On August 28, 2025, the US Department of Commerce officially announced the release of official macroeconomic data onto the blockchain network, marking the first attempt by the US government to provide official statistical data through blockchain. According to the press release from the US Department of Commerce, the US second-quarter GDP data was publicly released that day through nine major public chains including Bitcoin, Ethereum, Solana, TRON, and Stellar.
US Secretary of Commerce Howard Lutnick emphasized in a statement that this initiative responds to President Trump's vision of a 'crypto president', marking the first time that America's 'economic truth' is released in an immutable, globally accessible way.
Howard Lutnick's statement video
After the announcement, the prices of the two main technology providers collaborating with the Department of Commerce, the native token PYTH of the decentralized verification layer Pyth Network, surged over 108% within 10 hours, with market capitalization exceeding $1 billion and trading volume increasing nearly 27 times in 24 hours. The LINK token of decentralized oracle service provider Chainlink also rose by 10% within 7 hours, then retreated to the pre-announcement level, currently quoted at $24.28.
The price surge of Link and Pyth after the announcement, source: TradingView
How is macro data brought on-chain?
This collaboration is provided by the US Department of Commerce's Bureau of Economic Analysis (BEA) for macroeconomic data, with Pyth Network and Chainlink participating as decentralized verification layers and oracle partners.
Chainlink co-founder Sergey Nazarov signed the (Genius Act) at the White House, source: Chainlink
After the BEA provides data, Chainlink will launch a series of on-chain data feeds, releasing key economic indicators such as GDP, Personal Consumption Expenditures (PCE) Price Index, and Actual Final Sales onto about ten blockchains including Ethereum, Avalanche, and Optimism, with data update frequency synchronized with the official release cycle (usually updated once a month).
First batch of on-chain data: • Real GDP - Level • Real GDP - Percentage change (annual rate) • PCE Price Index - Level • PCE Price Index - Percentage change (annual rate) • Actual final sales to domestic private buyers - Level • Actual final sales to domestic private buyers - Percentage change (annual rate)
Pyth Network focuses on helping GDP data maintain cryptographic verifiability and distribution, initially providing the historical US quarterly GDP data for the past 5 years on-chain, and plans to gradually support more macro datasets such as PCE price index and actual final sales.
Pyth's data dashboard
The official press release states that the Department of Commerce has written the hash values of GDP and other data onto the blockchain to ensure the records are tamper-proof, and completed the on-chain release with the assistance of compliant exchanges like Coinbase, Gemini, and Kraken.
To date, the BEA provides data, Chainlink turns multiple indicators into cross-chain standardized data feeds, and finally, Pyth ensures a complete data loop of on-chain verifiability and long-term distribution is formed. Subsequently, macro data will be able to deeply participate in the on-chain ecosystem.
What impact does the on-chain verified data have on the ecosystem?
This government-enterprise collaboration provides a model for introducing blockchain technology to public data infrastructure, with profound significance in greatly enhancing data transparency and real-time accessibility. Official economic indicators, after being hashed on-chain, will be difficult to tamper with, reducing the likelihood of disputes arising from human modifications of statistical data.
At the same time, developers can directly access verified official data for real-time applications such as decentralized finance (DeFi) protocols and prediction markets. For example, lending protocols can automatically adjust interest rates based on GDP growth rates, and prediction markets can reference the PCE price index as a basis for inflation expectations.
Chainlink officially stated that the on-chain government data will give rise to innovative applications such as automated trading strategies, inflation-linked digital asset issuance, real-time prediction markets, immutable on-chain data dashboards, and DeFi crisis management based on macro factors. The Pyth team stated that the on-chain economic data opens a new era of transparency, accessibility, and composability, providing a more reliable data foundation for DeFi, enterprise applications, and public accountability. But which projects will these scenarios specifically materialize in?
Automated trading strategies
Chainlink Automation: A decentralized automation network that can trigger contract 'Upkeep' when preset conditions are met, often used in conjunction with Chainlink data feeds. For example, when a certain data source meets a threshold (which could be replaced with on-chain GDP/PCE indicators in the future), it automatically rebalances or executes strategy orders. Its official documentation details trigger types, network coverage, and development processes.
Gelato Automate (Web3 Functions): A multi-chain automation execution infrastructure that provides SDK and Web3 Functions, triggering trades and contract calls based on time, events, or custom logic. After macro indicators come on-chain, developers can use 'conditions - execution' to integrate GDP/PCE as a signal source into trading logic.
Set Protocol (TokenSets): An early supporter of 'programmable asset baskets' and automated rebalancing on-chain portfolio management tools, strategies can be automatically adjusted based on technical indicators/external price feeds. After macro data comes on-chain, strategy managers can incorporate macro thresholds (such as growth rate ranges) into rebalancing rules, forming a regulated quantitative asset basket.
Enhancing the composability of tokenized assets
Centrifuge (RWA Market): Bringing real-world assets (RWA) such as receivables on-chain and integrating them with DeFi, emphasizing 'composability' with broader DeFi, and has opened an RWA lending market with Morpho. After macro data comes on-chain, these RWA pools can embed macro thresholds into risk control or pricing templates, enhancing the composability with lending/derivative protocols.
Ondo Finance (OUSG / USDY): A 'tokenized US Treasury/money fund' product for qualified investors, supporting 24/7 minting and redemption, and gradually accessing multi-chain and DeFi. On-chain macro data (such as PCE, GDP) helps to use OUSG/USDY as 'macro condition-driven' collateral and liquidity components in more protocols, enhancing cross-protocol composability.
