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Record W3119978661 · doi:10.1016/j.jwb.2020.101186

Host country corporate income tax rate and foreign subsidiary survival

2021· article· en· W3119978661 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of World Business · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsWestern University
FundersUniversity Research Board, American University of Beirut
KeywordsMultinational corporationSubsidiaryForeign direct investmentSample (material)International businessEconomicsCorporate taxBusinessIncome taxHost (biology)Monetary economicsInternational economicsTax avoidanceDemographic economicsDouble taxationPublic economicsMacroeconomicsFinance

Abstract

fetched live from OpenAlex

Host country tax considerations are critical to multinational enterprise (MNE) foreign direct investment decisions, but understudied in international business (IB) research. We address this gap by examining the relationship between host country corporate income tax rates (HCCITRs) and foreign subsidiary survival. We develop our hypothesis drawing upon location/country-specific advantage theory and international tax literature. Our longitudinal sample (1990–2013) comprises 13,468 MNE subsidiaries in 78 countries. Results indicate a one standard deviation (7.7 %) decrease in HCCITR increases subsidiary survival probability (at any given time) by 33 %. This effect is stronger compared to several well studied explanatory variables in IB survival analysis.

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.

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)0.001
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 score0.057
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.024
GPT teacher head0.213
Teacher spread0.189 · 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