Observing FDI spillover transmission channels: evidence from firms in Uganda
Why this work is in the frame
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Bibliographic record
Abstract
We observe and analyse three intra-industry foreign direct investment \n(FDI) spillover transmission channels using unique firm-level data collected from on-site interviews and observations regarding domestic \nand foreign firms operating in Uganda in 2015. Our main results are: (1) \nthe spillover effects mainly depend on the channel(s) by which they \noccur (the competition channel is most important while spillover benefits through the worker mobility and the imitation channels are less \nprevalent) and (2) both positive and negative spillover effects occur \nwithin the same channel and, moreover, effects differ by channel for \nthe same case. These are novel and challenging findings that have not \nyet been recognised in theoretical and empirical research on FDI spillovers. Our results suggest that long-term pecuniary spillover effects are \npredominantly stimulated via the competition channel and show that \nonly limited short-term and long-term technological spillover effects \noccur through the imitation and the movement of workers channels. \nThese channels are not only less prevalent, but also appear to be constrained by competition-determined spillovers. We are confident that \nthese directions for future research will have a high pay-off because, as \nshown by this exploratory fieldwork, a more complete picture of the \nspillover effects is reached when the channels are considered \nsimultaneously
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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