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Record W4387352992 · doi:10.5267/j.ac.2023.9.001

The effect of low rate of corporate taxation on foreign direct investments (FDI) and gross domestic product (GDP): A case study of ten selected countries (2018-2022)

2023· article· en· W4387352992 on OpenAlexvenueno aff
Uchenna Chinwendu Nwankwo, Emmanuel Obiora Nwakeze

Bibliographic record

VenueAccounting · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentGross domestic productCorporate taxMultinational corporationEconomicsInternational economicsMonetary economicsDescriptive statisticsBusinessDouble taxationTax avoidanceMacroeconomicsFinance

Abstract

fetched live from OpenAlex

This research was undertaken to examine the effect of low corporation tax rate on Foreign Direct Investment (FDI) inflow and Gross Domestic Product (GDP). Investors and multinational firms are very rational and therefore prefer to invest in countries where the cost of taxation will be at the barest minimum to maximize their profit. The study aimed to critically analyze the Corporate Income Tax (CIT) rates of the randomly selected countries of the world, and their respective impacts on FDI and GDP. The study is descriptive in nature, based on quantitative data, sourced from various reports of Statutory Corporate Income Tax Rates of Tax Foundation, World Bank and UNCTAD World Investment Report of 2022. Ex-post Facto research design was deployed; while data were analyzed with a General Linear Model of Multivariate Analysis of Variance (MANOVA) with the aid of SPSS version 25. The study found that low rate of corporation tax has a positive and significant effect on FDI as well as on GDP. That is, CIT rate is a dominant determinant for FDI and GDP of countries.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.043
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.016
GPT teacher head0.237
Teacher spread0.220 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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