Replication Files for Baumgärtner, Zahner (2025)

Replication Files for

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------- Whatever it takes to understand a central banker - Embedding their words using neural networks. -----------
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Contents and Replication Instructions

This repository contains the replication code and dataset for the study. The current version reflects the code and data as of March 13, 2025. We maintain an updated GitHub repository at the following link, where we implement improvements, fix potential issues, and address code optimizations:

https://github.com/martinbaumgaertner/whatever_it_takes

This replication package includes: (i) detailed ReadMe file with clear, step-by-step instructions for replication. (ii) a mapping of scripts to outputs, specifying which scripts generate each figure and table in the paper. (iii) All necessary datasets and source code to fully replicate the analysis, including embedding generation, model training, and final application.

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Code Annotations and System Requirements

The code includes extensive comments for ease of understanding, along with specific guidance and alternative approaches for users without access to high-performance computing (HPC) resources. The replication process has been successfully executed on modern hardware (e.g., a recent MacBook Pro) within approximately a few dozen hours. However, users with less powerful systems may encounter performance limitations. To address this, we have explicitly annotated hardware-related constraints in the code and provided shortcuts, such as the use of pre-trained models, to facilitate replication. Some larger shortcuts (e.g., those used in Section 3.3 for measuring “rhetorical stability”) are not included in this replication package due to file size constraints (several GBs). However, these files are available upon request—please feel free to contact us if needed.