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Dark web marketplaces are websites that facilitate trade in illicit goods, mainly using Bitcoin. Since dark web marketplaces are unregulated, they do not offer any user protection, so police raids and scams regularly cause large losses to marketplace participants. However, the uncertainty has not prevented the proliferation of dark web marketplaces. Here, we investigate how the dark web marketplace ecosystem reorganises itself following marketplace closures. We analyse 24 separate episodes of unexpected marketplace closure by inspecting 133 million Bitcoin transactions among 38 million users. We focus on “migrating users” who move their trading activity to a different marketplace after a closure. We find that most migrating users continue their trading activity on a single coexisting marketplace, typically the one with the highest trading volume. User migration is swift and trading volumes of migrating users recover quickly. Thus, although individual marketplaces might appear fragile, coordinated user migration guarantees overall systemic resilience.

Dark web marketplaces (DWMs) are online platforms that facilitate illicit trade among millions of users generating billions of dollars in annual revenue. Recently, two interview-based studies have suggested that DWMs may also promote the emergence of direct user-to-user (U2U) trading relationships. Here, we carefully investigate and quantify the scale of U2U trading around DWMs by analysing 31 million Bitcoin transactions among users of 40 DWMs between June 2011 and Jan 2021. We find that half of the DWM users trade through U2U pairs generating a total trading volume greater than DWMs themselves. We then show that hundreds of thousands of DWM users form stable trading pairs that are persistent over time. Users in such stable pairs turn out to be the ones with the largest trading volume on DWMs. Then, we show that new U2U pairs often form while both users are active on the same DWM, suggesting the marketplace may serve as a catalyst for new direct trading relationships. Finally, we reveal that stable U2U pairs tend to survive DWM closures and that they were not affected by COVID-19, indicating that their trading activity is resilient to external shocks. Our work unveils sophisticated patterns of trade emerging in the dark web and highlights the importance of investigating user behaviour beyond the immediate buyer-seller network on a single marketplace.

Dark web marketplaces have been a significant outlet for illicit trade, serving millions of users worldwide for over a decade. However, not all users are the same. This paper aims to identify the key players in Bitcoin transaction networks linked to dark markets and assess their role by analysing a dataset of 40 million Bitcoin transactions involving the 31 major markets in the period 2011–2021. First, we propose an algorithm that categorizes users either as buyers or sellers, and show that a large fraction of the trading volume is concentrated in a small group of elite market participants. We find that the dominance of markets is reflected in trading properties of buyers and sellers. Then, we investigate both market star-graphs and user-to-user networks, and highlight the importance of a new class of users, namely ‘multihomers’, who operate on multiple marketplaces concurrently. Specifically, we show how the networks of multihomers and seller-to-seller interactions can shed light on the resilience of the dark market ecosystem against external shocks. Our findings suggest that understanding the behavior of key players in dark web marketplaces is critical to effectively disrupting illegal activities.

Renewable natural capital—terrestrial and marine ecosystems, fisheries, biodiversity, and fresh water—is in decline around the world, affecting the livelihoods of millions of people. Natural capital market design uses economic theory and analysis to develop practical solutions for maintaining, restoring, and improving natural capital. Many successful natural capital marketplaces (e.g. for emissions reduction, fish harvesting, and wetland restoration) focus on efficient trading of property rights. But many other natural capital markets (e.g. for carbon sequestration offsets, water quality, and water rights) are characterized by heterogeneity and high transaction costs that make trading difficult. We argue that, in order to fix many natural capital market failures, policy-makers should instead pay more attention to the allocation of property rights during marketplace design: this is particularly crucial in many markets for ecosystem services (e.g. biodiversity conservation and watershed protection) which exhibit strong ecological complementarities. We propose several promising designs for natural capital marketplaces which could fairly and efficiently allocate and redistribute property rights over different ecosystems.

