The dynamics of banking sector and stock market maturity and the performance of Asian economies
Bibliographic record
Abstract
Purpose – The purpose of this paper is to examine the nature of causal relations between banking sector maturity, stock market maturity, and four aspects of performance and operation of the economy: economic growth, inflation, openness in trade, and the degree of government involvement in the economy. Design/methodology/approach – The authors look for possible links between the variables by conducting panel cointegration and causality tests, using a large sample of Asian countries over the period 1960-2011. Novel panel data estimation methods allow for robust estimates, using both variation between countries and variation over time. Findings – The study identifies interesting causal links among the variables deriving uniquely from our innovations. In particular, The paper finds that for all regions considered, banking sector maturity and stock market maturity are causally linked, sometimes in both directions. Furthermore, stock market maturity may lead to economic growth, both directly and indirectly through indicators such as inflation and trade openness. The findings also support the notion that economic growth affects the maturity of the stock market in most regions. Practical implications – The results lend support to the notion that a mature financial sector is a key contributor to generating economic growth. Furthermore, economic growth itself has the potential to bring about maturity in the financial sector. Originality/value – The paper uses sophisticated principal-component analysis, panel cointegration, and Granger causality tests, methods not used in this literature before. The method was applied to recent data pertaining to 35 Asian countries – a group of countries that has previously not been adopted in this literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".