I've wanted to write this for a while. Every political debate about India's two decades collapses into anecdote, WhatsApp forwards, and selective statistics. Both sides cherry-pick. Neither is wrong about their chosen numbers. Both are hiding inconvenient ones.
So I decided to do the boring, unflattering version: compile 120+ data points across eleven categories, note the source for each, and let the numbers speak. Where one era was clearly stronger, I say so. Where data is disputed between government and independent sources, I show both. For metrics where % growth is misleading due to a low starting base, I compare absolute values and note it in the comments.
The two periods are made equal: 2003–2014 (11 years) corresponds to the UPA government under Prime Minister Manmohan Singh (who took office in May 2004; I use 2003 as the baseline year). 2014–2025 (11 years) corresponds to the NDA government under Prime Minister Narendra Modi. Anchor points: 2003 → 2014 → 2025. Both eras faced global shocks — UPA dealt with the 2008 GFC, NDA with COVID-19 in 2020. I note this where relevant and include a full G7 baseline comparison at the end.
This is not a verdict on which government was "better." That involves values, priorities, and trade-offs that numbers alone cannot resolve. This is a map of what changed, by how much, and in which direction.
How to read this:
- P1 Change = change from 2003 to 2014 (UPA era, 11 years). P2 Change = change from 2014 to 2025 (NDA era, 11 years).
- Sources linked inline; government and independent sources both cited where they differ.
- Where 2025 data is unavailable, latest actual year is shown and projection (if any) is clearly marked.
- All INR figures are nominal unless stated otherwise.
Verdict decision rules (applied consistently):
- NDA Stronger — NDA era delivered meaningfully better improvement OR avoided a UPA-era decline.
- UPA Stronger — UPA era delivered meaningfully better improvement OR the metric worsened under NDA. (Includes ex-"Declined" cases.)
- Mixed — assigned when ANY of the following apply:
- Data unavailable / projected — 2025 number is missing, significantly stale, or a long-horizon projection from earlier actual data.
- Base effect — the headline %-advantage of one era is mechanically driven by a smaller starting base AND the absolute change in both eras is similar (within ~1.5× of each other). When the absolute change in one era is 1.5× or more than the other, that era wins regardless of which era's % is higher.
- Ceiling / saturation hit — the metric approached a natural cap (population coverage, biological floor for fertility, full sanitation, etc.) constraining one era's growth.
- Similar magnitudes — both eras improved (or both declined) by roughly comparable absolute or pp changes (gap within ~20%).
- Methodology / measurement changed — the metric's denominator (country pool, survey methodology, classification) changed across years, making cross-era comparison non-comparable.
- External shock asymmetry — one era absorbed a shock the other didn't, and the gap is within shock-adjusted noise (e.g. COVID for P2, GFC for P1).
NDA Stronger — NDA era had better absolute or rate-of-change improvement
UPA Stronger — UPA era had better absolute or rate-of-change improvement (includes metrics that worsened under NDA)
Mixed — both eras moved the metric in the same direction and the apparent gap is meaningfully driven by base effects, saturation/ceilings, or external context (not policy quality)
Summary Scorecard
Verdicts across 153 data points (12 categories, equal 11-year windows, 2003–14 UPA vs 2014–25 NDA). Based on absolute improvement with explicit base-effect / saturation / data-availability adjustments. The full per-category breakdown follows below.
