Currency Depreciation, Trade Balance and Intra-Industry Trade Interactions in Turkey’s OECD Trade
Bibliographic record
Abstract
This study re-examines the determinants of Turkey’s trade balance in its manufactures trade with 33 OECD-member countries for the short-run and the long-run. Unlike other studies, in the relationships we also control the moderating effects of the availability of import substitutes proxied by intra-industry trade. We analyze quarterly aggregated time-series data of the period spanning from 1998.QI to 2015.QIII, following the autoregressive distributed lag (ARDL) bounds testing approach to the cointegration and the error correction modeling. Estimation results reveal that real effective exchange rate, together with domestic and foreign incomes are still among the core determinants of Turkey’s trade balance in the manufacturing sectors. There is no significant impact of domestic final oil prices that also include all the taxes on gasoline. The trade balance depends on domestic income negatively and the aggregated income of the OECD countries positively. The finding that real depreciation of Turkish lira against to those of Turkey’s OECD trade partners improves trade balance in both the short-run and the long-run, indicates no evidence of J-curve adjustment process. Unsurprisingly, the intra-industry trade seems to be an important factor that moderates the elasticities of trade balance to its determinants, especially to real effective exchange rate and domestic income. Overall results underline the importance of import-substitution capability besides the export-oriented production to ease the longstanding large trade deficits for Turkey.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".