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Record W4387051954 · doi:10.18174/638533

Calculating the effects of increasing the VAT on ornamental plant products in the Netherlands and the EU : update for the situation in 2023

2023· report· en· W4387051954 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

Venuenot available
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Systems and Logistics Management
Canadian institutionsImpact
Fundersnot available
KeywordsOrnamental plantRevenueAgricultural economicsBusinessUnemploymentTax revenueTariffEconomicsEu countriesInternational economicsEuropean unionFinancePublic economicsEconomic growthBiologyHorticulture

Abstract

fetched live from OpenAlex

Ornamental horticultural products are taxed at a reduced VAT rate in the Netherlands (9% rather than 21%) as well as in 14 other EU countries. Increasing VAT would have a negative impact on turnover and employment in the supply chain. These calculations show that a VAT increase in the Netherlands would lead to a loss of around €200 million in turnover in the ornamentals sector at wholesale prices (-1.6%). If VAT were to be increased in other EU countries too, this would have a particularly significant impact on the Netherlands’ exports and thus on primary production. In this scenario, the drop in turnover for the ornamentals sector (at wholesale prices) would be €930 million (-7%). The expected impact on the government’s VAT revenue would be partly offset by fewer flowers and plants being bought, and in the shorter term by a decline in tax receipts and social insurance premiums from businesses and employees, along with an increase in unemployment benefits being paid out.

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)0.013
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.093
GPT teacher head0.273
Teacher spread0.179 · 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