88
NDA Stronger
(NDA era led)
(NDA era led)
25
UPA Stronger
(UPA era led, incl. metrics that worsened under NDA)
(UPA era led, incl. metrics that worsened under NDA)
40
Mixed
(base effects / saturation / data unavailable / both same direction)
(base effects / saturation / data unavailable / both same direction)
A. Macroeconomics
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 1 | Nominal GDP (USD billion) | $618B | $2,039B | $4,270B | +230% (+$1,421B) | +109% (+$2,231B) | NDA Stronger | P1 % is higher due to the lower base ($618B). But in absolute dollars added, P2 added $2,231B vs P1's $1,421B — 57% more. Growing a $2T economy to $4.3T is a harder feat than $618B to $2T. Base effect favours P1 on %; absolute value favours P2. World Bank / IMF WEO Apr 2025 |
| 2 | GDP PPP (USD billion, current intl $) | $2,020B | $7,100B | $16,600B | +251% (+$5,080B) | +134% (+$9,500B) | NDA Stronger | P2 added $9,500B in PPP wealth vs P1's $5,080B — nearly double in absolute terms. India passed Japan and Germany on PPP during P2. Base effect: P1 had higher % from a lower base ($2T); absolute tells a different story. IMF WEO Apr 2025 |
| 3 | Average Annual GDP Growth Rate (%) | — | — | — | 7.9% avg (11 yrs) | 5.9% avg (11 yrs) | Mixed | Verdict revised to Mixed on base-effect grounds. Headline P1 7.9% vs P2 5.9% (incl. COVID) or P2 ~7.1% (ex-COVID FY21). The base sizes are not comparable: growing a $618B economy at 7.9% (P1) is mechanically easier than growing a $2T economy at 7%+ (P2 ex-COVID). P1 also rode global EM tailwinds (commodity supercycle, pre-GFC capital abundance); P2 absorbed three distinct shocks (demonetisation, GST transition, COVID). Ex-COVID the gap is only ~0.8pp — within the noise of any cross-period growth-rate comparison. A clean "X stronger" verdict on growth rate alone over-reads the data; absolute output added is captured in metrics #1 and #2. World Bank / MoSPI |
| 4 | Per Capita GDP — Nominal (USD) | $556 | $1,576 | $2,940 | +183% (+$1,020) | +87% (+$1,364) | NDA Stronger | P1 % is higher due to base effect ($556 start). But P2 added more absolute dollars ($1,364 vs $1,020) from a harder base. Growing per capita from $556→$1,576 benefits from low-base tailwinds; $1,576→$2,940 requires real productivity gains at scale (1.4B population). P2 wins on absolute and difficulty-adjusted basis. World Bank |
| 5 | Per Capita GDP — PPP (intl $) | $2,000 | $5,450 | $11,000 | +173% (+$3,450) | +102% (+$5,550) | NDA Stronger | P2 added $5,550 in PPP per capita vs P1's $3,450 — 61% more in absolute terms. Same base-effect logic: % looks better in P1 because it starts from $2,000. What actually improved living standards faster is the absolute gain. IMF WEO Apr 2025 |
| 6 | Global GDP Rank (nominal) | 13th | 10th | 5th | +3 ranks | +5 ranks | NDA Stronger | Passed France (2019), UK (2022). On track to pass Japan by ~2030. IMF |
| 7 | CPI Inflation — Annual Average (%) | ~3.8% | ~10.0% | ~4.8% | +6.2pp (worse) | −5.2pp (better) | NDA Stronger | UPA era saw double-digit inflation (2009–14 avg ~9.5%). NDA period averaged ~5.5%, with RBI inflation targeting framework adopted 2016. RBI / World Bank |
| 8 | Foreign Exchange Reserves (USD billion) | $99B | $304B | $640B | +207% (+$205B) | +110% (+$336B) | NDA Stronger | P2 added more absolute reserves ($336B vs $205B) from a much harder base. India is now 4th largest Forex holder globally. Peak hit $704B in Sept 2024. Base effect: P1 had higher % from $99B start. RBI Weekly Statistical Supplement |
| 9 | FDI Inflows — Annual (USD billion) | $4.7B | $34.6B | $55B | +636% (+$30B) | +59% (+$20B) | UPA Stronger | Both on % and absolute terms, P1 wins — FDI added $30B in P1 vs $20B in P2. FDI has been declining from a peak of $85B (FY22) to ~$55B (FY25 est.), a concerning trend. P1 created India's FDI credibility. DPIIT |
