Agglomeration Economies, Investment Promotion, and the Location of Foreign Direct Investment in the United States
Bibliographic record
Abstract
This paper investigates the effects of agglomeration economies and state-level promotion policies on the location of foreign direct investment (FDI) in the United States between 1977 and 1996. Specifically, it analyzes the level of foreign-owned real gross property, plant, and equipment (PPE) using a stock-adjustment model of investment in a dynamic panel data framework. We find that agglomeration forces measured in terms of same-country PPE in adjacent states had a robust 0.15 elasticity on own-state, same-country investment. Although the adjustment towards equilibrium levels of investment appears to have been slow, it was much quicker in states that attracted automobile investment or that shared metropolitan areas with other states. General investment incentives do not seem to have had an effect on the location of FDI, but policies targeting multinational enterprises (i.e., unitary taxation and state foreign offices) had an effect on the level of inward investment as measured by PPE.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".