Bibliographic record
Abstract
We develop open-economy variants of the old Friedman-Schwartz and the new Lucas-Sargent-Wallace monetarist models to investigate the puzzle of monetary neutrality. We further introduce financial aggregation theories into the models – theories that are, in the modern world, consistent with financial liberalization and innovations in the banking payments system. We then study the theoretical and business-cycle relationships between real output and financial aggregates, interest rates, exchange rate, and prices using Canadian quarterly data for the period 1959:1 to 2002:1. We find that the open-economy variants of the monetarist models with aggregation-theoretic financial aggregates perform the best in producing significant sign patterns that are predicted by theory – resolving the ‘twin ’ money and interest rate puzzle in previous research. Furthermore, Monte Carlo experiments show that large percentage of real output variance is explained by shocks to aggregation-theoretic financial aggregates relative to other variables--principally, the rate of interest and the exchange rate. Thus, there is no difference between anticipated and unanticipated monetary shocks. The policy implication is that the correct measurement of money and its opportunity cost as well as a robust specification of the money-output relationship improves the information content of monetary policy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.619 | 0.407 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".