Trust and Total Factor Productivity: What Do We Know About Effect Size and Causal Pathways?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores what is known about the relationship between trust and total factor productivity (TFP). Generalized interpersonal trust is widely considered the best summary measure for social capital, and if this is the case the impact of trust should be reflected in estimates of TFP. A systematic review of the literature on trust, incomes, growth, and TFP finds relatively few articles on the latter despite a developed literature on trust, income, and growth. Using a development accounting framework, a simple model of the relationship between trust and TFP is set out and the size of the impact of trust on TFP is estimated empirically using a cross-country panel dataset based on the European Social Survey (ESS). Despite the limitations of the ESS, estimates of the magnitude of the impact of trust on TFP are broadly similar to those from the only other similar study identified (Bjornskov and Meon, 2015), which is based on the World Values Survey. A counterfactual estimate of TFP is used to illustrate the magnitude of the effect of trust on TFP, highlighting that the impact of trust is non-trivial in real terms, even for high-trust countries.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.002 |
| 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