Countercyclical Bank Capital Requirement and Optimized Monetary Policy Rules
Why this work is in the frame
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Bibliographic record
Abstract
Using BoC-GEM-Fin, a large-scale dynamic stochastic general equilibrium (DSGE) model with real, nominal, and financial frictions featuring a banking sector, we explore the macroeconomic implications of various types of countercyclical bank capital regulations. Results suggest that countercyclical capital requirements have a significant stabilizing effect on key macroeconomic variables, but mostly after financial shocks. Moreover, the bank capital regulatory policy and monetary policy interact, and this interaction is contingent on the type of shocks that drive the economic cycle. Finally, we analyze loss functions based on macroeconomic and financial variables to arrive at an optimal countercyclical regulatory policy in a class of simple implementable Taylor-type rules. Compared to bank capital regulatory policy, monetary policy is able to stabilize the economy more efficiently after real shocks. On the other hand, financial shocks require the regulator to be more aggressive in loosening/tightening capital requirements for banks, even as monetary policy works to counter the deviations of inflation from the target.
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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 | 0.000 |
| 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 it