of those counties. We selected retailers for this “20-county unlicensed sample” arbitrarily from the first page of search results on Weedmaps for retailers in each of the 20 counties, but we did not use mathematical randomization to select the counties or the listings we chose within counties.These data may not be fully representative of legal cannabis price ranges for several reasons. First, as discussed above, not all legal retailers use Weedmaps or Leafly, and prices may not be representative of all prices. The price data we collected also may not fully rep resent the range of products in the market, which may have varied in different rounds of data collection.
As is suggested by the changing prevalence of 1-ounce flower packages and 500-milligram oil cartridge packages, product assortments may have changed within each of these categories. This problem plagues price data in many different industries, but changes in product assortments and price listings may have been especially rapid in the emerging cannabis market. The differences in price ranges we report here should not be interpreted as measures of price dispersion, because we are not observing maximum and minimum prices for exactly the same products at different retailers and thus are not comparing “apples to apples,” as is traditionally required to measure price dispersion. However, concrete differences in product attributes — such as potency or grow type for minimum-priced or maxi mum-priced cannabis — may also vary between retailers, and may correlate with price differences , even if price differences between agricultural products do not necessarily correlate with sensory characteristics . For instance, the minimum price for one-eighth ounce of flower at a particular retailer might represent a price for outdoor-grown cannabis with a THC concentration of 15%, whereas the minimum price for one-eighth ounce of flower at another retailer might represent a price for indoor-grown cannabis with a THC concentration of 20%. By analogy, if one were to collect minimum and maximum prices for all wine at retailers around California, the minimum-maximum range could not be used to measure price dispersion in a traditional sense; in order to measure dispersion, one would have to compare, for instance, the price of the same Kendall-Jackson Chardonnay at different stores. For our research, comparing prices for identical products across retailers would not have been feasible, given the Weedmaps format and our data collection methods. Our approach here, in reporting cannabis price ranges, is to make no assumptions about quality and assume that minimum and maximum prices are simply prices for different types of products. It would be interesting, in future work, to explore dispersion by collecting and comparing data on stadard product types across retailers.
Beyond requiring product standardization, an analysis of cannabis price dispersion with respect to geographic areas would also likely require a larger data set than ours. Hollenbeck and Uetake comment that regulatory barriers to entry can facilitate the exercise of monopolistic behavior by retailers. Dispersion measures, as proxies for competition, might help illuminate regulatory impacts. As more tax and sales data are released by government agencies, it might soon become possible for researchers to collect data sets of sufficient size and precision for dispersion to be measured.Table 2 shows average minimum and maximum prices over the course of the 21-month data collection period for the three product types that we studied, along with the number of observations in each period. In the last four rounds of data collection , we generally observe only relatively slight differences in both average prices and upward or downward movements among the three retailer groups . Both statewide and within the seven-county sample, average minimum and maximum prices for one-eighth ounce of flower and for 1 ounce of flower differed by 2.5% or less, but averages differed by up to 8.8% for 500-milligram cartridges. In table 3,indoor growing trays we report prices over the 21-month period for the non-attrited sample of the original retail store locations whose prices we collected in October 2016. These retailers may not be representative of overall state averages, particularly after the substantial attrition from the original group of retailers that we observed beginning in November 2017. However, this set of observations avoids potentially confounding factors introduced by the changing sample composition over time. Table 3 shows substantial attrition from the original seven-county sample of 542 retailers that listed prices on Weedmaps in October 2016. By July 2018, 21 months after the first round of price collection, only 74 non-attrited retailers from the original sample remained active on Weedmaps or Leafly. Local police crackdowns and municipal bans in some counties surely contributed to this 86% attrition rate, which should not be interpreted as representative of statewide attrition from Weedmaps or evidence of the general rate of business closures. What is more interesting, perhaps, is the basic observation that only 270 licensed cannabis retailers were listed on Weedmaps in all of California in July 2018, whereas in November 2017, near the end of the unregulated market, about 2,500 California cannabis businesses operated without the need for a license. This observation suggests, at least, that many medicinal cannabis retailers that had been operating legally in 2017 had not yet obtained licenses and entered the new legal market as of mid-2018. Figures 1, 2 and 3 show average minimum and maximum prices for one-eighth ounce of flower, 1 ounce of flower and 500-milligram oil cartridges for each round of data collection, both for legally marketed cannabis and for the 20-county unlicensed sample. In the 2016 and 2017 price data, before mandatory licensing, regulation and taxation, we observe relative stability in California cannabis price ranges for all three product types. In 2018, after licensing, regulation and taxation, we observe three patterns.
First, we observe falling prices for all products be tween February and May 2018, which may be related to retailers’ need to liquidate untested inventory that would become illegal as of July 2018. Second, we observe generally rising prices between May and July 2018, which may be related to the introduction of mandatory testing rules. However, because of the limitations and uncertain representativeness of the Weedmaps sample, as well as changes to our sampling methods in different rounds, we do not have a basis for inferring a causal relationship between testing rules or other regulatory events and our minimum and maximum price averages. Third, we observe rising maximum prices for 500-milligram oil cartridges over our last four data collection rounds. At all retailers statewide that listed prices on Weedmaps or Leafly, we observed a 33% in crease in maximum prices from November 2017 to July 2018. Table 2 shows that the latter pattern can be observed, with some variation, in prices both in the original seven counties and in all of California. We do not know to what extent the maximum price increases for cartridges might be attributed to the in troduction of new, higher-end products with differentiated sensory or functional attributes as the market has evolved; to differentiated packaging attributes; to price increases generated by increased high-end demand; to supply-side factors; or to other market effects. In general, the price patterns we observe demonstrate little evidence of seasonality, even though wholesale cannabis prices are known to vary seasonally because of the annual outdoor harvest and consequent increase in outdoor cannabis supply in the fall and winter months . We collected eight rounds of price data from the legal California retail cannabis market during a 21-month period of regulatory transition, as cannabis was being decriminalized, legalized and regulated in stages. Given the differences between the data sets we collected and the unknowns about Weedmaps that we have discussed above, readers should be especially cautious in interpreting the movements we observe as “trends.” We instead describe them as “patterns.” In general, one surprising result from our price data sets over time may be the relative lack of overall price movements in California cannabis prices, with the exception of rising maximum prices for cannabis oil cartridges in 2018. The data we report in this paper provides one source of unique information on the retail prices of cannabis flower and oil during the state’s period of transition to a regulated market environment. We hope that our data may useful to economists and other researchers who need to make basic assumptions about characteristics of the cannabis market. We did not collect price data for numerous products now available on the legal cannabis market in California, including edibles, waxes and topicals. The market has also changed in important ways since mid-2018. Many other basic reports on price data beyond ours are still needed to understand the economics of California’s rapidly changing cannabis market.Proposition 64 was really focused on the criminal justice aspects of cannabis prohibition — on [addressing] the negative impact of criminalization, primarily on people of color. It also focused on what happens to consumer safety and protection in the absence of regulation. It didn’t really prescribe regulation for the commercial sale of cannabis. The Legislature had already come up with a framework for regulating medical cannabis prior to Proposition 64 passing, and we didn’t have any reason to think that [the Legislature’s framework] would change drastically just because the criminal code had changed. We were right. You have to interface with a lot of agencies to be compliant. Those agencies are often over burdened and understaffed.