The COVID-19 pandemic has reshaped the demand for goods and services worldwide. The combination of a public health emergency, economic distress, and misinformation-driven panic have pushed customers and vendors towards the shadow economy. In particular, dark web marketplaces (DWMs), commercial websites accessible via free software, have gained significant popularity. Here, we analyse 851,199 listings extracted from 30 DWMs between January 1, 2020 and November 16, 2020. We identify 788 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds . Finally, we compare trends in their temporal evolution with variations in public attention, as measured by Twitter posts and Wikipedia page visits. We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs, especially now that real vaccines are available and in short supply. We anticipate our analysis will be of interest both to researchers and public agencies focused on the protection of public health.

Early analyses revealed that dark web marketplaces (DWMs) started offering COVID-19 related products (e.g., masks and COVID-19 tests) as soon as the COVID-19 pandemic started, when these goods were in shortage in the traditional economy. Here, we broaden the scope and depth of previous investigations by considering how DWMs responded to an ongoing pandemic after the initial shock. Our dataset contains listings from 194 DWMs collected until July 2021. We start by focusing on vaccines. We find 248 listings offering approved vaccines, like Pfizer/BioNTech and AstraZeneca, as well as vendors offering fabricated proofs of vaccination and COVID-19 passports. Then, we consider COVID-19 related products. We show that, as the regular economy has become able to satisfy the demand of these goods, DWMs have decreased their offer. Next, we analyse the profile of vendors of COVID-19 related products and vaccines. We find that most of them are specialized in a single type of listings and are willing to ship worldwide. Finally, we consider a broader set of listings mentioning COVID-19, in order to assess the general impact of the pandemic on the broader activity of DWMs. Among 10,330 such listings, we show that recreational drugs are the most affected among traditional DWMs product, with COVID-19 mentions steadily increasing since March 2020. We anticipate that our results will be of interest to researchers, practitioners, and law enforcement agencies focused on the study and safeguard of public health.

Abstract We show how to efficiently use costly testing resources in an epidemic, when testing outcomes can be used to make quarantine decisions. If the costs of false quarantine and false release exceed the cost of testing, the optimal myopic testing policy targets individuals with an intermediate likelihood of being infected. A high cost of false release means that testing is optimal for individuals with a low probability of infection, and a high cost of false quarantine means that testing is optimal for individuals with a high probability of infection. If individuals arrive over time, the policy-maker faces a dynamic trade-off: using tests for individuals for whom testing yields the maximum immediate benefit vs spreading out testing capacity across the population to learn prevalence rates thereby benefiting later individuals. We describe a simple policy that is nearly optimal from a dynamic perspective. We briefly discuss practical aspects of implementing our proposed policy, including imperfect testing technology, appropriate choice of prior, and non-stationarity of the prevalence rate.

Brexit creates challenges and opportunities for UK and EU climate policy. Without replacement policies for existing EU policies, the UK may not meet its domestic carbon budgets. Membership of the EU ETS, application of energy efficiency directives and renewables targets, and the maintenance of innovation funding are the key issues at stake for the UK. Brexit may also impact the ambition and shape of EU climate policy and the direction of future climate agreements.

We show how frictions and continuous transfers jointly affect equilibria in a model of matching in trading networks. Our model incorporates distortionary frictions such as transaction taxes and commissions. When contracts are fully substitutable for firms, competitive equilibria exist and coincide with outcomes that satisfy a cooperative solution concept called trail stability. However, competitive equilibria are generally neither stable nor Pareto-efficient.

Modelling the economics of climate change is daunting. Many existing methodologies from social and physical sciences need to be deployed, and new modelling techniques and ideas still need to be developed. Existing bread-and-butter micro- and macroeconomic tools, such as the expected utility framework, market equilibrium concepts and representative agent assumptions, are far from adequate. Four key issues—along with several others—remain inadequately addressed by economic models of climate change, namely: (1) uncertainty, (2) aggregation, heterogeneity and distributional implications (3) technological change, and most of all, (4) realistic damage functions for the economic impact of the physical consequences of climate change. This paper assesses the main shortcomings of two generations of climate-energy-economic models and proposes that a new wave of models need to be developed to tackle these four challenges. This paper then examines two potential candidate approaches—dynamic stochastic general equilibrium (DSGE) models and agent-based models (ABM). The successful use of agent-based models in other areas, such as in modelling the financial system, housing markets and technological progress suggests its potential applicability to better modelling the economics of climate change.