Cannabis prices on the dark web

Jakub Červený, Jan van Ours 28 September 2019

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Despite a recent surge in the liberalisation of policies towards consumption of cannabis—for example in Canada and Uruguay and in several US states—the drug still remains illegal in most countries. Because of cannabis’s illegal nature, information and, therefore, studies on quality, prices, and quantities of cannabis consumed or supplied are limited. However, with recent trends in legalisation and with the transition of illegal drug markets to the internet, much more detailed information about price and also quality is now available, making it easier to analyse the determinants of cannabis prices. 

Cannabis prices around the world

There is substantial variation in cannabis prices in cities around the world. According to the 2018 Cannabis Price Index, in a sample of 120 cities, cannabis prices vary from a low of $1.34 in Quito, Ecuador, to almost $33 in Tokyo, Japan (see Table 1). Both at the top and at the bottom of the price range are cities in which cannabis use is illegal. 

There is also substantial within-country variation in cannabis prices. Within Canada for example, the price range in dollars per gram was from 6.15 in Montreal to 7.82 in Toronto, while in the US, the range was from 7.58 in Seattle to 18.08 in Washington DC. 

Table 1 Cannabis prices in cities around the world: Top five highest and lowest prices 2018

Source: 2018 Cannabis Price Index: http://weedindex.io

Previous studies on cannabis prices

Previous studies on the determinants of drug prices are based on undercover operations or surveys among drug users. An early study by Brown and Siverman (1974) analyses heroin-price data based on purchases by US undercover narcotics agents and finds a quantity discount a positive price-effect of the purity of the heroin. Caulkins and Padman (1993)—analysing price data collected by US undercover narcotics agents for various illicit drugs including cannabis–find for most drugs quantity discounts and quality premiums. 

Caulkins and Pacula (2006) use data from a US household survey to investigate the variation in cannabis prices and find a quantity discount elasticity. Lakhdar et al. (2016) analyse cannabis prices using information from regular French cannabis users and find a significant quantity discount and significant positive quality effects. Smart et al. (2017) study cannabis prices of retail transactions from Washington State, where cannabis sales are legal, and find a significant quantity discount and significant positive price effects of quality. 

Dark web markets

The advent of sophisticated cryptographic algorithms and distributed networks gave rise not only to better privacy on the internet but sparked the creation of many ‘dark web’ websites. Thanks to The Onion Router (TOR) software, internet users are able to transmit their communication anonymously. 

Market places on the dark web offer a wide range of activities, spanning from fraud and scam websites to black-market activities such as illegal drug sales. Perhaps one of the most famous hidden services operating on the dark web was a site called Silk Road. Since its inception, the site became famous for selling, among other things, illicit drugs, weapons, and credit-card numbers. 

Dark web market places often have a layout similar to eBay, allowing users to advertise and sell virtually everything without fear of being traced. Payments are made exclusively in Bitcoin, the virtual currency allowing a similar degree of anonymity to both sides of the transaction.

For cannabis, the vast majority of the purchases still takes place via traditional street vendors. Online illegal drug markets with cannabis transactions as an important element are still a relatively recent phenomenon. Nevertheless, from a perspective of the user, the transition of the drug markets to the internet brings several benefits. Van Hout and Bingham (2013) show that users see online transactions as being safer than negotiating in a street-level drug market. Décary-Hétu et al. (2016) study the risk-taking behaviour of drug sellers on the dark web and conclude that, compared to traditional drug-market transactions, the risk of violence is reduced as face-to-face transactions are eliminated. Aldridge et al. (2018) argue that online illegal markets may reduce the harm of drug use because they raise the quality and safety of the drugs sold and because, in the course of the transaction, there is less conflict and violence. 

Our analysis

We use data from a dark web marketplace called Alpha Bay, collected between 29 September and 12 October 2015 (see Červený and Van Ours 2019 for details). We have information about 500 cannabis prices from around 140 sellers in 18 countries. The nature of the data allows us to exploit the detailed information about the quality of a particular cannabis strain, measured both by its potency (active ingredient content) and its popularity among users. Table 2 provides summary statistics of our dataset.

Table 2 Cannabis market statistics by country

Notes: THC: tetrahydrocannabinol. L: (quasi-)legalised, D: decriminalised, I: illegal. GDP = log(GDP per capita). * State-dependent.

