arXiv subjects

Alexander Teytelboym

Publications and source records attributed to Alexander Teytelboym.

18 recordsLinked to original sources

arXiv2025

The Combinatorial Multi-Round Ascending Auction

The Combinatorial Multi-Round Ascending Auction (CMRA) is a new auction format used in recent European spectrum auctions. We show that an auction-specific version of truthful bidding leads to an efficient allocation. We then characterize different ex-post equilibria that feature truthful bidding, demand expansion, and demand reduction. The truthtelling equilibrium is fragile to small asymmetries in the bidders' caps. Moreover, if bidders are sufficiently symmetric, the CMRA is vulnerable to risk-free collusion. We propose an alternative activity rule that prevents such collusive strategies while keeping other equilibria intact. We discuss outcomes of several Danish CMRAs in light of our equilibrium predictions.

econ.TH↗

arXiv2025

Efficiency, Envy, and Incentives in Combinatorial Assignment

Ensuring efficiency and envy-freeness in allocating indivisible goods without money often requires randomization. However, existing combinatorial assignment mechanisms (for applications such as course allocation, food banks, and refugee resettlement) guarantee these properties either ex ante or ex post, but not both. We propose a new class of mechanisms based on Competitive Equilibrium from Random Incomes (CERI): Agents receive random token budgets and select optimal lotteries at competitive prices that clear markets in expectation. Our main insight is to let the CERI price vector guide all ex-post allocations. We show that all ordinally efficient allocations are CERI allocations, which can be implemented as lotteries over near-feasible Pareto-efficient outcomes. With identical budget distributions, CERI allocations are ordinally envy-free; with budget distributions on small supports, ex-post allocations are envy-free up to one good. Moreover, we design an asymptotically efficient implementation of CERI that satisfies a strong new non-manipulability property in large markets.

econ.TH↗

arXiv2024

The Economics of Equilibrium with Indivisible Goods

This paper develops a theory of competitive equilibrium with indivisible goods based entirely on economic conditions on demand. The key idea is to analyze complementarity and substitutability between bundles of goods, rather than merely between goods themselves. This approach allows us to formulate sufficient, and essentially necessary, conditions for equilibrium existence, which unify settings with complements and settings with substitutes. Our analysis has implications for auction design.

econ.TH↗

arXiv2024

The Computational Complexity of the Housing Market

We prove that the classic problem of finding a competitive equilibrium in an exchange economy with indivisible goods, money, and unit-demand agents is PPAD-complete. In this "housing market", agents have preferences over the house and amount of money they end up with, but can experience income effects. Our results contrast with the existence of polynomial-time algorithms for related problems: Top Trading Cycles for the "housing exchange" problem in which there are no transfers and the Hungarian algorithm for the "housing assignment" problem in which agents' utilities are linear in money. Along the way, we prove that the Rainbow-KKM problem, a total search problem based on a generalization by Gale of the Knaster-Kuratowski-Mazurkiewicz lemma, is PPAD-complete. Our reductions also imply bounds on the query complexity of finding competitive equilibrium.

cs.GT↗

arXiv2023

Optimizing Sponsored Humanitarian Parole

The United States has introduced a special humanitarian parole process for Ukrainian citizens in response to Russia 2022 invasion of Ukraine. To qualify for parole, Ukrainian applicants must have a sponsor in the United States. In collaboration with HIAS, a refugee resettlement agency involved in the parole process, we deployed RUTH (Refugees Uniting Through HIAS), a novel algorithmic matching system that is driven by the relocation preferences of refugees and the priorities of US sponsors. RUTH adapts Thakral Multiple-Waitlist Procedure (MWP) that combines the main FIFO queue with location-specific FIFO queues to effectively manage the preferences of refugees and the supply of community sponsors. RUTH also incorporates various feasibility considerations, such as community capacity religious, and medical needs. The adapted mechanism is envy-free, efficient, and strategy-proof for refugees. Our analysis shows diverse refugee location preferences, not fully explained by observables, highlighting the challenge of predicting preferences directly from them. We use our data for two counterfactual simulations. First, we consider the effects of increased waiting times for refugees on the quality of their matches. We find that with a periodic Top Trading Cycles algorithm, increasing period length from 24 days to 80 days improves the average rank of a refugees match from 3.20 to 2.44. Second, we estimate the arrival rates of sponsors in each location that would be consistent with a long-run steady state. We find that more desirable locations (regarding refugee preferences) require the highest arrival rates, suggesting that preferences might be a useful indicator for investments in sponsorship capacity. Our study highlights the potential for preference-based algorithms such as RUTH to improve the efficiency and fairness of other rapidly deployed humanitarian parole processes.

