Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Associations and Statistical Inferences to the Productive Environment of the Oil Market: Analysis of the World’s Largest Producers from 1993 to 2020

Version 1 : Received: 27 September 2022 / Approved: 28 September 2022 / Online: 28 September 2022 (15:35:31 CEST)

How to cite: Ferreira, R.H.M.; Rubbo, P.; Picinin, C.T. Associations and Statistical Inferences to the Productive Environment of the Oil Market: Analysis of the World’s Largest Producers from 1993 to 2020. Preprints 2022, 2022090446. https://doi.org/10.20944/preprints202209.0446.v1 Ferreira, R.H.M.; Rubbo, P.; Picinin, C.T. Associations and Statistical Inferences to the Productive Environment of the Oil Market: Analysis of the World’s Largest Producers from 1993 to 2020. Preprints 2022, 2022090446. https://doi.org/10.20944/preprints202209.0446.v1

Abstract

The energy matrix worldwide has been going through difficulties in its discussions - such as irregular exploration, inefficient public policies, and arbitrariness concerning diplomatic and political definitions of those involved in this market. This work's general objective consists in analyzing associations and statistical inferences of the largest world oil producers, assimilating the contributions and singularities of this market from 1993 to 2020. Based on the Organization of the Petroleum Exporting Countries (OPEC), it was possible to identify the possible inferences and contributions of the ten largest oil producers in the world in more than two decades using statistical analysis through correlation, regression, and statistical analysis of variables. According to the research and the literature on the area, the oil market proposes support to its discussions, mainly in its productive approaches. It is possible to identify this market as a solid link to geopolitical actions, distributing the possibilities through economic bias and socio-cultural and historical factors on a global level.

Keywords

petroleum; oil market; oil; statistics

Subject

Business, Economics and Management, Econometrics and Statistics

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