Bibliographic record
Abstract
In this paper we deal with the financial sector of CANDIDE 1.1. We are concerned with the determination of the short-term interest rate, the term structure equations, and the channels through which monetary policy influences the real sector. The short-term rate is determined by a straightforward application of Keynesian liquidity preference theory. A serious problem arises from the directly estimated reduced form equation, which implies that the demand for high powered money, but not the demand for actual deposits, is a stable function of income and interest rates. The structural equations imply the opposite. In the term structure equations, allowance is made for the smaller variance of the long-term rates, but insufficient explanation is given for their sharper upward trend. This leads to an overstatement of the significance of the U.S. long-term rate that must perform the explanatory role. Moreover a strong structural hierarchy, by which the long Canada rate wags the industrial rate, is imposed without prior testing. In CANDIDE two channels of monetary influence are recognized: the costs of capital and the availability of credit. They affect the business fixed investment and housing sectors. The potential of the personal consumption sector is not recognized, the wealth and real balance effects are bypassed, the credit availability proxy is incorrect, the interest rate used in the real sector is nominal rather than real, and the specification of the housing sector is dubious.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.007 |
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 source (direct Gemma or distilled Codex), 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".