Federal tax policies, congressional voting and natural resources
Bibliographic record
Abstract
Abstract Can abundance of natural resources affect legislators' voting behaviour over federal tax policies? We construct a political economy model of a federalized economy with district heterogeneity in natural resource abundance. The model shows that representatives of natural resource‐rich districts are more (less) willing to vote in favour of federal tax increases (decreases). This occurs because resource‐rich districts are less responsive to federal tax changes due to the immobile nature of their natural resources. We test the model's predictions using data on roll‐call votes in the US House of Representatives over the major federal tax bills initiated during the period of 1945–2003, in conjunction with the presence of active giant oil fields in US congressional districts. Our identification strategy rests on plausibly exogenous giant oil field discoveries and exploitation and narrative‐based aggregate federal tax shocks that are exogenous to individual congressional districts and legislators. We find that: (i) resource‐rich congressional districts are less responsive to changes in federal taxes and (ii) representatives of resource‐rich congressional districts are more (less) supportive of federal tax increases (decreases), controlling for legislator, congressional district and state indicators. Our results indicate that resource richness is approximately half as dominant as the main determinant, namely party affiliation, in driving legislators' voting behaviour over federal tax policies.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".