| 10 | Merchandise Exports (USD billion) | $63B | $317B | $450B | +403% (+$254B) | +42% (+$133B) | UPA Stronger | P1 wins on both % and absolute — added $254B vs P2's $133B. Merchandise growth stalled post-2014 due to global trade slowdown and China competition. FY25 target: $500B not met. DGFT |
| 11 | Services Exports (USD billion) | $38B | $155B | $380B | +308% (+$117B) | +145% (+$225B) | NDA Stronger | P2 added $225B in absolute services exports vs P1's $117B — nearly double. GCC (Global Capability Center) boom drove P2 growth — India now hosts 1,700+ GCCs. Base effect: P1 had higher % from $38B. NASSCOM / RBI |
| 12 | Central Fiscal Deficit (% of GDP) | 4.1% | 4.5% | 5.6% | Widened 0.4pp | Widened 1.1pp | UPA Stronger | UPA failed to consolidate; NDA fared worse on this metric. COVID FY21 spike (9.2%) distorts; pre-COVID FY20 was 3.5% (best in decades). Target: 4.5% by FY26. MoF Union Budget |
| 13 | Tax-to-GDP Ratio (%) | 9.2% | 10.1% | 12.0% | +0.9pp | +1.9pp | NDA Stronger | GST implementation (2017), expanded tax base, UPI trails helping formalization. MoF |
| 14 | Direct Tax Collections (INR lakh crore) | ₹0.37L cr | ₹2.97L cr | ₹22.5L cr | +703% (+₹2.6L cr) | +658% (+₹19.5L cr) | NDA Stronger | P2 added ₹19.5L cr in absolute direct tax revenue vs P1's ₹2.6L cr — 7.5× more in absolute terms. Base effect explains why P1's % is slightly higher despite adding far less money; it does not explain away an absolute gap of this magnitude. ITR filers grew from ~30M (2003) to ~90M (2025). GST + UPI trails + faceless assessment + PAN-Aadhaar linking drove structural formalization. Cross-validates with Tax-to-GDP (#13, #16). CBDT Annual Reports |
| 15 | BSE Sensex (year-end, index level) | 5,839 | 27,499 | ~79,000 | +371% (+21,660 pts) | +187% (+51,501 pts) | Mixed | Verdict revised to Mixed on base-effect grounds. Stock indices compound multiplicatively — absolute pts gained mechanically scales with starting base. P1 had higher %-return (371% vs 187%) from a smaller base; P2 had higher absolute pts gained from a much larger base. Neither comparison cleanly attributes to policy quality — equity returns reflect global liquidity, earnings cycles, and FII flows as much as domestic policy. The genuine structural story under P2 (SIP inflows, retail participation deepening, demat account growth) is real and is captured better by the IT/Software (#45), Services Exports (#11), and Unicorn (#46) metrics. BSE India |
| 16 | Tax-to-GDP Ratio (centre + state, %) | ~9.8% | ~10.4% | ~11.7% (FY24) | +0.6pp | +1.3pp | NDA Stronger | Verdict based on absolute pp added: P2 +1.3pp vs P1 +0.6pp. GST (2017) consolidated indirect taxes, widened the base. Direct tax formalization via PAN-Aadhaar linking, faceless assessments. Higher tax-to-GDP reflects deeper economic formalization. India still below emerging-market peers (~14–16% avg). Union Budget / NIPFP |
| 17 | Current Account Balance (% of GDP) | −0.1% | −1.7% | −1.1% (FY24) | −1.6pp (worsened) | +0.6pp (improved) | NDA Stronger | Verdict based on absolute change: P1 worsened deficit by 1.6pp of GDP; P2 improved by 0.6pp. India hit a CAD crisis in 2013 (rupee fell 15–20% in months). NDA maintained steadier external balance through commodity cycle. Note: both eras ran a deficit — the direction of change decides verdict. RBI Balance of Payments Data |
| 18 | External Debt (% of GDP) | ~21.1% | ~23.5% | ~19.0% (2024) | +2.4pp (worsened) | −4.5pp (improved) | NDA Stronger | Verdict based on absolute pp change: P1 increased external vulnerability by 2.4pp; P2 reduced it by 4.5pp. Lower external debt/GDP = less exposure to currency/global rate shocks. P2 benefitted from higher nominal GDP growth reducing the ratio, plus disciplined ECB policy. RBI India's External Debt |
