A Study on the Improvement of Income Tax reporting For Business Combinations in Mongolia
Bibliographic record
Abstract
In line with the international trend and practice of deeming associated entities as a single economic unit and assessing the taxable income at the group level based on the consolidated income tax statements, many countries in the world including the United States, Australia, New Zealand, and France allow the preparation of consolidated income tax returns and provide special tax credits and exemptions for transactions between the parent and subsidiaries companies of the group, unrealized gains (losses) arising from them, and intercompany dividends. This study aims to examine the needs and demand to prepare a consolidated income tax report, the current practice of business combinations to file income tax returns, and some issues related to the methodology of preparing a consolidated income tax statement. This study also attempts to prepare a consolidated income tax statement form for national business combinations according to the international trend within the framework of the currently acting laws and regulations of Mongolia and to prepare recommendations for improving the consolidated income tax reporting for the business combinations. This paper uses a Ten-step methodology for recording the impact of income tax within the framework of IFRS used in the research of B.Byambakhishig (2017). Our data covers separate financial statements, income tax reports, intercompany transactions, and other related financial data of "AM" LLC (Canadian-invested mining company) and its fully controlled "ASI" LLC, which operates business in mining subcontracting, software development, and analytics. The study lacks a recording of the impact of income tax and income tax consolidation, therefore, a further study will be conducted on the consideration related to the analysis of the Consolidated Income Tax Statements.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".