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Record W3096390177 · doi:10.31410/eman.2020.55

AN ANALYSIS OF THE EU’S INVESTMENT POLICY AFTER CETA: EFFECTS ON THE BULGARIAN ECONOMY

2020· article· en· W3096390177 on OpenAlexaboutno aff
Nikolay Marin, Mariya Paskaleva

Bibliographic record

VenueInternational Scientific Conference EMAN. Economics & Management: How to Cope With Disrupted Times · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsBulgarianInvestment (military)Order (exchange)Foreign direct investmentInternational economicsBusinessInternational tradeEconomicsMacroeconomicsPolitical science

Abstract

fetched live from OpenAlex

In this paper we analyze the changes of the EU’s investment policy provoked by the mixed trade agreements. The EU’s investment policy has turned towards attaining bilateral trade agreements. One of these “new-generation” agreements is the Comprehensive Economic and Trade Agreement (CETA). It is in a process of being ratified by the national parliaments of the EU members. This study is focused on the general characteristics of CETA and the eventual problems posed by its regulatory and wide-ranging nature. We prove that the significance of this agreement pertains not only to the economic influence, that it will have on the European and Canadian economies, but CETA is also the first trade agreement to have been negotiated with a focus on investment protection and a change in the EU’s investment policy. The current study reveals the influence arising from the conclusion of CETA on the Bulgarian economy with an emphasis on electronic industry, machinery industry and manufacturing. We estimate both – the direct and indirect effects on Bulgaria’s exports, imports, value added and employment. In order to estimate the influence, we apply the multi-regional input-output model. It is proved that CETA will have a low but positive impact on the Bulgarian economy. After constructing different scenarios of development, we prove that the influence of CETA on the Bulgarian economy will amount to 0.010% GDP. The average total employment will be increased by more than 172 jobs in Bulgaria, which in turn, relative to the labor market, represents less than 0.01% of the total employment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
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 score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.215
Teacher spread0.187 · 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.

Study designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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Same venueInternational Scientific Conference EMAN. Economics & Management: How to Cope With Disrupted TimesSame topicGlobal trade and economicsFrench-language works237,207