Blockchain Association Calls For Modernized Crypto Tax Rules In New Release

bitcoinistPublicado em 2026-02-25Última atualização em 2026-02-25

Resumo

The Blockchain Association has released a proposal titled "Digital Asset Tax Principles" to modernize U.S. crypto taxation. The framework calls for practical rules that reflect the realities of digital assets, aiming to reduce compliance burdens and support U.S. competitiveness. Key recommendations include a de minimis exemption for small transactions, treating stablecoins as cash, and taxing mining and staking rewards only upon sale. It also advocates for consistent treatment of similar economic activities, nonrecognition for non-material changes, and privacy-conscious reporting. The proposal seeks to close loopholes while encouraging onshore digital asset activity. Currently, the IRS treats crypto as property, subject to capital gains or ordinary income tax.

As congressional momentum behind the crypto market structure bill known as the CLARITY Act slows, the Blockchain Association has stepped forward with its own proposal aimed at shaping the next phase of digital asset regulation in the United States.

On Tuesday, the Washington-based nonprofit — which represents more than 125 crypto companies — released a document titled Digital Asset Tax Principles.

The framework is intended to guide lawmakers as they revisit tax policy for digital assets amid broader regulatory discussions. The association has also participated in White House meetings over the past month related to the CLARITY Act.

Blockchain Association’s Proposal

In announcing the framework, Summer Mersinger, Chief Executive Officer of the Blockchain Association, said lawmakers must ensure that any tax legislation reflects the economic realities of how digital assets function.

She emphasized that tax rules should be practical for both taxpayers and regulators, adding that the group’s recommendations are designed to provide clarity while reinforcing US competitiveness in the global digital economy.

The principles outlined in the document focus heavily on making crypto taxation workable in practice. One major recommendation is the creation of a meaningful de minimis exemption for small digital asset transactions, which would ease compliance burdens for everyday users.

The association also proposes that stablecoins be treated as cash for tax purposes, arguing that such treatment would prevent disproportionate reporting requirements for routine payments.

Another key theme is functional consistency. The group argues that economically similar activities should be taxed similarly, regardless of the technical structure behind them.

For example, it recommends that mining and staking rewards be treated as self-created property, taxable only when the tokens are sold or otherwise disposed of, and sourced to the owner’s residence.

Crypto Tax Plan

The framework also addresses economic ownership, urging lawmakers to allow nonrecognition treatment for transactions that do not materially change a taxpayer’s economic exposure.

In addition, the association highlights privacy and safety concerns, advocating for reporting requirements that achieve legitimate enforcement goals without unnecessarily compromising taxpayer privacy.

Global competitiveness is another pillar of the proposal. The Blockchain Association suggests implementing a safe harbor for foreign individuals trading on US exchanges and adopting policies that encourage digital asset activity to remain onshore rather than move abroad.

It also calls for anti-abuse provisions that close wash sale loopholes while preserving the ability of Americans to use digital assets in everyday transactions. Further recommendations aim to improve access and flexibility within the tax system.

Currently, the Internal Revenue Service (IRS) classifies crypto as property rather than currency. As a result, most crypto-related activity falls into one of two categories: capital gains or ordinary income.

The 1D chart shows the total crypto market cap valuation at $2.19 trillion. Source: TOTAL on TradingView.com

Featured image from OpenArt, chart from TradingView.com

Perguntas relacionadas

QWhat is the main purpose of the document released by the Blockchain Association?

AThe document, titled 'Digital Asset Tax Principles,' is a framework intended to guide lawmakers in revisiting tax policy for digital assets, aiming to provide clarity and reinforce US competitiveness in the global digital economy.

QWhat is one major recommendation for small digital asset transactions proposed by the Blockchain Association?

AThe association recommends creating a meaningful de minimis exemption for small digital asset transactions to ease compliance burdens for everyday users.

QHow does the Blockchain Association propose that stablecoins be treated for tax purposes?

AThe association proposes that stablecoins be treated as cash for tax purposes to prevent disproportionate reporting requirements for routine payments.

QWhat treatment does the association recommend for mining and staking rewards?

AThe group recommends that mining and staking rewards be treated as self-created property, taxable only when the tokens are sold or otherwise disposed of, and sourced to the owner's residence.

QWhat is the current classification of cryptocurrency by the Internal Revenue Service (IRS)?

AThe IRS currently classifies crypto as property rather than currency, meaning most crypto-related activity falls into one of two categories: capital gains or ordinary income.

Leituras Relacionadas

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbitHá 43m

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbitHá 43m

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHá 47m

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHá 47m

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHá 47m

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbitHá 47m

Trading

Spot
活动图片