LNG exports from the US—what role will the new Administration play?
Bibliographic record
Abstract
The LNG industry today is uncertain and looking for a new business model. Even willing buyers and sellers find it hard to agree a long-term sales and purchase construct that is durable and unlikely to embarrass in the future. The reasons are clear: the world is likely to be more long than short LNG for a few years and the spot price of LNG has swung wildly between a steep discount and significant premium to long-term, oil indexed prices. HH-indexed LNG volumes have only just begun to flow and yet in the future, for several reasons, this new price construct could send the wrong price signals to the global market at a time when oil prices remain low, a condition it is hard to see changing. Coupled with this, the migration to an increasingly liquid and spot LNG market discourages new investment and at the same time hobbles potential new investment with a greater financing challenge. Doing nothing has become the ultimate defensive move but should not be mistaken for a strategy. As we look to the new supplies, we should separate the signal from the noise. Indisputably, the third wave (post-2021) of US projects will provide the cheapest unit construction costs for contemporary global greenfield LNG and will do so backed by trillions of cubic feet of cheap US shale gas. These will combine to provide long-term, low priced LNG with far lower expected volatility for the global markets. This will happen against the backdrop of a new US administration under the leadership of a President with a doctrine of putting America more firmly on the global stage. The question is, will the early, somewhat contradictory messages from the White House, which on the positive side include the identification of priority projects, a drive toward reduced bureaucracy and balancing the trade deficit with international trade partners and on the negative side call for greater local content and border taxes, lead to a better environment for US projects? My comments will address these contradictions, but with the firm intention to leave no doubt that the new US administration is open for business and that we see a return to firm, yet sensible regulation as a major positive for our fast-growing US LNG industry.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".