A. Macroeconomics — Section Score (18 metrics)
13
NDA ↑
3
UPA ↑
2
Mixed
B. Roads & Transport Infrastructure
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 16 | National Highways — Total Length (km) | 65,569 | 91,287 | 1,45,155 | +39% (+25,718 km) | +59% (+53,868 km) | Mixed | Verdict revised to Mixed on methodology-change grounds. 2015 NH reclassification added ~28,000 km of former state highways to the NH network on paper. Adjusted for the reclassification: P2 organic new-build ≈ 26,000 km vs P1's 25,718 km — functionally tied. Real construction acceleration shows up cleanly in row #17 (NH Construction Rate km/day), where NDA wins decisively without measurement artefacts. NHAI / MoRTH |
| 17 | NH Construction Rate (km/day avg) | ~7 | ~10 | ~33 | +43% | +230% | NDA Stronger | Peak: 37 km/day in FY22. This is actual construction, not reclassification. A genuine acceleration with no base-effect caveat. NHAI Annual Reports |
| 18 | 4-Lane+ Highways (km) | ~8,500 | 18,371 | 44,654 | +116% | +143% | NDA Stronger | NHAI |
| 19 | Expressways (km, operational) | ~185 | ~1,208 | ~4,500 | +553% (+1,023 km) | +273% (+3,292 km) | NDA Stronger | P1 % is misleading — it started near zero. What matters is absolute km built: P2 added 3,292 km vs P1's 1,023 km — over 3x more. Expressway network built in P2 include Purvanchal, Delhi-Mumbai, Agra-Lucknow, Yamuna, Bundelkhand. Clear P2 win. NHAI |
| 20 | PMGSY Rural Roads — Cumulative km Built | ~1.8L km | ~4.3L km | ~8.0L km | +139% (+2.5L km) | +86% (+3.7L km) | NDA Stronger | P2 built 3.7 lakh km vs P1's 2.5 lakh km — 1.5× more in absolute terms, on harder last-mile habitations (the remaining unconnected villages by 2014 were the structurally hardest). UPA launched PMGSY and deserves credit for the framework; NDA delivered the larger physical buildout. PMGSY Portal / MoRD |
| 21 | % Eligible Habitations Connected (Rural) | ~37% | ~70% | ~99% | +33pp | +29pp | NDA Stronger | Pp gain looks similar (33 vs 29) but the last 30% of habitations are the hardest — remote, hilly, tribal areas. Connecting 37%→70% is structurally easier than 70%→99%. P2 completed what P1 could not. PMGSY |
| 22 | Railway Route km (total) | 63,465 | 65,808 | 68,043 | +3.7% | +3.4% | Mixed | New route additions have been slow in both eras (~2–3% per decade). Focus has shifted to capacity/electrification over new lines. Indian Railways Annual Stat Summary |
| 23 | Railway Electrification (km of BG routes) | ~16,000 | ~22,224 | ~61,500 | +39% | +177% | NDA Stronger | Mission 100% electrification declared 2017; 90%+ achieved by 2024. Saves ~₹14,000 crore/yr in diesel costs. Ministry of Railways |
| 24 | Vande Bharat Trains (semi-HSR, 160 km/h) | 0 | 0 | 100+ | — | New fleet | NDA Stronger | Designed and manufactured in India. First run: Feb 2019. 130+ trains operational by 2024. Ministry of Railways |
| 25 | High Speed Rail (350 km/h, km operational) | 0 | 0 | 0 | — | — | No Change | Neither era built HSR — both start and end at 0 km operational. Not a decline, just no progress. Mumbai–Ahmedabad HSR (508 km, ₹1.08 lakh crore, JICA-funded) was announced in 2017 and is under construction; target revised to 2026–27. NHSRCL |
| 26 | Metro Rail — Cities Operational | 1 | 5 | 21 | +4 cities | +16 cities | NDA Stronger | MoHUA Metro Rail Policy |
| 27 | Metro Rail — Total km Operational | 65 | 362 | ~1,000 | +457% (+297 km) | +176% (+638 km) | NDA Stronger | P1 had higher % from a tiny base (65 km). P2 added 638 km in absolute terms vs P1's 297 km — more than double. P2 also expanded to 20 new cities; P1 was mainly Delhi. MoHUA |
