Institutions and Cyclicality of the Fiscal and Monetary Policies in Brazil
Bibliographic record
Abstract
This paper investigates the relationship between the quality of institutions and the cyclical properties of macroeconomic policies in the Brazilian economy in the recent period. We extend the monetary and fiscal policy rules proposed by Taylor (2000) to incorporate a proxy for institutional quality. In the empirical analysis, we estimate reaction functions for monetary and fiscal policies by the Markov-Switching method. This methodology allows us to analyze how changes in the quality of institutions might influence the guidance of the fiscal and monetary policies over the sample period. The major results maintain that both monetary and fiscal policies are significantly countercyclical in periods that exhibit higher levels of institutional quality and are pro-cyclical or acyclical in periods which exhibit lower levels of institutional quality. Thus, the quality of institutions plays a key role in the government's ability to implement countercyclical monetary and fiscal policies to stabilize the Brazilian economy over the business cycle.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".