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Record W7163615495

Angola’s first competition regime: learning from experience, the importance of competition regulation in merger transactions: a reflection on the South African Competition Act and the lessons for the Angolan competition commission

2019· other· en· W7163615495 on OpenAlexaboutno aff
Lisbella Patricia Guimarães Belchior

Bibliographic record

VenueOpen University of Cape Town (University of Cape Town) · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCompetition (biology)LegislationCommissionParliamentNoticeCapital (architecture)Mergers and acquisitions
DOInot available

Abstract

fetched live from OpenAlex

After being in a monopoly-controlled economy for decades, the Parliament of Angola finally recognised the necessity of institutionalising a Competition regime by enacting the Lei da Concorrência n.° 5/18, Angola's first Competition regime, which seeks to regulate Competition within the Angolan economy, and bring the country's economy in line with international best practices. In line with the Notice 2/2018 from the Angolan National Bank (BNA), commercial banks operating in Angola had until the end of the year 2018 to increase their share capital from 2.5 billion to 7.5 billion kwanzas ($35 million). This means that many banks that have a share capital below the new required minimum will have to consider alternatives, with mergers being one of them. The inclusion of this legislation in the Angolan legal system is significant as it comes at a time when the Angolan economy is expected to experience a number of corporate mergers, particularly in the banking sector. Since then, while there is still no sign of such corporate mergers taking place, the BNA has ordered the closure of two private banks, namely Banco Mais and Banco Postal on account of insufficient share capital, revoking the banking licences of the respective banks and declaring them bankrupt. In this paper, Angola's first Competition regime is examined by considering the merger evaluation process Competition authorities of Angola will now have to consider. Without losing sight of the reality that Angola is in a development phase, the paper relies on the relatively mature South African Competition regime as a significant point of reference to assess how the legislation will impact on corporate mergers in Angola. In the first chapter, the paper systematically discusses the development of Competition regimes in Canada, United States of America and South Africa. In chapter 2, the focus is placed on the merger evaluation process in Angola prior to the enactment of the Competition regime, before turning to the new merger process and examining some of the factors that have contributed to the development of the Competition Law in Angola. Emanating from this, chapter 3 continues with the discussion on the merger evaluation process, and provisions of the South African Competition Act, while contrasting it with the process the Angolan Competition authorities will have to follow. The chapter highlights the significance of public interest criteria in mergers, particularly in developing countries. Chapter 4 focuses on mergers, identifying specific challenges that horizontal and vertical mergers present to an economy, suggesting that, if not regulated effectively, horizontal mergers could lead to a situation where firms are ‘too big to fail', highlighting how firms often rely on mergers as a pretext to achieve a number of strategic objectives. The chapter discusses further key decisions taken by the South African Competition Tribunal and Commission as a point of reference. In addition, the chapter closes by evaluating the proposed changes to merger provisions contained in the South African Competition Amendment Bill. The paper ends in chapter 5 by concluding that notwithstanding the divergent legal systems and jurisdictions of Angola and South Africa, the latter's merger regulation process and approach is considerably advanced and better experienced than other developing states. Given that proper regulation contributes to effective economic growth, the Competition authorities of Angola stand to benefit from the experiences of South Africa, which offers some useful recommendations to the Angolan Competition authority.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.010
Scholarly communication0.0150.012
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.033
GPT teacher head0.242
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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