On the relationship between export and economic growth: A nonparametric causality-in-quantiles approach for Turkey
Bibliographic record
Abstract
This study re-examines the dynamic causal relationship between exports and economic growth in Turkey for the period from 1960 to 2018. Unlike the previous studies ignoring the presence of the potential nonlinearities in the relationship between the series; we apply a novel nonparametric causality-in-quantile methodology that relaxes the restrictive assumption of linearity and provides more reliable and inclusive inference in the causal nexus between the variables. Using the nonlinearity test, we show that the absence of causality linkages based on the linear framework is subject to a misspecification error. However, by employing the causality-in-quantiles test, we find evidence of positive causation from economic growth to export growth at low- and high-quantile ranges of export growth. Our findings highlight the emphasis on the modelling of nonlinear interactions between the variables as well as the consideration of the entire conditional distribution to avoid the risk of misleading inferences on the causality analysis.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".