Replication Data for: Populism and De Facto Central Bank Independence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Replication data and code for all tables and figures in the paper as well as all robustness checks and figures in the online-only appendix. Requires Stata 14.2+ and R 4.1.2+ to run. Although central bank independence is a core tenet of monetary policy-making, it remains politically contested: In many emerging markets, populist governments are in frequent public conflict with the central bank. At other times, the same governments profess to respect the monetary authority’s independence. We model this conflict drawing on the crisis bargaining literature. Our model predicts that populist politicians will often bring a nominally independent central bank to heel without having to change its legal status. To provide evidence, we build a new data set of public pressure on central banks by classifying over 9000 analyst reports using machine learning. We find that populist politicians are more likely than non-populists to exert public pressure on the central bank, unless checked by financial markets, and also more likely to obtain interest rate concessions. Our findings underscore that de jure does not equal de facto central bank independence in the face of populist pressures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it