physics.soc-ph↗

arXiv2023

Identifying key players in dark web marketplaces

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 31 markets in the period 2011-2021. First, we propose an algorithm that categorizes users either as buyers or sellers and shows that a large fraction of the traded volume is concentrated in a small group of elite market participants. 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.

physics.soc-ph↗

arXiv2023

Dynamic Combinatorial Assignment

We study a model of dynamic combinatorial assignment of indivisible objects without money. We introduce a new solution concept called ``dynamic approximate competitive equilibrium from equal incomes'' (DACEEI), which stipulates that markets must approximately clear in almost all time periods. A naive repeated application of approximate competitive equilibrium from equal incomes (Budish, 2011) does not yield a desirable outcome because the approximation error in market-clearing compounds quickly over time. We therefore develop a new version of the static approximate competitive equilibrium from carefully constructed random budgets which ensures that, in expectation, markets clear exactly. We then use it to design the ``online combinatorial assignment mechanism'' (OCAM) which implements a DACEEI with high probability. The OCAM is (i) group-strategyproof up to one object (ii) envy-free up to one object for almost all agents (iii) approximately market-clearing in almost all periods with high probability when the market is large and arrivals are random. Applications include refugee resettlement, daycare assignment, and airport slot allocation.

econ.TH↗

arXiv2022

Dynamic Placement in Refugee Resettlement

Employment outcomes of resettled refugees depend strongly on where they are placed inside the host country. Each week, a resettlement agency is assigned a batch of refugees by the United States government. The agency must place these refugees in its local affiliates, while respecting the affiliates' yearly capacities. We develop an allocation system that suggests where to place an incoming refugee, in order to improve total employment success. Our algorithm is based on two-stage stochastic programming and achieves over 98 percent of the hindsight-optimal employment, compared to under 90 percent of current greedy-like approaches. This dramatic improvement persists even when we incorporate a vast array of practical features of the refugee resettlement process including indivisible families, batching, and uncertainty with respect to the number of future arrivals. Our algorithm is now part of the Annie MOORE optimization software used by a leading American refugee resettlement agency.

cs.GT↗

arXiv2022

Macroscopic properties of buyer-seller networks in online marketplaces

Online marketplaces are the main engines of legal and illegal e-commerce, yet their empirical properties are poorly understood due to the absence of large-scale data. We analyze two comprehensive datasets containing 245M transactions (16B USD) that took place on online marketplaces between 2010 and 2021, covering 28 dark web marketplaces, i.e., unregulated markets whose main currency is Bitcoin, and 144 product markets of one popular regulated e-commerce platform. We show that transactions in online marketplaces exhibit strikingly similar patterns despite significant differences in language, lifetimes, products, regulation, and technology. Specifically, we find remarkable regularities in the distributions of transaction amounts, number of transactions, inter-event times and time between first and last transactions. We show that buyer behavior is affected by the memory of past interactions and use this insight to propose a model of network formation reproducing our main empirical observations. Our findings have implications for understanding market power on online marketplaces as well as inter-marketplace competition, and provide empirical foundation for theoretical economic models of online marketplaces.

physics.soc-ph↗

arXiv2022

The illicit trade of COVID-19 vaccines on the dark web

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 analysing 194 DWMs until July 2021, including the crucial period in which vaccines became available, and by considering the wider impact of the pandemic on DWMs. First, we focus on vaccines. We find 250 listings offering approved vaccines, like Pfizer/BioNTech and AstraZeneca, as well as vendors offering fabricated proofs of vaccination and COVID-19 passports. Second, we consider COVID-19 related products. We reveal that, as the regular economy has become able to satisfy the demand of these goods, DWMs have decreased their offer. Third, 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 as proxy for the general impact of the pandemic on these 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 effort is of interest to researchers, practitioners, and law enforcement agencies focused on the study and safeguard of public health.

cs.CY↗

arXiv2021

Emergence and structure of decentralised trade networks around dark web marketplaces

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 quantify the scale of, and thoroughly investigate, 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 stable pairs are typically 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.

physics.soc-ph↗

arXiv2021

Dark Web Marketplaces and COVID-19: before the vaccine

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.

