Determinants of foreign direct investment inflow in real estate sector
Why this work is in the frame
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Bibliographic record
Abstract
Many of the previous research shows that ups and downs of real estate prices are affected by the foreigners' investments. Some countries such as Australia have implement relevant measures to lower the incentives of foreigners to invest in their housing sector. The objective of this paper is to examine the major determinants of FDI inflow in real estate sector in five countries, i.e. Korea, Japan, Australia, Canada and the UK via Artificial neural networks. It shall investigate the relationship between foreign direct investment inflow in real estate sector, residential property price index, gross domestic product per capita, global house price index growth rate, global housing price index, effective exchange rate, housing price to income index and natural disaster. The results show that there are different determinants in different countries. While global housing price index plays the most important role in foreign direct investment inflow in Korea, Japan and UK, Gross domestic product and house price to income ratio is the most important factor in Canada and Australia respectively.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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