Foreign Shareholdings Impact on Efficiency of the Acquired Local Banks in Indonesia
Bibliographic record
Abstract
The motivation of the studies is to investigate the impact of foreign shareholding originated from developed and developing countries on the efficiency of acquired local banks in Indonesia during 2007-2017 by including Corporate Governance as a moderating variable.Methodology: Using the secondary aggregate data of 29 commercial banks acquired by foreign shareholders, a panel regression model using econometrics methods of GLS, and DEA was applied to examine the effects of percentage of foreign shareholdings on efficiency of the acquired local banks. The main findings; First, percentage of foreign shareholdings positively affecting efficiency of acquired local banks only if the foreign shareholders is originated from developed countries. Second, the level of economic advancement of the country of origin of foreign shareholders has significant effects on the efficiency of the acquired local banks. Third, the increase in the size of the Board of Directors tends to decrease the efficiency of the acquired local banks and fourth, the presence of Foreign Director has a positive moderating effect on strengthening the effect of percentage of foreign shareholdings on the efficiency of the acquired local banks. Overall, the originality of this studies is that the percentage of foreign shareholdings and its country of origin are two combined factors that cannot be separated in affecting the level of efficiency of its acquired local bank and the fact of significant positive moderating effect of Foreign Director. As policy consideration, monetary authority need to perform strict due diligence on prospective foreign shareholders specifically originated from developing countries, advise banks to maintain the existence of Foreign Director and to encourage small local banks to be merged prior to the acquisition by foreign shareholders.
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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) | 0.000 | 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) | 0.003 | 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".