The determinants of FDI location choice in China: a discrete-choice analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study addresses two questions: What are the determinants of foreign direct investment (FDI) location choice in China? What are the factors that determine investors’ choice between ‘Economic zones’ in China on one hand, and ‘other cities’ of China on the other hand? This study shows that FDI location choice is sensitive both on the endowment conditions in different regions/cities/economic zones in China as well as on the country of origin of the FDI. Based on a data set of 1218 observations, the results of the binary logit regressions indicate that the protection of intellectual rights, agglomeration economies, investments in education and gross regional product affect the location choice of FDI in China. This choices, however, varies depending on the origin of the FDI. Policy makers can use these findings to channel FDI to targeted regions/ cities.
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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 | 0.000 |
| 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 | 0.000 |
| 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 it