Technical Appendix

A1. Index Construction Methodology

General Principles

All indices follow a standardized construction methodology:

Index_t = Σ(w_i × normalize(X_it)) / Σw_i where: X_it = Raw value of component i at time t w_i = Weight assigned to component i normalize() = Min-max normalization to [0,1]

Normalization Formula

normalize(X) = (X - X_min) / (X_max - X_min) For reverse indicators: normalize_reverse(X) = 1 - normalize(X)

A2. Statistical Suppression Index (SSI) Details

Component Weights and Graded Severity

SSI is a 0-10 weighted sum of graded suppression severities: SSI_t = Σ(weight_i × severity_it), severity ∈ [0,1] (1.0 = full suppression / discontinuation, ~0.7 = methodology dispute, ~0.3 = delay or post-resolution scar). Six documented streams; weights sum to 10. The UPA years (2004-2013, shaded) record nothing, so SSI = 0. Both eras are computed identically in data/compute_indices.py. Cell values are the annual severity; published third-party data is not involved — these are author-coded severities anchored to datable events (see notes).

Year	Census (2.5)	Consumption (1.5)	Employment (1.0)	GDP back-series (1.5)	Institutional (1.5)	Mortality undercount (2.0)	SSI Score
2004	0	0	0	0	0	0	0.00
2005	0	0	0	0	0	0	0.00
2006	0	0	0	0	0	0	0.00
2007	0	0	0	0	0	0	0.00
2008	0	0	0	0	0	0	0.00
2009	0	0	0	0	0	0	0.00
2010	0	0	0	0	0	0	0.00
2011	0	0	0	0	0	0	0.00
2012	0	0	0	0	0	0	0.00
2013	0	0	0	0	0	0	0.00
2014	0	0	0	0	0	0	0.00
2015	0	0	0	.70	0	0	1.05
2016	0	0	0	.70	0	0	1.05
2017	0	0	1	.70	0	0	2.05
2018	0	1	1	1	0	0	4.00
2019	0	1	.30	1	1	0	4.80
2020	1	1	0	1	1	0	7.00
2021	1	1	0	1	1	1	9.00
2022	1	1	0	1	1	1	9.00
2023	1	1	0	1	1	.60	8.20
2024	1	.50	0	1	1	.40	7.05
2025	1	.30	0	1	1	.30	6.55
2026	1	.20	0	1	1	.30	6.40

Key Finding: SSI was 0 across the UPA decade, then climbed to a peak of 9.0 in 2021-2022 — the COVID-mortality undercount (official ~0.5M deaths vs 3-5M excess) stacking on top of the census delay, the withheld consumption survey, the shelved GDP back-series and the permanent NSSO→NSO merger. It remains elevated at 6.4 in 2026: the acute events eased, but the institutional damage (merger, unresolved back-series) is permanent and the data scars persist.

A3. Fiscal Centralisation Index (FCI) Components

Detailed Component Calculation

FCI_t = (1/6) × [C1_t + C2_t + C3_t + C4_t + C5_t + C6_t] Where: C1_t = minmax(Cess_Share_t) C2_t = 1 - minmax(Devolution_t) C3_t = 1 - minmax(States_Own_Revenue_t) C4_t = minmax(CSS_Share_t) C5_t = Borrowing_Restrictions_t ∈ {0, 0.5, 1} C6_t = GST_Centralisation_t ∈ [0,1] (0 pre-2017; full once GST compensation ended mid-2022)

