Stock market, real estate market, and economic growth: an ARDL approach
Bibliographic record
Abstract
The paper investigates the correlation between stock market, real estate market, and economic growth in Vietnam, which is an emerging country. Quarterly data in Vietnam from the third quarter of 2004 to the third quarter of 2018 were utilized. By using the Autoregressive Distributed Lag (ARDL) approach, the results reveal that economic growth is positively associated with stock market and real estate market. An unprecedented finding of this study is that economic growth (GDP) is more correlated to stock market efficiency (SME) than net trading value by foreign investors (FI). Moreover, global financial crisis (GFC) exerts a negative impact on economic growth and real estate market in Vietnam. Further, net trading value by foreign investors (FI) also negatively influences real estate market (REM) in the short term. The study has greatly succeeded in giving first empirical evidence on the relationship between stock market, real estate market, and economic growth in Vietnam. More than that, the results show the key role of global financial crisis in this correlation. The findings are valuable to economies around the world, especially bringing a practical and meaningful value to developing countries like Vietnam.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".