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Households · indicator 33

Domestic LPG customers / consumers

Modi ahead

Rahul India

59.29

synthetic 2023

Modi India

76.70

actual 2023

Difference

+29%

vs counterfactual

Placebo rank

4/36

p = 0.11

What this measures

Domestic LPG customers / consumers is the share of households cooking with gas or electricity rather than wood, dung or coal. A rising number is an improvement.

India stood at 42.40 in 2013, before the two paths separate. By 2023 Modi’s current India had risen to 76.70, while Rahul’s India — the blend of comparison countries that tracked India before 2014 — reached 59.29.

That leaves Modi’s current India 29% higher than Rahul’s India — better than where comparable economies ended up. Modi’s current India ranks 4/36 against placebo countries (p = 0.111) — within the range chance produces, so the gap is not distinguishable from noise.

Both paths, 1984–2023

Weights fitted on 2000-2013 only; the counterfactual is projected across 2014-2023.

Modi India · actualRahul India · syntheticModi ahead

Divergence

Modi India minus Rahul India, in % of population.

What Rahul’s India is made of

Donor weights, solved on pre-2014 data. 35 countries in the pool; those not listed carry zero weight.

  • Ethiopia
    25.7%
  • Vietnam
    23.8%
  • Myanmar
    20.3%
  • Morocco
    17.2%
  • Sri Lanka
    6.9%
  • Philippines
    5.7%

Method & reliability

Measure
clean_cook_pct
Source type
Cross-country proxy
Estimation window
2000-2013
Projection window
2014-2023
Donor pool
35 countries
Pre-2014 fit (RMSPE)
0.9% of pre-period mean
Placebo rank
4/36
Standardised p-value
0.111
BH-adjusted q across tier 1
0.317

The q-value applies a Benjamini–Hochberg correction across all 20 indicators with a counterfactual. We report p as the primary figure because each indicator is treated as a separate question rather than one family of hypotheses — but no result on this site survives q ≤ 0.10, and a reader who prefers the family view should read the p-values accordingly.

LPG customers -> access to clean cooking fuels

How this was calculated

Nothing here is chosen by hand. The comparison countries are not picked for being like India — they are whatever mix best reproduces India’s own path before 2014 on this particular measure.

  1. 1Describe India before 2014

    India's domestic lpg customers / consumers is summarised over 2000-2013 — the value at five evenly spaced years starting 2000, plus three background controls averaged across the whole window: GDP per capita, urbanisation and life expectancy.

  2. 2Find the blend that matches it

    Each of the 35 comparison countries is described the same way. An optimiser then searches for the weighted mix of them whose pre-2014 path sits closest to India's. Weights cannot be negative and must sum to 100%, so the result is always a real combination of real countries — never an extrapolation.

  3. 3Check the match is good enough

    The blend misses India's actual pre-2014 path by 0.9% on average. That is close enough to treat the projection as meaningful.

  4. 4Project it forward and compare

    The weights are frozen and applied to 2014-2023, years the optimiser never saw. That projection is Rahul's India. The difference against what actually happened is the gap shown above.

  5. 5Test it against the other countries

    The whole procedure is re-run pretending each comparison country was the one treated in 2014. India's break ranks 4/36 against those placebos, giving p = 0.111 — well within what chance produces, so this gap is not distinguishable from noise.

Why Ethiopia?

Ethiopia carries 26% of the weight here — not because it resembles India economically or politically, but because its domestic lpg customers / consumers moved like India’s did between 2000 and 2013. On 19 of the other 27 indicators on this site it carries no weight at all; where it does appear, the largest is neonatal mortality rate at 50%. The blend is re-solved from scratch for every indicator, which is why the same country can dominate one estimate and be absent from the next.

6 of 35 comparison countries carry any weight at all. The rest are assigned zero by the optimiser.

The counterfactual is 'India without the 2014 structural break', estimated from comparator countries. It is not a forecast of any individual's policies. Sources: World Bank WDI API (2026-07-13); IRENA via Our World in Data.