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Record W3124505698

Trade Facilitation in India: An Analysis of Trade Processes and Procedures

2011· preprint· en· W3124505698 on OpenAlexfundno aff
Prabir De

Bibliographic record

VenueEconstor (Econstor) · 2011
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsTrade facilitationInternational tradeBusinessTrade barrierProcess (computing)International economicsRegional tradeFacilitationWorld tradeIndustrial organizationEconomicsFree tradeComputer science
DOInot available

Abstract

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Moving goods across borders requires meeting a vast number of commercial, transport and regulatory requirements.Inefficiencies in complying with these requirements often create unnecessary delays and costs.A source of tremendous inefficiencies is associated with the preparation of transport and regulatory documents, unclear border procedures, and overzealous cargo inspection.We need to understand how much these add to the costs of doing business across border and which way they affect the growth in trade.Besides, estimating time and costs of the procedures and processes would help policy makers and other stakeholders to enhance the regional and global trade.This study undertakes Business Process Analysis (BPA) to help assess the trade processes and procedures.One of the research objectives in BPA is to identify administrative and procedural barriers that unnecessarily impede the participation of more firms and more countries in regional and global trade, and propose solutions.Our BPA covers India's exports of cotton yarn to Bangladesh, fresh vegetables to Gulf and fruits to EU, and India's import of rubber tyres from Sri Lanka.The BPA maps show total time taken to complete the export procedures is about 31 days, which is very high compared to any international benchmark.The maximum time goes into getting payment from Bangladeshi importer, whereas transportation of goods comes next to it.The whole process costs an average of US$ 542 per container, of which insurance and inland transportation cost are the major components.This study also suggests that besides tariff, bottlenecks are in inland transportation, customs clearance and getting payment from importer.Unlike export of cotton yarn, the export of vegetables to Gulf is not executed through letter of credit or advance payment.However, the export of fruits to EU is done on the basis of advance payment in our particular case study.It takes about 29 days for export of vegetables and 33 days for export of fruits till the payment is received from the importers.The maximum time goes into sending the goods from India to EU, whereas payment comes next to it.In case of export of vegetables, getting payment from importer takes the most of the time, whereas transportation time comes next to it.The whole process of exporting vegetables costs an average of US$ 1573 per container, whereas the average cost is US$ 2031 per container in case of export of fruits to EU.However, in both cases, transportation cost (domestic and international) has been the major trade barrier.The time-procedure charts show that total time taken to complete the trade procedures is about 29 days for vegetables and 33 days for fruits.It also suggests that bottlenecks are in transportation, customs clearance and getting payment from importer.In case of import of rubber tyres from Sri Lanka, the trade processes and procedures are relatively simple.The import procedure of rubber tyres consists in placing order from Indian office to Sri Lankan subsidiary, clearing custom at Indian port, unloading the goods and inland transportation.It takes about 17 days to import rubber tyres from Sri Lanka including settling the payment.Contrary to popular belief, the maximum time actually goes into making the payment.Cost of inland transportation is also major barrier to trade.The whole process of importing rubber tyres costs an average of US$ 360 per container with a maximum and minimum range of US$ 393 and US$ 326, respectively.Overall, the time and cost of trade processes and procedures estimated in this study call for greater attention to trade facilitation.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.229
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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