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.
Bibliographic record
Abstract
Purpose The purpose of this paper is to present an up-to-date estimation of the tax gaps (TGs) of 35 countries (28 EU member states and 7 additional countries – Australia, Canada, Japan, New Zealand, Turkey, Switzerland and the USA, both as a percentage of the gross domestic product (GDP) and a nominal value (in US$). Design/methodology/approach The authors’ empirical study was carried out on 35 selected countries. To estimate the TG, indirect methodology has been applied, where the basic components used in the estimation procedure are the level of the shadow economy estimated with the multiple indicators multiple causes method, the GDP at current prices (in US$), the total tax rate (TTR) of a given country and the indirect method of follow-up and estimation of lacking data. Findings The basic finding of the research is that the level of the TG is determined individually for a given country and is strongly correlated with the GDP, i.e. if the GDP is high, the TG as the percentage of the GDP is lower in the majority of countries. It is particularly easily noticeable in countries such as the USA (TG – 3.8 per cent of the GDP), the Great Britain (TG – 3.2 per cent of the GDP) or Japan (TG – 4.3 per cent of the GDP). Research limitations/implications A limitation of the adopted research method is the lack of application of direct (supplementary) methods which would include potentially lost contributions from foreign sources and not registered taxpayers. Another research constraint is that the authors’ estimations do not take into account the so-called direct top-down approach based on the VAT Theoretical Total Liability. The weakness of the adopted procedure of estimation is also the use of TTR only instead of comparative approach including tax burdens and average tax rate. Practical implications TG has recently become a hotly debated issue and poses a big challenge to the public finance in many countries. The paper provides some recommendations for the policymakers how to reduce the size of the TG. Social implications Tax evasion and tax avoidance leading to the emergence and expansion of the TG erode the business ethics and distort the rules of fair competition, thus undermining the social trust and moral infrastructure of business transactions. Originality/value One of the major research findings is that 30 per cent of the TG in a given country is determined by the TTR, which – for the first time – provides empirical proof that tax policy (as part of overall economic policy) plays an important role and that it may determine the fiscal effectiveness of a given country.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it