The Fiscal Impact of Trade Tariff Cuts: Long‐Series Historical Evidence
Bibliographic record
Abstract
Abstract Contemporary empirical evidence shows that trade tariff cuts have a negative impact on customs revenue in low‐income countries. This article documents the historical experience of the US and Canada from 1870 to 1996, which shows that customs revenue declined in these two countries with falling trade tariffs. Such a decline should therefore have been anticipated while advocating trade liberalisation in low‐income countries, and trade reform hyphenated with fiscal reform, so as to identify compensating revenue ex ante . A recent cross‐country study by Baunsgaard and Keen covering the period 1975–2006 fails to find complete replacement from other revenue sources in low‐income countries even in the long run, let alone concurrently. This is an issue affecting countries all across the size spectrum, and is of immediate importance in the context of the slow progress towards achieving the Millennium Development Goals. Another problem, limited to large federal countries in the developing world, is that trade taxes are levied exclusively by the national government, so that compensating revenue from a source not similarly restricted to that level has the potential to destabilise the balance of power within the federation. Policy Implications The Millennium Development Goals call for fiscal revenue with which to finance the public expenditure required. Policy advice to the developing world advocating trade liberalisation has neglected the revenue impact of trade tariff cuts. This article documents the historically negative impact of trade tariff cuts on customs revenue in the US and Canada, on the basis of which the fiscal impact in the developing world should have been anticipated, and compensating revenue identified ex ante . VAT, which is identified as the optimal replacement source for lost trade tariff revenue, may not be optimal from a political economy perspective in some fiscal federations. Recent cross‐country evidence, showing that the revenue loss from reduced trade tariffs persists in the long run, highlights the difficulty of finding complete replacement from other revenue sources, and shows that the policy homework for achievement of the MDGs remains sadly unaddressed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".