Demand Analysis of Non-Alcoholic Beverages in Japan
Bibliographic record
Abstract
This paper estimates the demand of non-alcoholic beverages in Japanese household using the linear approximation quadratic almost ideal demand system model (LA/QUAIDS). Eight expenditure shares and prices demand equations for non-alcoholic beverage group: green tea, black tea, tea beverage, coffee, coffee beverage, fruit and vegetable juice, carbonated beverage and milk are estimated for two or more households in forty-nine cities for the period January 2000 through March 2013. The expenditure elasticity results indicate that green tea (2.320), black tea (1.357), coffee (1.090) and fruit and vegetable juice (1.019) are luxury goods while tea beverage (0.836), coffee beverage (0.896), carbonated beverage (0.844) and milk (0.677) are necessities in the Japanese household. The demographic effects reveal that people under the age of 18 prefer milk (5.928) than any other beverages whereas elderly people tend to drink more green tea (24.427). Moreover, temperature effects shows it has mostly positive effect on demand for tea beverage, coffee beverage, fruit and vegetable juice, and carbonated beverage and negative effect on green tea, black tea, and coffee in most of the months.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".