The Financial Impact of State Tax Regimes on Local Economies in the U.S.
Bibliographic record
Abstract
We examine the complex relationship between taxes and local economies at the county level. Specifically, we explore the impacts of different types of state-level taxes, including income and payroll taxes, property and other taxes, as well as sales tax, on key economic performance indicators. Our study aims to comprehensively analyze how state-level taxation influences entrepreneurship, innovation, labor markets, and overall economic growth in local communities. The findings consistently demonstrate that taxes harm local economies, although the magnitude of the impact varies depending on the specific type of tax. Notably, a 10 percent increase in income and payroll taxes leads to a 3 percent drop in the nonfarm proprietors employment rate, 0.3 fewer patents per 1000 people, and a USD 3000 decrease in GDP per capita. A similar tax hike in sales taxes results in a 4.5 percent decline in the nonfarm employment rate and a 0.2 patent reduction per 1000 people. Property and other taxes also harm the economy: a 10 percent increase is linked to a 5.3 percent fall in the nonfarm proprietors employment rate, a 7.5 percent rise in local unemployment, and a USD 55,000 drop in regional GDP per capita.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".