Trade facilitation in Asia and the Pacific : which policies and measures affect trade costs the most?
Bibliographic record
Abstract
How much of international trade costs can be mitigated through implementation of trade facilitation measures and policies?What measures and policies affect trade costs the most?This paper presents findings from an initial analysis of new non-tariff trade cost estimates and their determinants, based on a bilateral database of comprehensive trade cost maintained by ESCAP.Although trade costs consist for the most part of non-tariff trade costs, tariff cuts accounted for a very significant portion of trade costs reduction between 1996-99 and 2004-07.That said, most countries are found to have reduced their non-tariff policy-related trade costs between 1996 and 2007.Among the top trade facilitating economies are Malaysia, the United States, China, Republic of Korea and Thailand, with Japan and Germany following closely.The dominance of Asian countries in the ranking is fully consistent with the trade-led growth strategies of these economies and their emphasis on reducing international trade costs.The more detailed analysis of bilateral non-tariff policy-related trade costs further reveals that ASEAN developing countries often faced higher such costs when trading with one another than with the United States or Japan in 2007.However, while the trade costs of many developing countries with developed countries have remained roughly unchanged since 1996, their trade costs with other developing countries have often sharply decreased between 1996 and 2007 -at least within ASEAN.A closer look at the bilateral trade costs of large Asian economies revealed that China, Republic of Korea and Japan have achieved similar levels of trade facilitation, but that India has lagged behind.China impressively reduced its trade costs with all 13 partner economies examined in our study.Nontariff policy-related trade costs between China and India decreased significantly over the past 10 years.Results of the non-tariff policy-related trade costs modeling exercise strongly suggest that improving port efficiency (liner shipping connectivity) and access to information and communication technology facilities is essential to reducing trade costs.Policies aimed at liberalizing logistics and information technology services and increasing competition among service providers should therefore be readily considered, with a view to maximizing efficiency at any given level of hard infrastructure development.Establishment of public-private partnerships to accelerate the development of the national IT and transport and logistics infrastructure may also be actively pursued.The econometric results also supports the view that, given limited resources available, focusing on improving the overall business environment may be often more effective in facilitating trade than implementing soft measures solely targeted at speeding up movement of goods between factory and the port (or viceversa).
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".