| 28 | Operational Airports | 61 | 75 | 150 | +23% | +100% | NDA Stronger | UDAN regional connectivity scheme launched 2016 drove tier-2/tier-3 airport expansion. AAI / MoCA |
| 29 | Air Passengers — Domestic (million/yr) | ~40M | ~61M | ~160M | +53% (+21M) | +162% (+99M) | NDA Stronger | P2 added 99M annual passengers vs P1's 21M — 4.7× more in absolute terms. India became the world's 3rd-largest domestic aviation market. LCCs drove much of this demand-side, but UDAN regional connectivity (2016) plus airport expansion (75 → 150 operational) were the supply-side policy enablers. Both demand and policy contributed; the era differential is too large to wash out as exogenous. DGCA |
| 30 | Registered Vehicles (millions, cumulative) | ~57M | ~185M | ~380M | +225% (+128M) | +105% (+195M) | NDA Stronger | P2 added 195M vehicles vs P1's 128M — 1.5× more in absolute terms. Both eras benefited from rising aspirational class and cheaper credit (exogenous drivers); P2 delivered the larger absolute expansion regardless. Accident-rate per vehicle data (#31) is the cleaner safety-policy metric. VAHAN Dashboard / MoRTH |
| 31 | Road Accident Fatalities (annual) | ~83,000 | ~1,40,000 | ~1,68,491 | +69% | +20% | NDA Stronger | Absolute deaths rose +20% under NDA vs +69% under UPA, on a vehicle fleet that grew far faster. Deaths per 1 lakh registered vehicles fell from ~57 (2014) to ~38 (2024) — a ~33% improvement. Deaths per 1 lakh population also declined. Fairer metric: NDA reduced accident rate meaningfully despite more roads and far more vehicles. MoRTH Road Accidents Report |
| 32 | Railway Electrification (% of total route km) | ~23% | ~36% | ~100% (Dec 2023) | +13pp | +64pp | NDA Stronger | Verdict based on absolute pp added: P2 +64pp vs P1 +13pp — decisively NDA. India completed 100% railway electrification of broad-gauge routes by Dec 2023, eliminating diesel traction (~₹16,000 Cr/year fuel saving). This was a stated NDA Mission Electrification target. UPA laid groundwork but scale-up was overwhelmingly P2. Ministry of Railways Annual Report |
| 33 | Major Port Cargo Throughput (million tonnes, annual) | ~314 MT | ~851 MT | ~1,600 MT (FY24) | +537 MT | +749 MT | NDA Stronger | Verdict based on absolute MT added: P2 +749 MT vs P1 +537 MT. Sagarmala Programme (2016) targeted port-led industrialization — modernization, new berths, rail connectivity to hinterland. Capacity utilization improved; turnaround time fell from ~4 days (2014) to ~0.9 days (2024). Sagarmala / MoPSW |
| 34 | Logistics Performance Index — Score (World Bank, 1–5) | 3.07 (2007) Rank 39/150 (26th %ile) | 3.08 (2014) Rank 54/160 (34th %ile) | 3.41 (2023) Rank 38/139 (27th %ile) |
Score +0.01 (flat); %ile 26→34 (worsened) | Score +0.33; %ile 34→27 (improved) | NDA Stronger | Verdict based on LPI score (comparable across years) AND percentile-adjusted rank. UPA left logistics score flat and percentile worsened (26th→34th). NDA improved score by +0.33 and recovered to 27th percentile — Sagarmala, PM Gati Shakti (multimodal logistics), NLP 2022 drove gains. India target: top 25 in LPI by 2030. World Bank LPI |
B. Roads & Transport — Section Score (19 metrics)
16
NDA ↑
0
UPA ↑
3
Mixed
C. Energy & Power
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 32 | Total Installed Power Capacity (GW) | 107 | 250 | ~500 | +134% (+143 GW) | +100% (+250 GW) | NDA Stronger | P2 added 250 GW vs P1's 143 GW in absolute terms. P2 also shifted the mix — renewable went from ~5% to ~25% of installed capacity. Base effect: P1 had higher % from 107 GW base. CEA (Central Electricity Authority) |
