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Record W4301186641 · doi:10.24818/jamis.2022.03006

Mandatory extraction payment disclosures and tax haven use: Evidence from United Kingdom

2022· article· en· W4301186641 on OpenAlex
Sameh Kobbi-Fakhfakh, Fatma Driss

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAccounting and Management Information Systems · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsTax havenMultinational corporationAccountingTransparency (behavior)Tax avoidanceBusinessStock exchangeSubsidiaryFinanceDouble taxationLawPolitical science

Abstract

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Research Question: Does public country by country reporting (CbCr) deter multinationals' tax avoidance practices operating in extractive industries? Motivation: Public CbCr has already been implemented for two specific sectors, namely the financial and extractive sectors. Prior studies have focused on tax avoidance of EU banks around the implementation of public CbCr requirement (Joshi et al., 2020; Eberhartinger et al., 2020; Overesch & Wolff, 2021). However, studies on how resource-extracting multinationals respond to the CbCr regulation are scarce. This study seeks to fill this gap by examining the effect of public CbCr on tax avoidance with a special focus on extractive industries. Idea: To improve fiscal transparency, Canadian and European legislators have adopted regulations requiring multinational corporations (MNCs) to provide, annually, their Extraction Payment Disclosures (EPD) (Public CbCr standard for extractive industries) to governments (EC, 2013; Natural Resource Canada, 2014). This study examines the effect of mandatory EPD adoption on the extent of tax haven use. Data: For a 10-year period surrounding the mandatory EPD adoption (2010-2019), we selected a sample of UK MNCs operating in the oil, gas, and mining sectors and listed on the London Stock Exchange. The analysis is mainly based on firm-level information taken from DATASTREAM database. Based on hand-collected data from annual reports, we measured the extent of tax haven use using the percentage of multinational subsidiaries located in tax haven jurisdictions/countries as listed in Dyreng and Lindsey (2009). An alternative list identified by the Organization for Economic Co-operation and Development (OECD) (2006) was also used in a robustness test. Tools: To examine our research question, we estimated a linear regression model with panel data using STATA software. Findings: The results show that the increased transparency resulting from public EPD does not appear to significantly affect the intensity of tax haven use. Contribution: This study extends and complements prior literature examining the effect of CbCr on tax avoidance and profit shifting by focusing on a specific setting i.e. extractive sector. To the best of our knowledge, apart from Johannesen and Larsen (2016) and Rauter (2020), no studies have provided empirical evidence on how resource-extracting multinationals respond to the EPD regulation.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.007
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 head0.039
GPT teacher head0.242
Teacher spread0.203 · 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