Employing the Panel Quantile Regression Approach to Examine the Role of Natural Resources in Achieving Environmental Sustainability: Does Globalization Create Some Difference?
Why this work is in the frame
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Bibliographic record
Abstract
In the modern era of globalization, natural resources have become an important factor in shaping a sustainable future; however, the evidence on the role of globalization in reducing the adverse environmental impacts of natural resources is relatively scarce. The current study explores the dynamic interaction between energy consumption, economic development proxied through the human development index, population, natural resources, globalization, and ecological footprint under the core idea of the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT). This research applies panel data for the period from 1999 to 2018 in nine countries with the highest oil production (Brazil, Canada, China, Iran, Kuwait, Russia, Saudi Arabia, United Arab Emirates, and the United States). The results of this study are based on the panel Method of Moments Quantile Regression (MMQR). Empirical findings foundthat economic development, energy consumption, population, and natural resources contribute to increased environmental degradation, while globalization seems the main source of environmental sustainability. Concerning the indirect impacts of globalization, expanded interaction and integration among oil-producing countries helped to inhibit ecological footprint; nevertheless, natural resources complicate the design of a sustainable future by promoting environmental degradation. Additionally, a bidirectional causality relation was discovered between population, energy consumption, globalization, and ecological footprint; however, the panel Dumitrescu and Hurlin causality test results revealed a unidirectional causality association from economic development to ecological footprint and from natural resources to ecological footprint. Our findings shed new light on the criticality of globalization in achieving environmental sustainability by providing cleaner practices that will prevent rent-seeking.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it