Insights

By education of head — mean MPCE

Report §3.2.13 · head = Relation_to_Head = 1.

Visualisation

Weighted P1–P99 (log scale). Dashed grey = P50 median. Hover moves crosshair.

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Data used

Exact rows behind the viz — full width.

—

Raw SQL — exactly as executed

DuckDB over Parquet · copy-paste runnable in duckdb.

SQL — DuckDB · Parquetcopy-paste runnable
-- Raw MPCE CTE  +  head education — level_02 §D10 (01–13)
SELECT  edu."Education_Level",
        hh.mpce, hh.mult
  FROM (raw MPCE CTE)  hh
  JOIN "level_02_section_3" edu
    ON hh.FSU = edu."FSU_Serial_No"
   AND hh.HHNo = edu."Sample_Household_No"
   AND edu."Relation_to_Head" = '1'  -- head only
TE=E1+(E2 / P2) × P1+(E3 / P3) × P1AppxB 3.5.2 pB11
MPCE=TE / P13.5.3· keep only HH where P1, P2, P3 all present (§2.2.0)
E1
Food — 7-day recall → × 30/7 to monthly — from level_05/06 (§1.5 Cat I)
E2
Consumables & Services — 30-day recall → × 1 — from level_08/09/10 (§1.5 Cat II)
E3
Durables — 365-day recall → × 30/365 — from level_12/13/14 (§1.5 Cat III)
P1 P2 P3
Household size at FDQ / CSQ / DGQ canvass — level_15 VISIT 1/2/3 → HOUSEHOLD_SIZE

wmean per Edu (01..13 §D10) = Σ(mpce×mult)/Σ(mult).

Processing & manipulations — full transparency

Every step after SQL. No hidden transforms.

WHAT WE DO — step by step

  1. 1 Python: left join on HH key, drop non-head rows, weighted mean with raw MULT.
  2. 2 No imputation, no calibration.

WHAT WE DO NOT DO — report does, we intentionally skip

  1. Weight calibration N/n × D1 × H/h → Census 2011 — AppxB pB13 4.0 & B9–B10. Source: censusindia.gov.in projected Sector×State×SSS.
  2. Free-item imputation (KDE) §2.3 p15–16 — modal Sector×State via Gaussian KDE, 061–075 + PDS 7 + durables 600–623. Would lift to Sec II 4247 / 7078.
  3. CPI deflation Table 3.3 note(ii) p25 — CPI(R)/CPI(U) to 2011-12. Source: mospi.gov.in / RBI DBIE.

Hence raw ~2793 / 5146 vs published 4122 / 6996 is documented, not hidden. No outlier trimming, no re-weight; filters only HOUSEHOLD_SIZE > 0, MPCE > 0 and P1 & P2 & P3 all present (§2.2.0 — incomplete visits dropped).

How to replicate the published figures — sources

Exact pinpoints in NSS Report 592 (HCES 2023-24). Raw + external inputs.

PinpointDefinesData source
§1.5 p4–5MMRP — 7d (Cat I) / 30d (Cat II) / 365d (Cat III) reference periodssurvey
§1.9 p6–7Home produce & gifts — ex-farm / retail valuationfield
§2.2 p13All 3 visits required — §2.2.0 drop if incompletesurvey
AppxB pB11TE = E1+(E2/P2)P1+(E3/P3)P1 & MPCE = TE/P1 — 3.5.2–3.5.3survey
AppxB pB134.0 Weight N/n × D1 × H/h then calibrated — gap to publishedcensusindia.gov.in
§2.3 p15–16KDE Gaussian modal price — free 061–075 + PDS 7survey + KDE
§3.2.5 p30Table 3.5 — food / non-food share breakdownderived
T3.3 p25note(ii) CPI(R)/CPI(U) → 2011-12 pricemospi.gov.in
Amber rows = external inputs not in Parquet — add them to go from raw ~2793/5146 to published 4122/6996 (Sec I) and 4247/7078 (Sec II).
The Household Consumption Expenditure Survey (HCES) for 2023-24 was conducted by the National Statistical Office (NSO) under the Ministry of Statistics and Programme Implementation (MoSPI), Government of India Survey weights normalized to national estimates for display