Year	Cess/Surcharge %	Devolution %	States' Own Rev %	CSS Share %	Borrowing	GST	FCI Score
2004	6.5	36.5	45.0	22.0	0.0	0.00	0.00
2005	7.0	36.3	44.8	22.8	0.0	0.00	0.03
2006	7.5	36.1	44.5	23.5	0.0	0.00	0.05
2007	8.0	35.9	44.2	24.2	0.0	0.00	0.07
2008	8.5	35.8	44.0	24.8	0.0	0.00	0.09
2009	9.0	35.7	43.7	25.4	0.0	0.00	0.11
2010	9.3	35.6	43.4	26.0	0.0	0.00	0.12
2011	9.6	35.5	43.1	26.6	0.0	0.00	0.14
2012	9.9	35.4	42.9	27.2	0.0	0.00	0.16
2013	10.1	35.3	42.7	27.7	0.0	0.00	0.17
2014	10.4	35.0	42.5	28.3	0.0	0.00	0.19
2015	11.5	35.6	41.8	29.5	0.0	0.00	0.21
2016	13.5	36.2	40.2	31.2	0.0	0.00	0.25
2017	15.3	36.6	38.5	33.8	0.0	0.60	0.41
2018	17.8	35.5	37.2	36.5	0.0	0.70	0.53
2019	19.0	34.0	36.1	38.9	0.0	0.80	0.65
2020	20.2	33.0	34.5	42.3	1.0	0.85	0.92
2021	18.3	32.7	35.2	41.5	0.5	0.90	0.82
2022	16.3	32.4	36.8	40.2	0.0	1.00	0.70
2023	14.8	32.1	37.5	39.8	0.0	1.00	0.68
2024	14.8	31.8	37.9	39.5	0.0	1.00	0.68
2025	14.6	31.6	38.0	39.2	0.0	1.00	0.68
2026	14.5	31.4	38.1	39.0	0.0	1.00	0.68

Note: Six components, each min-max normalised over the full 2004-2026 sample, so FCI is relative: 0.00 = least-centralised year (2004), ~0.92 = most (2020). UPA average 0.09 vs 0.57 under NDA. The new GST component captures the structural loss of independent state taxation in 2017 (cesses and CSS are symptoms; GST is the regime shift), phasing to full weight once GST compensation ended in June 2022. NDA component values (2014-2024) are budget / Finance-Commission anchors; UPA values interpolate official anchors (12th-15th FC devolution; Receipt-Budget cess and CSS shares).

A4. Democratic Quality Index (DQI) Calculations

Four-Component Geometric Mean

DQI_t = (V_t × F_t × R_t × C_t)^(1/4) Where: V_t = V-Dem Liberal Democracy Index (0-1) F_t = Freedom House aggregate score / 100 R_t = (180 - RSF_rank_t) / 180 C_t = V-Dem Core Civil Society Index (0-1)

All four are published third-party measures. The Civil Society Index is added because press-freedom rank barely separates the eras (India was mediocre throughout), whereas civil-society space collapsed from 0.669 to 0.302 under NDA — the dimension a headline democracy score flattens. (V-Dem also reclassified India from electoral democracy to electoral autocracy in 2019.)

Year	V-Dem LDI	Freedom House	RSF Rank	Civil Society	DQI Score
2004	0.578	78/100	120/180	0.826	0.59
2005	0.573	78/100	106/180	0.760	0.61
2006	0.569	78/100	105/180	0.760	0.61
2007	0.569	78/100	120/180	0.760	0.58
2008	0.569	78/100	118/180	0.760	0.58
2009	0.539	79/100	105/180	0.760	0.61
2010	0.532	79/100	122/180	0.744	0.56
2011	0.532	79/100	131/180	0.744	0.54
2012	0.525	79/100	140/180	0.743	0.51
2013	0.522	78/100	140/180	0.735	0.51
2014	0.488	78/100	140/180	0.669	0.49
2015	0.417	77/100	136/180	0.576	0.46
2016	0.406	77/100	133/180	0.555	0.46
2017	0.371	77/100	136/180	0.523	0.44
2018	0.363	75/100	138/180	0.471	0.42
2019	0.324	71/100	140/180	0.454	0.39
2020	0.292	67/100	142/180	0.404	0.36
2021	0.307	66/100	142/180	0.421	0.37
2022	0.291	66/100	150/180	0.421	0.34
2023	0.273	66/100	161/180	0.346	0.28
2024	0.281	66/100	159/180	0.302	0.28
2025	0.260	66/100	151/180	0.302	0.30
2026	0.260	66/100	157/180	0.302	0.29

Key Finding: DQI fell from a UPA-era average of 0.57 (peak 0.61) to 0.29 by 2026, and from 0.49 in 2014 — with the steepest drop after 2019, the year V-Dem reclassified India as an electoral autocracy. The geometric mean is now pulled hardest by the collapse in civil-society space (0.669 → 0.302), not just press freedom.