The lowest average price offered was in Cambodia, at $3.4 per gram, whereas the highest price was in Germany, at $14.5 per gram. The average price in the biggest market, the US, was slightly more than $9 per gram. The most potent cannabis herb originated from France, with an average 17% content of THC (tetrahydrocannabinol, the main psychoactive compound in cannabis), followed by Canada with 16.5% of THC. 

In terms of total cannabis sold, with almost 105 kilogrammes sold over the two-week period, the biggest market is the US. There also seems to be a strong relationship between GDP per capita and cannabis price. In countries with a low GDP per capita, such as Cambodia and India, the average cannabis price is lower than in richer countries such as Germany. 

The top graph of Figure 1 shows the relationship between (log) prices and (log) quantities in our sample. Although there is a wide dispersion in prices and quantities, there is a clear negative association between the two, i.e. larger quantities were offered at lower prices. The bottom graph of Figure 1 plots cannabis prices against estimated THC-content. There does not seem to be a systematic relationship between these two variables.

Figure 1 Cannabis prices and quantities per offer; Cannabis prices and THC content

In our empirical analysis, we take into account that cannabis prices may be affected by quantity discounts, i.e. by the quantities offered and by several characteristics of offers and country. The cannabis-quality characteristics we take into account in our analysis are whether the cannabis strain on offer was placed in the so-called Cannabis Cup competition and its THC content. We also control for electricity prices, since cannabis is usually produced indoors, which requires significant amounts of electricity to power lamps used as a substitute for natural sunlight. And, we account for GDP per capita, as well as for legal status of cannabis in the seller’s origin country. 

Main findings

We find that a 1% increase in the quantity of cannabis offered is reflected in a 0.19% decrease in cannabis price. This is an expected result since a quantity discount is often used as an incentive to purchase larger quantities. A quantity discount could also be related to risk-averse behaviour of the seller. 

Furthermore, we find that cannabis prices are affected by quality, as measured by the success of the particular cannabis strain in the Cannabis Cup. Successful cannabis strains on average have a 10%-higher price. We find that higher electricity prices are indeed reflected in cannabis prices. There is a significant positive relationship between GDP per capita and cannabis prices. 

From all this, we conclude that the internet-based cannabis market is characterised by monopolistic competition, where many sellers offer differentiated products with quality variation causing dispersion of cannabis prices. We also conclude that sellers have some control over cannabis prices. 

References

Aldridge, J, A Stevens and M J Barratt (2018), “Will growth in cryptomarket drug buying increase the harms of illicit drugs?”, Addiction 113: 789–796. 

Brown, G F, and L P Siverman (1974), “The retail price of heroin: Estimation and applications”, Journal of the American Statistical Association 69(347): 595-606.

Caulkins, J P, and R L Pacula (2006), “Marijuana markets: Inferences from reports by the household population”, Journal of Drug Issues 36(1): 173–200. 

Caulkins, J P, and R Padman (1993), “Quantity discounts and quality premia for illicit drugs”, Journal of the American Statistical Association 88(423): 748-757.

Červený, J, and JC van Ours (2019), “Cannabis prices on the Dark Web”, CEPR Discussion Paper 13933; forthcoming in European Economic Review

Clements, K W (2006), “Pricing and packaging: The case of marijuana”, Journal of Business 79(4): 2019–2044. 

Décary-Hétu, D, M Paquet-Clouston and J Aldridge (2016), “Going international? Risk taking by cryptomarket drug vendors”, International Journal of Drug Policy 35: 69–76. 

Jikomes, N, and M Zoorob (2018), “The cannabinoid content of legal cannabis in Washington state varies systematically across testing facilities and popular consumer products”, Scientific Reports 8: 1–15. 

Lakhdar, C B, N G Vaillant and FC Wolff (2016), “Price elasticity of demand for cannabis: Does potency matter?”, Addiction Research and Theory 24(4): 300–312. 

Smart, R, J P Caulkins, B Kilmer, S Davenport and G Midgette (2017), “Variation in cannabis potency and prices in a newly legal market: Evidence from 30 million cannabis sales in Washington state”, Addiction 112(12): 2167–2177. 

Van Hout, M C, and T Bingham (2013), “Surfing the Silk Road: A study of users’ experiences”, International Journal of Drug Policy 24: 524–529.

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Topics:  Microeconomic regulation

Tags:  cannabis, dark web, cryptocurrency, legalisation, cannabis legalisation, drugs, prices, decriminalisation, black market, drug markets, illegal drugs

Post-doctoral researcher, Medical University of Vienna

Professor of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, The Netherlands Professorial Fellow at the Department of Economics, University of Melbourne; CEPR Research Fellow

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