Economies of Scale in the South Korean Natural Gas Industry
Bibliographic record
Abstract
The South Korean natural gas (NG) import volume in 2017 was 33.7 million tonnes per annum (13.1%), making it the second-largest NG-importing country in the world after Japan. Nevertheless, the NG wholesale market in South Korea has remained monopolistic since the Korea Gas Corporation (KOGAS) was established in 1983. Thus, the purpose of this study is to determine whether the NG wholesale market in South Korea has economies of scale by estimating the translog cost function and estimating the minimum efficient scale (MES) using robust linear regression. We used quarterly business reports of KOGAS from the first quarter of 2000 to the second quarter of 2018 to construct the data. The results showed that diseconomies of scale existed in all the years in the first and fourth quarters, and the second quarter showed the same result during 2010–2014. From 2011, the production quantity of all the quarters has exceeded the MES (5.81 million tons). The reason for these results is that the demand for NG power generation and city gas has surged since 2000, while the monopolistic structure of the past has been maintained. This study implies that it would be more efficient to allocate some of KOGAS’s additional import volume to the existing private NG companies and mitigate the regulation on resale.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".