arXiv subjects

Brett Hemenway Falk

Publications and source records attributed to Brett Hemenway Falk.

5 recordsLinked to original sources

arXiv2026

The AI Layoff Trap

If AI displaces human workers faster than the economy can reabsorb them, it risks eroding the very consumer demand firms depend on. We show that knowing this is not enough for firms to stop it. In a competitive task-based model of a transitioning economy, each firm captures the full cost saving from automation but bears only a fraction of the demand loss it creates in the product market; the rest falls on rivals. This demand externality traps rational firms in an automation arms race, displacing workers well beyond what is collectively optimal. The resulting loss harms both workers and firm owners. More competition and ``better'' AI amplify the excess; wage adjustments and free entry cannot eliminate it. Neither can capital income taxes, worker equity, universal basic income, upskilling, or Coasean bargaining. A Pigouvian automation tax can. The results suggest that policy should address not only the aftermath of AI labor displacement but also the competitive incentives that drive it.

econ.TH↗

arXiv2026

Economics of NFTs: The Value of Creator Royalties

Non-Fungible Tokens (NFTs) are transforming how content creators, such as artists, price and sell their work. A key feature of NFTs is the inclusion of royalties, which grant creators a share of all future resale proceeds. Although widely used, critics argue that sophisticated speculators, who dominate NFT markets, simply price in royalties upfront, neutralizing their impact. We show this intuition holds only under perfect, frictionless markets. Under more realistic market conditions, royalties enable creators to capitalize on the presence of speculators in at least three ways: They can enable risk sharing (under risk aversion), mitigate information asymmetry (when speculators are better informed), and unlock price discrimination benefits (in multi-unit settings). Moreover, in all three cases, royalties meaningfully expand trade, implying increased transaction volume for platforms. These results offer testable predictions that can guide both empirical research and platform design.

econ.GN↗

arXiv2025

Can AI Detect Wash Trading? Evidence from NFTs

Existing studies on crypto wash trading often use indirect statistical methods or leaked private data, both with inherent limitations. This paper leverages public on-chain NFT data for a more direct and granular estimation. Analyzing three major exchanges, we find that ~38% (30-40%) of trades and ~60% (25-95%) of traded value likely involve manipulation, with significant variation across exchanges. This direct evidence enables a critical reassessment of existing indirect methods, identifying roundedness-based regressions à la Cong et al. (2023) as most promising, though still error-prone in the NFT setting. To address this, we develop an AI-based estimator that integrates these regressions in a machine learning framework, significantly reducing both exchange- and trade-level estimation errors in NFT markets (and beyond).

econ.GN↗

arXiv2022

Scaling Blockchains: Can Committee-Based Consensus Help?

In the high-stakes race to develop more scalable blockchains, some platforms (Binance, Cosmos, EOS, TRON, etc.) have adopted committee-based consensus (CBC) protocols, whereby the blockchain's record-keeping rights are entrusted to a committee of elected block producers. In theory, the smaller the committee, the faster the blockchain can reach consensus and the more it can scale. What's less clear, is whether such protocols ensure that honest committees can be consistently elected, given blockchain users typically have limited information on who to vote for. We show that the approval voting mechanism underlying most CBC protocols is complex and can lead to intractable optimal voting strategies. We empirically characterize some simpler intuitive voting strategies that users tend to resort to in practice and prove that these nonetheless converge to optimality exponentially quickly in the number of voters. Exponential convergence ensures that despite its complexity, CBC exhibits robustness and has some efficiency advantages over more popular staked-weighted lottery protocols currently underlying many prominent blockchains such as Ethereum.

cs.CR↗

arXiv2018

Properties of Constacyclic Codes Under the Schur Product

For a subspace $W$ of a vector space $V$ of dimension $n$, the Schur-product space $W^{\langle k\rangle}$ for $k \in \mathbb{N}$ is defined to be the span of all vectors formed by the component-wise multiplication of $k$ vectors in $W$. It is well known that repeated applications of the Schur product to the subspace $W$ creates subspaces $W, W^{\langle 2 \rangle}, W^{\langle 3 \rangle}, \ldots$ whose dimensions are monotonically non-decreasing. However, quantifying the structure and growth of such spaces remains an important open problem with applications to cryptography and coding theory. This paper characterizes how increasing powers of constacyclic codes grow under the Schur product and gives necessary and sufficient criteria for when powers of the code and or dimension of the code are invariant under the Schur product.

cs.IT↗