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Record W4366829994 · doi:10.37394/23207.2023.20.81

A Statistical Analysis of the Impact of Tourism on Economic Growth in Albania

2023· article· en· W4366829994 on OpenAlexaboutno aff
Miftar Ramosacaj, Elmira Kushta

Bibliographic record

VenueWSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsTourismGranger causalityQuarter (Canadian coin)Test (biology)Selection (genetic algorithm)EconomicsCausality (physics)EconomyEconometricsGeographyComputer science

Abstract

fetched live from OpenAlex

Tourism has become an important sector in Albania in recent years. After the pandemic period where the tourism industry suffered a big blow, the year 2022 has turned out to be very successful in this sector. Tourism this year is extending throughout the year, unlike previous years, which focused only on summer. In this paper, we analyzed the number of tourists and economic growth in Albania for the years 2016-2022 with quarterly frequencies (until the third quarter of 2022). The purpose of the paper is to analyze the relationship between the two variables in the short and long term periods. AIC, BIC, HQC model selection criteria are used throughout the analysis, the ADF test is used for series stationarity, the Granger test for causality and the Johansen test for co integration.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.024
GPT teacher head0.315
Teacher spread0.291 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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