Hurdles to Exporting: A Decomposition of Fixed Export Costs
Bibliographic record
Abstract
When firms enter a new foreign market, they not only face per-unit export costs such as tariff and transport costs, but also fixed export costs such as information and compliance costs that do not vary with export volume. This paper distinguishes export market specificity and evaluate the impact of market-specific fixed trade costs on firm export decisions by considering firmdestination trade relationship. By decomposing fixed export costs into information costs and compliance costs, we empirically investigate how their presence impacts the decision of whether or not to export to a specific destination. Using a panel of bilateral trade flow data at SITC4-digit industry level from 1991-2000 to approximate export decisions of heterogeneous firms, results show that information costs and compliance are equally prohibitive to export. Paying information costs decreases the probability of export by 9 to 16 percentage points and acts as a prior hurdle in determining whether or not to export to a specific foreign market. Meanwhile, compliance cost decreases the probability of export by 16 to 18 percentage points.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".