Relaxing CAFE: Foreign direct investment, NAFTA and domestic product standards
Bibliographic record
Abstract
Abstract This paper studies the effects of domestic product standards on the offshoring behaviour of automotive firms. In particular, we examine an important non‐tariff barrier to trade within US fuel economy policy—the Corporate Average Fuel Economy (CAFE) “two‐fleet rule.” By leveraging the removal of the two‐fleet rule upon implementation of NAFTA and exploiting a policy discontinuity based on vehicle characteristics, we present evidence that the costs of offshoring were reduced to a larger degree for varieties that were subject to US fuel economy rules. Specifically, we estimate that prices fell between 5% to 10% for varieties subject to the CAFE two‐fleet rule relative to varieties that were exempt from the rule. These effects are persistent, not present for manufacturers that did not offshore prior to NAFTA and are robust to variety‐specific trends. These effects also reconcile the post‐NAFTA differences in implied compliance costs between cars and trucks for our treatment manufacturer (Chrysler). Overall, the results highlight the potential costs of regional enforcement of otherwise location‐neutral product standards, which may act as a barrier to natural patterns of efficient specialization.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".