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Record W1971370247 · doi:10.1108/15253831211286273

A note on geographical diversification and performance of the world's largest reinsurance groups

2012· article· en· W1971370247 on OpenAlexaff
J. François Outreville

Bibliographic record

VenueMultinational Business Review · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsReinsuranceDiversification (marketing strategy)UnderwritingInternationalizationTransaction costSample (material)EconomicsBusinessFinancial economicsEconometricsActuarial scienceInternational tradeMicroeconomicsMarketing

Abstract

fetched live from OpenAlex

Purpose This paper aims to examine the relationship between geographical diversification and the underwriting performance for the world's largest reinsurance groups. It also aims to verify that the form and nature of the relationship between diversification and performance follow an S‐shaped curve with increased diversification of the largest reinsurance groups. Design/methodology/approach Analysis in the paper is based on the concept of Geographical Spread Index defined and calculated by UNCTAD. Data on largest reinsurance groups in the world are published annually by Standard & Poor's for only a limited number of reinsurance groups. To overcome the small sample problem, a re‐sampling procedure from the original sample, similar to a bootstrap sample, is used to validate the results. Findings The results show that, overall, international geographical diversification has a positive effect on a reinsurance firm's underwriting performance but that this relationship is not linear. It rather follows an S‐shaped curve. Although data limitation does not allow more sophisticated investigations, the results reported in this paper are nevertheless significant. It seems that at an early stage of expansion in proximate markets there are efficiency gains for the firm. With increased internationalization there may be a diminution in performance because of higher transaction costs or learning costs for new markets. Further expansion in foreign markets brings back efficiency and higher performance. Research limitations/implications Only cross‐section data for a small sample of companies are available and therefore it is not possible to analyze the dynamics of geographical diversification. A firm may deliberately expand for long‐term strategy reasons such as market share even though this is detrimental to medium‐run performance. Also, the analysis cannot provide any answer to the existence or not of a maximum level of international diversification beyond which performance would decline. Originality/value In the literature on firm diversification in the financial services sector, product diversification and performance has received significant attention with mixed results but except for a few papers, the internationalization aspect has not been examined. The reinsurance sector is important since reinsurance activities are, by nature, more geographically diversified than other financial activities. Furthermore, the largest European reinsurance groups dominate this worldwide market and many reinsurance companies have, in the past decade, increased their foreign direct investment and acquired other companies in part because of the belief that only very large players will have the cost advantages necessary to remain competitive in global markets.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.234
Teacher spread0.213 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2012
Admission routes1
Has abstractyes

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