| 33 | Solar Energy Installed Capacity (GW) | ~0.01 | 2.6 | ~90 | Nascent | +3,362% | NDA Stronger | India became world's 3rd largest solar market. Target: 500 GW renewable by 2030. This is a genuine P2 achievement — solar barely existed in P1. MNRE |
| 34 | Wind Energy Installed Capacity (GW) | ~4.4 | ~22 | ~46 | +400% (+17.6 GW) | +109% (+24 GW) | NDA Stronger | P2 added 24 GW of wind capacity vs P1's 17.6 GW — 1.4× more in absolute terms. P1's headline % advantage is base-effect-driven (started at only 4.4 GW). P2 focus shifted heavily to solar (which is cheaper), so wind growth as a share decelerated — but more GW of wind were nonetheless added. MNRE |
| 35 | Renewable Energy % of Total Power Gen | ~29% (mainly hydro) | ~30% | ~40% | +1pp | +10pp | NDA Stronger | Non-hydro renewable: 2014 ~5%, 2024 ~25% — a structural shift. CEA |
| 36 | Household Electrification (%) | ~56% | ~67% | ~99.9% | +11pp | +32pp | NDA Stronger | Saubhagya scheme (2017) provided connections to ~26M unelectrified homes. Quality of supply (hours/day) still uneven but access is near-universal. Saubhagya Portal / MoP |
| 37 | Coal Production (million tonnes) | 407 | 612 | ~997 | +50% | +63% | NDA Stronger | India became coal self-reliant — imports reduced. Coal India production crossed 900 MT. Dual-edged: energy security vs. climate commitments. Coal India Ltd |
| 38 | Electric Vehicles Sold (thousands, annual) | <1 | ~3 | ~1,700 | Nascent | Explosive | NDA Stronger | FAME I (2015), FAME II (2019), PLI for EV battery drove growth. 2-wheeler EVs dominate. Cars: ~100k units. VAHAN / SIAM |
C. Energy & Power — Section Score (7 metrics)
7
NDA ↑
0
UPA ↑
0
Mixed
D. Digital & Technology
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 39 | Internet Users (millions) | ~18M | ~243M | ~950M | +1,250% (+225M) | +291% (+707M) | NDA Stronger | P2 added 707M internet users vs P1's 225M — over 3x more in absolute terms. Jio (Sept 2016) dropped data to near-zero price; India went from the world's most expensive to cheapest data. Base effect: P1 started from only 18M. TRAI Telecom Subscription Data |
| 40 | Mobile Subscribers (millions) | 76 | 944 | ~1,170 | +1,142% | +24% | Mixed | Verdict revised to Mixed on saturation/ceiling grounds. Both eras grew subscribers, but the addressable market is structurally capped at ~1.0–1.1B (population minus children under ~10 and the very elderly). P1 grew into a virgin market (76M → 944M, capturing most of the addressable population in one decade). P2 inherited a near-saturated market (944M → 1,170M) where additional growth is mathematically constrained — almost the entire addressable population already had a SIM by 2014. The headline P1 advantage (+1,142% vs +24%) is real but is mechanically driven by the ceiling, not by policy quality. The substantive transition in P2 has been smartphones (~150M → 850M+), mobile data (UPI, OTT, e-commerce), and second-SIM penetration. Comparing raw subscriber growth across the two eras isn't apples-to-apples. TRAI |
| 41 | Avg Mobile Data Cost (USD/GB) | ~$12 | ~$6 | ~$0.09 | −50% | −98.5% | NDA Stronger | Jio disruption made India the world's cheapest data market. Enabled digital public goods at population scale. Cable.co.uk Worldwide Mobile Data Pricing |
| 42 | Broadband Subscribers (millions) | ~1M | ~61M | ~950M | +6,000% (+60M) | +1,457% (+889M) | NDA Stronger | P2 added 889M subscribers vs P1's 60M — 15x more in absolute terms. Jio triggered a complete market restructuring. Base effect: P1 started from ~1M, hence astronomical %. Fixed broadband still weak; 99% of P2 gains are wireless. TRAI |
| 43 | UPI Monthly Transactions (billions) | 0 | 0 | ~14B | — | Built from zero | NDA Stronger | UPI launched Oct 2016. India now processes more real-time digital payments than USA + Europe + China combined. A genuine global first. NPCI UPI Stats |