Correction, 15 August 2026. The two V-Dem columns above previously held approximated values whose pre-2014 entries were too high (Liberal Democracy Index 0.555 for 2014 against a published 0.488; Core Civil Society Index 0.87 against a published 0.669). That inflated the baseline and therefore exaggerated the measured decline — an error running in this project’s own favour. Both columns are now the published V-Dem series verbatim (v2x_libdem and v2xcs_ccsi). The UPA-decade mean falls from 0.59 to 0.57 and the 2014 value from 0.54 to 0.49; the 2026 value is unchanged at 0.29.

A4b. Unpaid Household Work: Time Use Survey Data

National accounts place own-account household services outside the production boundary, so none of the GDP figures in this appendix include them. The hours are nonetheless measured. Source: NSO Time Use Survey, January–December 2019 and January–December 2024; the later round covered about 4.5 lakh persons in 1.3 lakh households. Ages 15–59. Minutes are the daily average among participants, not across the whole population.

Indicator	Women 2019	Women 2024	Men 2019	Men 2024
Unpaid domestic services, minutes/day	299	289	97	88
Participation in unpaid domestic services, %	81.2	83.9	26.1	45.8
Participation in employment, %	21.8	25	70.9	75
Caregiving, minutes/day (2024)	—	140	—	74
Caregiving participation, % (2024)	—	41	—	21.4

Derived result: the participant gap in unpaid domestic services was 299 − 97 = 202 minutes in 2019 and 289 − 88 = 201 minutes in 2024. Male participation rose from 26.1% to 45.8% over the same period while minutes among participants fell for both sexes, so the gap closed by 1 minute in five years. Female employment participation rose 21.8% → 25%.

A4b.1 Published valuations

Estimates of what this work would be worth, as a share of GDP. The spread reflects valuation method, not uncertainty in the hours. This project publishes the range and adopts none of them; no GDP figure anywhere in this assessment is adjusted.

Estimate	Method	% of GDP
SBI Ecowrap (2023)	minimum-wage valuation	7.5%
Ministry of Women and Child Development (2024 submission)	not fully specified	15–17%
Generalised opportunity cost, 2019-20	opportunity cost	24.6%
Economic and Political Weekly (2024), 2022-23	replacement and opportunity cost	26–36%
Replacement cost method, 2019-20	replacement cost	32.4%

Bearing on the employment series: female labour force participation of ~21% in the main tables is customarily read as an absence of work, while the Time Use Survey records 83.9% of women aged 15–59 in unpaid domestic work on the reference day. The participation figure measures the absence of work the accounts recognise. How much of the gap is behavioural rather than definitional is unresolved here.

A5. Employment Elasticity Estimation

Methodology

Employment Elasticity = (%ΔEmployment) / (%ΔGDP) Log-linear specification: ln(E_t) = α + β×ln(Y_t) + γ×X_t + ε_t Where: E_t = Employment at time t Y_t = Real GDP at time t X_t = Control variables β = Employment elasticity

Period	GDP Growth %	Employment Growth %	Elasticity	95% CI	R²
2004-2009	8.4	0.8	0.10	[0.08, 0.12]	0.72
2009-2011	8.5	0.4	0.05	[0.02, 0.08]	0.65
2011-2016	6.7	0.1	0.01	[-0.02, 0.04]	0.58
2016-2020	5.2	-1.2	-0.23	[-0.28, -0.18]	0.81
2020-2023	7.8	8.6	1.11	[0.95, 1.27]	0.69

Note: The 2020-2023 elasticity of 1.11 reflects distress employment in informal sector post-pandemic, not quality job creation.