cs.CY↗

arXiv2021

Collective Dynamics of Dark Web Marketplaces

Dark markets are commercial websites that use Bitcoin to sell or broker transactions involving drugs, weapons, and other illicit goods. Being illegal, they do not offer any user protection, and several police raids and scams have caused large losses to both customers and vendors over the past years. However, this uncertainty has not prevented a steady growth of the dark market phenomenon and a proliferation of new markets. The origin of this resilience have remained unclear so far, also due to the difficulty of identifying relevant Bitcoin transaction data. Here, we investigate how the dark market ecosystem re-organises following the disappearance of a market, due to factors including raids and scams. To do so, we analyse 24 episodes of unexpected market closure through a novel datasets of 133 million Bitcoin transactions involving 31 dark markets and their users, totalling 4 billion USD. We show that coordinated user migration from the closed market to coexisting markets guarantees overall systemic resilience beyond the intrinsic fragility of individual markets. The migration is swift, efficient and common to all market closures. We find that migrants are on average more active users in comparison to non-migrants and move preferentially towards the coexisting market with the highest trading volume. Our findings shed light on the resilience of the dark market ecosystem and we anticipate that they may inform future research on the self-organisation of emerging online markets.

cs.CY↗

arXiv2020

Adaptive Combinatorial Allocation

We consider settings where an allocation has to be chosen repeatedly, returns are unknown but can be learned, and decisions are subject to constraints. Our model covers two-sided and one-sided matching, even with complex constraints. We propose an approach based on Thompson sampling. Our main result is a prior-independent finite-sample bound on the expected regret for this algorithm. Although the number of allocations grows exponentially in the number of participants, the bound does not depend on this number. We illustrate the performance of our algorithm using data on refugee resettlement in the United States.

econ.EM↗

arXiv2020

The Equilibrium Existence Duality: Equilibrium with Indivisibilities & Income Effects

We show that, with indivisible goods, the existence of competitive equilibrium fundamentally depends on agents' substitution effects, not their income effects. Our Equilibrium Existence Duality allows us to transport results on the existence of competitive equilibrium from settings with transferable utility to settings with income effects. One consequence is that net substitutability---which is a strictly weaker condition than gross substitutability---is sufficient for the existence of competitive equilibrium. We also extend the ``demand types'' classification of valuations to settings with income effects and give necessary and sufficient conditions for a pattern of substitution effects to guarantee the existence of competitive equilibrium.

econ.TH↗

arXiv2019

Complexity of Stability in Trading Networks

Efficient computability is an important property of solution concepts in matching markets. We consider the computational complexity of finding and verifying various solution concepts in trading networks-multi-sided matching markets with bilateral contracts-under the assumption of full substitutability of agents' preferences. It is known that outcomes that satisfy trail stability always exist and can be found in linear time. Here we consider a slightly stronger solution concept in which agents can simultaneously offer an upstream and a downstream contract. We show that deciding the existence of outcomes satisfying this solution concept is an NP-complete problem even in a special (flow network) case of our model. It follows that the existence of stable outcomes--immune to deviations by arbitrary sets of agents-is also an NP-hard problem in trading networks (and in flow networks). Finally, we show that even verifying whether a given outcome is stable is NP-complete in trading networks.

cs.CC↗

arXiv2017

Interpreting Economic Complexity

Two network measures known as the Economic Complexity Index (ECI) and Product Complexity Index (PCI) have provided important insights into patterns of economic development. We show that the ECI and PCI are equivalent to a spectral clustering algorithm that partitions a similarity graph into two parts. The measures are also related to various dimensionality reduction methods and can be interpreted as vectors that determine distances between nodes based on their similarity. Our results shed a new light on the ECI's empirical success in explaining cross-country differences in GDP/capita and economic growth, which is often linked to the diversity of country export baskets. In fact, countries with high (low) ECI tend to specialize in high (low) PCI products. We also find that the ECI and PCI uncover economically informative specialization patterns across US states and UK regions.

econ.GN↗

arXiv2015

Trading Networks with Bilateral Contracts

We consider a model of matching in trading networks in which firms can enter into bilateral contracts. In trading networks, stable outcomes, which are immune to deviations of arbitrary sets of firms, may not exist. We define a new solution concept called trail stability. Trail-stable outcomes are immune to consecutive, pairwise deviations between linked firms. We show that any trading network with bilateral contracts has a trail-stable outcome whenever firms' choice functions satisfy the full substitutability condition. For trail-stable outcomes, we prove results on the lattice structure, the rural hospitals theorem, strategy-proofness, and comparative statics of firm entry and exit. We also introduce weak trail stability which is implied by trail stability under full substitutability. We describe relationships between the solution concepts.

cs.GT↗