| 44 | Aadhaar Enrollment (millions) | 0 | ~600M | ~1,380M | +600M absolute | +780M absolute | Mixed | Verdict revised to Mixed — both eras contributed substantively. UPA initiated and built Aadhaar (UIDAI formed 2009, ~600M enrolled by 2014). NDA scaled and operationalised it (added 780M, integrated into DBT, Jan Dhan, ITR, KYC, vaccine drive). Absolute additions favour P2 (780M vs 600M) but P1 did the foundational work from zero. Calling either era "stronger" misses that this was a relay handoff that worked. UIDAI |
| 45 | IT / Software Exports (USD billion) | $13B | $86B | ~$290B | +562% (+$73B) | +237% (+$204B) | NDA Stronger | P2 added $204B in absolute IT exports vs P1's $73B — 2.8x more. GCC boom (1,700+ centres by 2025) is a structural P2 shift. Base effect: P1 started from $13B, hence high %. NASSCOM Tech Report 2025 |
| 46 | Unicorn Startups (count) | ~1 | ~3 | ~110 | +2 | +107 | NDA Stronger | India became 3rd largest startup ecosystem globally. Flipkart ($21B exit), Zepto, Meesho, CRED etc. driven by P2 conditions — cheap data, UPI, digital-native consumers. Hurun India / CB Insights |
| 47 | BharatNet — OFC Laid (km, cumulative) | 0 | 0 | ~680,000 | — | New initiative | NDA Stronger | Target: fiber to all ~250,000 Gram Panchayats. Execution has been slower than planned but significant ground covered. DoT / BharatNet |
| 48 | CoWIN / DigiLocker / ONDC (digital public infra) | 0 | 0 | Active | — | Built in P2 | NDA Stronger | India Stack — Aadhaar + UPI + DigiLocker + CoWIN + ONDC — is arguably India's most globally replicated policy innovation. Recognized by IMF, World Bank, G20. India Stack |
| 48a | Global Innovation Index Rank (WIPO) | ~62/117 (2007) (53rd %ile) | 76/143 (2014) (53rd %ile) | 39/132 (2023) (30th %ile) |
%ile: flat (53→53) | %ile: 53→30 (+23pp) | NDA Stronger | UPA kept India flat in innovation percentile rank despite global expansion. NDA moved India from 53rd to 30th %ile — driven by startup ecosystem growth, patent filings, R&D investment, and tech talent pool. India's GII rank improvement (76→39) is one of the largest rises globally in a decade. India now outranks China (26) is within reach. Target: top 25 by 2027. WIPO Global Innovation Index |
| 48b | Indian Unicorns — Count (startups valued $1B+) | 0 (2006) | 4 (2014) | ~111 (2024) | +4 | +107 | NDA Stronger | India is now the world's 3rd-largest startup ecosystem after US and China. Unicorns span fintech, edtech, logistics, SaaS, D2C. UPA built the policy foundations (Startup India launched 2016 under NDA, but digital infra groundwork was laid earlier). Funding peaked in 2021-22; corrected since. NASSCOM / Tracxn |
| 48c | ISRO — Satellites Launched & Major Milestones | ~8 satellites (2003–04 era baseline) | ~38 satellites (2003–14) 1 landmark mission Chandrayaan-1 (2008) | ~130 satellites (2014–25) 6 landmark missions |
~30 satellites added 1 landmark mission | ~92 satellites added 6 landmark missions |
NDA Stronger | Verdict based on total satellites launched + landmark missions. P1 (2003–14): ~38 satellites across PSLV/GSLV missions; landmark: Chandrayaan-1 (2008, India's first lunar orbiter, first to detect water ice on Moon). P2 (2014–25): ~130 satellites including PSLV-C37 (2017, set world record of 104 satellites in single launch — smashed previous record of 37), Cartosat, NavIC constellation (7 satellites, India's own GPS), and commercial launches via NewSpace India Ltd. Landmark missions: Mangalyaan/MOM (2014, first Asian Mars mission, first attempt globally to succeed), PSLV-C37 (world record), Chandrayaan-2 (2019, partial success), Chandrayaan-3 (2023, first ever soft landing on Moon's south pole), Aditya-L1 (2023, solar observatory at L1 point), Gaganyaan crewed mission in progress. NDA era is decisively stronger on both volume and milestone quality. ISRO |
