A Comparison of Alternative Methods of Monetary Aggregation: Some Preliminary Evidence
Bibliographic record
Abstract
The monetary aggregates presently computed have a number of restrictive structural characteristics which could limit their usefulness as economic indicators and policy targets, when these aggregates are used to measure the volume of liquidity or "money" in the economy. Their simple linear structure implicitly treats all the included monetary components as perfect substitutes, and imposes an additive unit-weighted utility function on all asset holders. Additionally, the traditional aggregates are very selective and exclude non-bank monetary assets. In this paper we construct and test a number of alternative, "superlative", monetary aggregates. These new aggregates have a more flexible functional form and give explicit recognition to the heterogeneous nature of various financial instruments by assigning a unique price weight to each monetary component. Superlative monetary aggregates are compared with conventional (summation) monetary aggregates in three critical areas: information content, causality, and stability. While superlative aggregates tend to follow more consistent time paths than summation aggregates, their overall performance is very mixed. Superlative monetary aggregates appear to contain less information on contemporaneous and future income levels than their summation counterparts, and fail to provide any new insights on money-income causality. Equations explaining their behaviour do, however, display greater parameter stability at broad levels of aggregation, providing weak evidence in favour of superlative aggregation. This is not the case at narrower levels of aggregation. All of these findings are generally consistent with the results of similar tests in the United States and, taken together, suggest that narrow conventional aggregates are at least as good as and perhaps better than any existing alternatives. Though superlative aggregation in general has much to recommend it, the superlative monetary aggregates appear to be affected by a number of practical and theoretical problems which may limit their viability as alternatives to the conventional money measures.
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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 | 0.072 | 0.191 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".