The Study of Dynamic Relationships between Flow of Foreign Direct Investment and the Pattern of Comparative Advantage in the Polish Economy
Bibliographic record
Abstract
The paper presents the dynamic relationship between foreign direct investment (FDI) in Poland and the values of revealed comparative advantage indexes of goods with different share of the production factors. For this purpose, the vector error correction model (VECM) was used. To investigate the feedback between the variables there are analyzed the results of the impulse response functions and forecast error variance decomposition.The results provide a benchmark for the verification of the theory of dynamic comparative advantages (Ozawa, 1992), which is an important cell in a long-term relationship between FDI and competitiveness of the economy. One of the main conclusions of the article is to determine the simultaneous occurrence of symptoms typical for the different phases of economic development in the Ozawa model. For the calculations were used data from the Central Statistical Office covering the period from the first quarter of 2002 to the fourth quarter of 2012.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".