Franklin Templeton OnChain U.S. Government Money Fund: The 'on-chain money market fund' of a traditional asset management giant uses blockchain accounting and has expanded to networks including Base, Stellar, Aptos, Avalanche, Arbitrum, Polygon; SEC documents also disclose its on-chain accounting mechanisms. After macro data comes on-chain, the compliance funds' pool will have greater space for interaction with DeFi's instructions/risk control.
A new type of crypto asset
Frax Finance (FPI and sFRAX): FPI is an 'inflation-stablecoin' pegged to the US CPI-U, using on-chain mechanisms to track the inflation basket; sFRAX's yield attempts to follow the Federal Reserve's IORB (Interest on Reserves Balances), synchronizing with the macro interest rate environment through the 'IORB oracle'. With official macro data on-chain, the transparency and verifiability of inflation/rate-linked assets are further enhanced.
Synthetix (Synthetic Asset Protocol): Supporting the minting of synthetic assets that track various underlying prices (including inverse synthetic assets), relying on price feeding networks like Chainlink. In the future, using 'official macro time series' such as GDP and PCE as pricing or settlement indicators is expected to expand the category of 'macro index synthetic assets'.
Pendle Finance (Yield Tokenization: PT / YT): Splitting yield-generating assets into tradable 'principal (PT)/yield (YT)', equivalent to on-chain 'coupon separation', giving rise to a new type of 'yield-based derivative asset'. When RWA (such as OUSG, USDY) is integrated with macro data, Pendle can support richer macro yield curve trading and risk hedging.
Real-time prediction markets
Polymarket: A mainstream on-chain event prediction market that uses UMA's optimistic oracle to complete market settlements. After macro data comes on-chain, the settlement of macro-related contracts (growth rates, inflation paths, unemployment rate ranges, etc.) will be more certain and traceable.
Omen: A decentralized prediction market built using the 'conditional token' framework; this framework tokenizes 'outcomes', facilitating reuse across different applications. After macro data becomes the source of truth on-chain, applications like Omen can conveniently create 'macro-financial' cross-prediction scenarios.
Azuro Protocol: A scalable 'prediction/gambling layer' that utilizes decentralized oracles (including integration with Chainlink) to import odds and results, providing infrastructure for various prediction applications. After macro data is input as 'event/indicator feeds', Azuro can support prediction products on macro themes.
Immutable data-supported DashBoard
Dune: An open-chain data analysis and dashboard platform that allows direct SQL queries of multi-chain public data and visual sharing. After official macro data is on-chain, analysts can build linked dashboards of 'official statistics - on-chain finance - RWA liquidity', achieving verifiable public transparency.
The Graph: A decentralized indexing protocol that allows developers to structure on-chain events in the form of 'Subgraph' and provide a GraphQL query interface. After writing macro time series (such as quarterly GDP, monthly PCE) as on-chain events, they can be stably indexed by Subgraph, becoming a standard data source for various dashboards and applications.
DefiLlama: The industry's mainstream open-source DeFi data and TVL aggregation dashboard, publicly disclosing its calculation standards and data adapters. As macro data comes on-chain, aggregation dashboards like DefiLlama can juxtapose macro indicators with protocol fundamentals (TVL, revenue, leverage), facilitating cross-validation.
DeFi protocol risk management based on macroeconomic factors
Aave (× Gauntlet Risk Engine): Aave relies on Chainlink price feeds and community governance, with Gauntlet proposing parameter suggestions (such as LTV, liquidation thresholds, borrowing limits, etc.) based on market liquidity/volatility. Governance posts and reports have long recorded the 'data-driven parameter tuning' process. After macro data comes on-chain, this risk control process can introduce 'macro-on-chain' joint indicators for more timely parameter adjustments.
MakerDAO (DAI/DSR/Stable Fees): The Maker protocol maintains the stability of DAI through stable fees, liquidation mechanisms, and dynamically adjusts parameters through governance decisions; documentation and community resources detail how stable fees/DSR respond to changes in market conditions. After macro data comes on-chain, governance can more finely map macro thresholds to stable fees or collateral parameters.
Frax (sFRAX / Interest Rate Benchmarking): The yield of sFRAX attempts to follow the Federal Reserve's IORB, essentially smart-contracting 'macro interest rates'; media outlets such as Blockworks have also reported on its route of 'connecting treasury yields'. As more official macro indicators come on-chain, the Frax system can further use macro signals for stabilization mechanisms and risk thresholds.
Blockchain is welcoming a new identity
This collaboration marks a shift in the traditional paradigm of official data release. The Pyth official announcement emphasizes that this on-chain release by the Department of Commerce is not a one-time attempt, but the beginning of a long-term collaboration between government and enterprises, and in the future, it will consider bringing a broader range of economic datasets on-chain.
This move aligns with the overall direction of the Trump administration's promotion of crypto-friendly policies. Recently, the US House of Representatives passed bills such as the (2025 US Blockchain Deployment Act), aimed at consolidating America's leadership in blockchain technology. 'Bringing economic truths on-chain' is becoming an important part of the US digital strategy, not only giving the US an advantage in the digital financial space but also providing a model for other countries to follow. In the future, we might expect a global 'economic data truth' era.
As the US government takes the lead in bringing key macro data on-chain, the public data infrastructure is accelerating its transformation from traditional channels to on-chain models. The trend of 'everything can be on-chain' is gradually becoming a reality. From financial market prices to government statistical data, blockchain is ushering in a new identity as 'a new public infrastructure that enhances trust and efficiency.'
