Elite Capture : Residential Tariff Subsidies in India
Why this work is in the frame
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Bibliographic record
Abstract
India - home to one of the world's largest populations without electricity access - has set the ambitious goal of achieving universal electrification by 2017. 311 million people, a quarter of its population, remains without power, despite substantial efforts to increased affordable access for the poor. This study focuses on India's residential electricity subsidies, as viewed through a poverty lens. Addressing these issues is especially urgent since the residential electricity sector accounts for nearly a quarter of India's total electricity consumption. Comparison of two survey rounds (2004/05 and 2009/10) was used to assess changes in electricity consumption over time. The study approach analyzed subsidy distribution by both below poverty line (BPL) and above poverty line (APL) grouping, as well as income quintile, to allow for the wide variation in poverty rates states. The key findings in this study are that 87 percent of subsidy payments go to APL households instead of to the poor, and over half of subsidy payments are directed to the richest two-fifths of households. Furthermore, these estimates are conservative because they assume that BPL and APL households are accurately identified. Because APL households tend to consume more electricity, subsidies are skewed toward the upper quintiles. The major driver of these outcomes is tariff design. Few states have highly concessional BPL tariffs; in most, all households are eligible for a subsidy on at least a portion of their monthly electricity consumption. Combined with the fact that the poorest households consume relatively small amounts of electricity means that wealthier consumers with electricity access are typically eligible for just as much, if not more, subsidy as poorer ones. India's states have a variety of available options for improving their subsidy performance. Certain states model good practices that other states could consider adopting, for example, Punjab, Sikkim, Chattisgarh, and others. States may consider four model tariff structures that meet the twin, medium-term policy goals of high subsidy targeting and low cost. These are (i) creating BPL tariff schedules and eliminating subsidies from other schedules, (ii) delivering subsidies through cash transfers instead of tariffs, (iii) creating a volume differentiated tariff (VDT), and (iv) creating a lifeline tariff and removing subsidies from other tariffs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 it