Heterogeneity in Food Demand among Rural Indian Households: The Role of Demographics
Bibliographic record
Abstract
Food expenditures, influenced by social, demographic, and economic factors, constitute a significant proportion of the typical rural Indian's household income. Based on cross‐sectional household data, this study employs the Quadratic Almost Ideal Demand System to estimate food demand among rural Indian households. Special attention is given to the rural household's two‐stage budgeting in total food expenditure and then to a demand for a specific food item. Conditional and unconditional expenditure and price elasticities for seven food groups are estimated. Results indicate that own‐price elasticities for each group are negative ranging from fairly inelastic to elastic range. Expenditure elasticities indicate that food items are a normal necessity to luxury goods. Additionally, socio‐demographic factors play a significant role in food consumption patterns. Based on our unconditional expenditure elasticities, we also project food demand from rural Indian households for next two decades. Les dépenses alimentaires, qui sont influencées par des facteurs socioéconomiques et démographiques, absorbent une partie considérable du revenu des ménages ruraux typiques en Inde. Dans la présente étude, nous avons utilisé le modèle de demande quasi idéal quadratique pour estimer, à l'aide de données transversales sur les ménages, la demande alimentaire des ménages ruraux en Inde. Nous avons accordé une attention spéciale à la budgétisation en deux étapes des dépenses alimentaires totales et à la demande d'un produit alimentaire particulier du ménage rural. Nous avons estimé les dépenses conditionnelles et inconditionnelles et l’élasticité‐prix de sept groupes alimentaires. Les résultats de notre étude indiquent que l’élasticité‐prix de chaque groupe est négative et qu'elle varie de plutôt inélastique à divers degrés d’élasticité. L’élasticité des dépenses indique que les produits alimentaires varient de nécessités de base à produits de luxe. Les facteurs sociodémographiques jouent également un rôle important dans les habitudes de consommation alimentaire. D'après les élasticités des dépenses établies dans notre étude, nous avons estimé la demande alimentaire des ménages ruraux en Inde pour les deux prochaines décennies.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".