💥 NEW: Patent-based IV for identification of technology news shocks💥 NEW: Monthly Utilization-Adjusted TFP for the US💥 NEW: UKMPD High frequency event study database for BOE communication events💥 COMING SOON: High-frequency event study database for Fed communication eventsSep 2025
C O D E & D A T A
The content of this section is organised per topic. Replication material for individual papers is marked within each topic.
D A T A
MONTHLY TFP & IV FOR TECHNOLOGY NEWS SHOCKS
IV for Technology News Shocks 💥
Monthly TFP for the US economy 💥
Constructed using interpolation based on higher-frequency data on John Fernald’s quarterly estimates of TFP (2014 vintage) as in Miranda-Agrippino, Hacioglu-Hoke and Bluwstein (2025), “Patents, News, and Business Cycles”
💾 download
MONETARY POLICY EVENT-STUDY DATASETS
UKMPD💥
Continuously updated collection of monetary policy surprises around Bank of England policy communication events as in Braun, Miranda-Agrippino and Saha (2025), “Measuring Monetary Policy in the UK: The UK Monetary Policy Event-Study Database”
USMPD💥
coming soon!
INSTRUMENTS FOR MONETARY POLICY SHOCKS
High-frequency
Instruments for conventional Fed and BOE monetary policy shocks as in Miranda-Agrippino (2016), “Unsurprising Shocks: Information, Premia, and the Monetary Transmission”
💾 download
Instrument for conventional Fed monetary policy shocks as in Miranda-Agrippino and Ricco (2021), “The Transmission of Monetary Policy Shocks”
💾 download
Instruments for unconventional Fed and ECB monetary policy shocks as in Miranda-Agrippino and Nenova (2022), “A Tale of Two Global Monetary Policies”
💾 download
Narrative
Monthly and quarterly extensions of Fed monetary policy shocks as in Romer and Romer (2024)
💾 download
GLOBAL FINANCIAL CYCLE FACTOR
Original
Common factor across world risky asset prices as in Miranda-Agrippino and Rey (2020), “US Monetary Policy and the Global Financial Cycle”
💾 download
Extensions (same methodology, larger and more up-to-date underlying data)
REAL-TIME MIXED-FREQUENCY DATASET FOR THE UK ECONOMY
Real-time mixed-frequency dataset for the UK used in Anesti, Galvao & Miranda-Agrippino (2018), “Uncertain Kingdom: Nowcasting GDP and its Revisions”
💾 download
MatLab CODE
IMPULSE RESPONSE FUNCTIONS
Proxy SVAR/SVAR-IV
Frequentist VAR identified with either Cholesky or Instrumental Variables as in Miranda-Agrippino (2016), “Unsurprising Shocks: Information, Premia, and the Monetary Transmission”
💾 download
BVAR/BVAR-IV & LP/LP-IV
Bayesian VAR with standard NIW priors and Local Projections identified with either Cholesky or IV as in Miranda-Agrippino and Ricco (2021), “The Transmission of Monetary Policy Shocks”
💾 download
BLP/BLP-IV
Bayesian Local Projections identified with either Cholesky or IV as in Ferreira, Miranda-Agrippino and Ricco (2023), “Bayesian Local Projections”
💾 download
FACTOR MODELS
BASICS
Estimation of factor models under different modelling assumptions. 1) Static and Exact with spherical idiosyncratic variance (PC); 2) Static with diagonal idiosyncratic variance (EM algorithm); 3) Dynamic Factor Model (EM algorithm). The code is associated with the Lecture Slides on Factor Models prepared for a guest lecture at the University of Surrey
DFM with Block Structure
DFM with loading restrictions for estimation of block-specific factors as in Miranda-Agrippino & Rey (2020), “US Monetary Policy and the Global Financial Cycle”. Due to restrictions on the distribution of asset price data, the demo code reads US macro variables instead
NOWCASTING WITH DATA REVISIONS: RA-DFM
Revision-Augmented DFM as in Anesti, Galvao & Miranda-Agrippino (2018), “Uncertain Kingdom: Nowcasting GDP and its Revisions”