On the use of Malmquist productivity indices for intertemporal performance assessment by means of composite indicators
Bibliographic record
Abstract
The family of Malmquist non-parametric productivity indices using either a single constant input or a single constant output is a consistent approach for measuring performance change in terms of composite indicators. In this setting, testing for Hicks-neutral technical change is important, since in its presence the choice among these Malmquist indices is unnecessary, whereas its absence points towards the asymmetric effects of overarching events and policies across the evaluated units. In this paper, we provide an empirical test for Hicks-neutral technical change by relying on recent developments on inference in dynamic nonparametric models of production. We then use it to examine the pattern of technical change in two study cases related to the UNDP Human Development Index and a social inclusion composite indicator. In both cases, country performance change over time is entirely attributed to technical change, which however is economically significant only in the latter case.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".