A6. Inequality Measurement Methods

Income Share Calculation

Top 1% Share = Σ(Y_i) / Y_total for i ∈ top percentile Gini Coefficient = (1/2n²μ) × ΣΣ|y_i - y_j| Palma Ratio = Income share of top 10% / Income share of bottom 40%

Year	Top 1%	Top 10%	Middle 40%	Bottom 50%	Gini	Palma
2014	15.0%	52.9%	32.1%	15.0%	0.812	3.5
2015	16.2%	54.1%	31.5%	14.4%	0.821	3.8
2016	17.5%	55.3%	30.9%	13.8%	0.830	4.0
2017	18.9%	56.4%	30.3%	13.3%	0.838	4.2
2018	19.8%	57.1%	29.9%	13.0%	0.843	4.4
2019	20.6%	57.8%	29.5%	12.7%	0.847	4.6
2020	21.0%	58.2%	29.3%	12.5%	0.850	4.7
2021	21.7%	58.9%	28.9%	12.2%	0.854	4.8
2022	22.2%	59.4%	28.6%	12.0%	0.857	5.0
2023	22.6%	59.8%	28.4%	11.8%	0.860	5.1

A7. Robustness Tests

Sensitivity Analysis Results

Test	Base Result	Alternative Specification	Difference	Significant?
SSI with ±20% weights	7.05 (2024)	5.6-8.5	±20%	No
FCI excluding borrowing	0.68 (2024)	0.81	+19%	No
DQI arithmetic mean	0.29 (2024)	0.34	+17%	Yes*
Employment elasticity (quarterly)	0.01	0.03	+200%	No
Inequality (CMIE vs WID)	22.6%	21.8%	-3.5%	No

*Note: Geometric mean penalizes weak dimensions more heavily, making DQI more sensitive to democratic erosion.

A8. Complete Results Tables

Master Results Table 2014-2024

Year	GDP Growth	Unemployment	Top 1%	SSI	FCI	DQI	Press Rank	Devolution
2014	7.4%	4.9%	21.3%	0.00	0.19	0.54	140	35.0%
2015	8.0%	5.0%	21.7%	1.05	0.21	0.54	136	35.6%
2016	8.2%	5.0%	21.5%	1.05	0.25	0.53	133	36.2%
2017	7.2%	6.0%	21.5%	2.05	0.41	0.50	136	36.6%
2018	6.1%	6.1%	21.7%	4.00	0.53	0.46	138	35.5%
2019	4.2%	5.8%	22.1%	4.80	0.65	0.43	140	34.0%
2020	-7.3%	7.1%	22.3%	7.00	0.92	0.40	142	33.0%
2021	8.7%	4.2%	22.5%	9.00	0.82	0.38	142	32.7%
2022	7.2%	4.1%	22.6%	9.00	0.70	0.33	150	32.4%
2023	7.6%	3.2%	22.6%	8.20	0.68	0.28	161	32.1%
2024	7.8%	3.2%	22.6%	7.05	0.68	0.29	159	31.8%

Summary Statistics

GDP Growth (2014–2026): Mean = 6.08%, SD = 4.01%
Unemployment: Mean = 5.4%, SD = 0.78%
Top 1% Share: 21.3% (2014) → 22.6% (2023), +1.3pp; the level is the highest recorded since 1922. Bottom 50% Share: 15.0% → 13.1%, −1.9pp (a 12.7% relative decline)
SSI: 0 across UPA; peaked 9.0 (2021-22, COVID undercount); sustained 6.4 (2026)
FCI: rose from 0.19 (2014) to 0.68 (2024); peak 0.92 (2020); UPA avg 0.09 (incl. GST component)
DQI: fell from 0.49 (2014) to 0.29 (2026); UPA avg 0.57 (incl. civil-society index)
Press Freedom: Fell 21 ranks (140 → 161)
Devolution: Decreased 9.3% (35% → 31.8%)

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