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Record W2903661021 · doi:10.21608/jes.2018.21793

THE IMPACT OF FOREING DIRECT INVESTMENT IN THE PETROLEUM SECTOR ON THE EGYPTIAN ENVIRONMENT

2018· article· en· W2903661021 on OpenAlexaff
A. F Mandour, Mohamed Abdel Hamid, Samah Abdallah

Bibliographic record

VenueJournal of Environmental Science · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsForeign direct investmentPetroleumBusinessNatural resourceInvestment (military)Developing countryEconomic sectorPublic sectorAgency (philosophy)EconomicsEconomyEconomic growthMacroeconomics

Abstract

fetched live from OpenAlex

Countries all over the world are racing to attract as much foreign direct investment (FDI) as possible due to its crucial impact on the economic development projects in the hosting countries. If these countries could well choose their economic projects and foreign partners, FDI could fill up the gap of limited resources and possibilities, increase the investment base, and help making the best use of the available natural resources for the hosting countries. Furthermore, FDI is an effective tool to transfer and use new technologies, as well as create new jobs in the hosting countries. Petroleum sector is one of the most important investing sectors with its huge directed investment whether for searching, exploring or extracting processes. Moreover, petroleum has a significant impact on the environment, as it emits contaminated waste while being produced. Thus, extracting petrol is an expensive process and -in some cases- harmful to the environment. The current research aims to study the impact of FDI in petroleum sector on the environment and to study the advantages and disadvantages of FDI in petroleum sector. To achieve that, analytical method based on the extrapolation method was used through gathering and analyzing the required data. Data was collected from CAPMAS (Central Agency for Public Mobilization and Statistics) and reports of the Central Bank of Egypt during the period of 2008 and 2016. The collected data was statistically analyzed through “SPSS” software. Results show that FDI in petroleum sector has a significant impact on the environment due to the harmful emissions resulted from searching, exploring and extracting processes; protecting the environment leads to huge cost as petrol production has the highest portion of the total FDI comparing with other sectors. Furthermore, this cost increases as FDI increases in spite of the exerted efforts. Researchers recommend to do more efforts in the petroleum sector to reduce the pollution resulted from FDI, spend more money on researches and development processes as well as use modern technologies that reduce the emissions of petroleum sector production.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.209
Teacher spread0.189 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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