Monetary Policy and Financial Market Reactions from Twitter Traffic

Replication data for a 2026 study analyzing central bank announcements. The dataset contains aggregated, event-level data merging tweet-disagreement measures with high-frequency asset-price reactions around ECB, Federal Reserve, and Bank of England announcements. It was created by Masciandaro, Romelli, and Rubera and includes external series for robustness checks and Stata code to reproduce the paper's tables and figures.

Use Cases

• Analyzing the relationship between Twitter disagreement and market volatility based on event-level data.
• Replicating econometric results on monetary policy announcements based on the included Stata code.
• Conducting robustness checks on financial market reactions using the provided external series.
• Studying high-frequency asset-price reactions to ECB, Federal Reserve, and Bank of England communications.

Strengths

• Includes complete replication package with Stata code to reproduce every table and figure from the published paper.
• Data is aggregated at the event level, merging social media and high-frequency market data.
• Covers announcements from three major central banks: the ECB, Federal Reserve, and Bank of England.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The raw Twitter/X data and Refinitiv intraday tick prices cannot be redistributed, limiting full reproducibility.

Provenance

Source

Masciandaro, D., Romelli, D., and Rubera, G. (2026), 'Monetary Policy and Financial Markets: Evidence from Twitter Traffic', The B.E. Journal of Macroeconomics.

Collection Method

Aggregated from Twitter/X traffic and high-frequency asset-price data around central bank announcements; construction code is included.

Time Range

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Freshness

Last updated 2026-07-04 22:05:44; freshness should be verified.

Geography

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