The Effect of Regulation on the Development of Natural Gas Value Chain in Nigeria
Bibliographic record
Abstract
Abstract Natural and Energy resources are synonymous. They are very important to the nation's economy and industrial growth. Therefore, Government always has control through regulations over natural resources in any nation. Regulations can sometimes have negative impact on the development of natural resources and create artificial scarcity to the detriment of economic and industrial growth, and the welfare of the citizens. Over-regulated market has been known not to be conducive for competitive market and may even create price hike, which can be destructive to innovation and create unattractive business environment to both foreign and local investors. Nigeria's Niger Delta has been described as gas rich zone. Up to date, the same gas has been poorly developed compared with oil. Apart from the liquefied natural gas project, the gas value chain in Nigeria has been poorly developed. This paper examines the historical gas development trend and evaluates the impact of regulation on the natural gas value chain in Nigeria. The historical impact of regulation on the United States of America's natural gas value chain development is also studied as a standard so as to underpin, by way of comparison, the reasons for the poor development of the natural gas value chain in Nigeria. As a link to utility, natural gas is used for heating and cooking at homes, and providing electricity in the United States of America and other developed countries. It is also linked to some industrial sectors such as fertilizer, petrochemical, and refinery. Because of its utility structure, natural gas is regulated at some nodes along the value chain to accommodate, not by subsidizing, the financial capability of all citizens in purchasing such utility products. When natural gas is fully developed along its value chain for national development, the consequences are vibrant and stable economy coupled with industrial growth. Therefore, the purpose of this paper is to examine the natural gas market in Nigeria and compare it with United States' market which is a standard market that Nigeria can use as a blue print to follow.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".