D. Digital & Technology — Section Score (13 metrics)
11
NDA ↑
0
UPA ↑
2
Mixed
E. Public Health
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 49 | Life Expectancy at Birth (years) | 64.3 | 68.5 | ~72 (proj. 2025) Actual: 70.8 (2022) |
+4.2 yrs | +3.5 yrs | Mixed | Verdict revised to Mixed. Three reasons: (a) diminishing returns — adding years gets structurally harder at higher life expectancies, (b) COVID-19 caused a 1–2 year setback in P2 (2020–21) that P1 did not face, (c) 2025 figure is projected, not measured. The 0.7-year gap (4.2 vs 3.5) is within the noise of these confounds. Both eras improved life expectancy meaningfully. World Bank / SRS India |
| 50 | Infant Mortality Rate (per 1,000 live births) | 58 | 40 | ~21 (proj. 2025) Actual: 27 (2020) |
−18pp absolute | −19pp absolute | Mixed | Verdict revised to Mixed — near-identical magnitude + projected 2025. P1 −18pp vs P2 −19pp is a 1pp gap on absolute reduction — well within the "similar magnitudes" criterion. Plus the P2 figure (~21) is projected from 2020 actual (27); only achieved if recent decline rate holds. Both eras delivered consistent, near-identical pace of reduction. World Bank / SRS Bulletin |
| 51 | Maternal Mortality Ratio (per 100k live births) | ~254 | 167 | ~70 (proj. 2025) Actual: 97 (2018–20) |
−87pp absolute | −97pp absolute | NDA Stronger | India hit SDG target of <100 ahead of schedule. Projecting ~70 by 2025 at ~9 pts/yr decline. P2 absolute reduction (167→70 = 97pp) exceeds P1's (254→167 = 87pp). Institutional deliveries: 47% (2006) → 89% (2021). WHO / MoHFW SRS |
| 52 | Under-5 Mortality Rate (per 1,000 live births) | 76 | 49 | ~26 (proj. 2025) Actual: 34 (2021) |
−27pp absolute | −23pp absolute | Mixed | Verdict revised to Mixed. Both eras reduced under-5 mortality substantially. The 4pp absolute-reduction gap (27 vs 23) is within the noise of (a) diminishing returns at lower bases (76→49 has more "low-hanging fruit" than 49→26), and (b) the 2025 figure being a projection from 2021 actual of 34. Both eras delivered on this metric. World Bank / UNICEF |
| 53 | Child Stunting Rate (% under 5, height-for-age) | 48.0% (2005-06) | 38.4% (2015-16) | ~32% (proj. 2025) Actual: 35.5% (NFHS-5, 2019-21) |
−9.6pp | −6.4pp | UPA Stronger | P1 reduced stunting by 9.6pp vs P2's 6.4pp projected — 1.5× larger absolute reduction. NFHS-5 (2019-21) actual was 35.5%; ~32% by 2025 is projected. Diminishing returns make further reduction from a lower base structurally harder, but the absolute pp gap is large enough that P1 wins by the same threshold we apply elsewhere. PM Poshan and ICDS continue to chip away. India still home to ~30% of world's stunted children. NFHS-4 (2015–16) & NFHS-5 (2019–21) |
| 54 | Child Wasting Rate (% under 5, weight-for-height) | 20.0% (2005-06) | 21.0% (2015-16) | ~17.5% (proj. 2025) Actual: 19.3% (NFHS-5, 2019-21) |
+1pp (worse) | −3.5pp | NDA Stronger | Critical nuance: wasting actually WORSENED under UPA (20→21%, +1pp). NDA reversed the trend — 21→19.3% actual (NFHS-5), projected ~17.5% by 2025. P2 absolute improvement: ~3.5pp vs P1's -1pp (worsening). Verdict is NDA Stronger on this important child nutrition metric. India still has world's highest wasting rate — work remains. NFHS-4 & NFHS-5 |
| 55 | Total Fertility Rate (TFR) | 2.9 | 2.3 | ~1.9 (proj. 2025) Actual: 2.0 (2020) |
−0.6 | −0.4 | Mixed | Verdict revised to Mixed on saturation grounds. TFR has a natural floor (most demographers place it at ~1.5–1.7 globally; sub-replacement <2.1 represents a structural transition). P1 had room to drop from 2.9 → 2.3. P2 was working against the floor — going from 2.3 → ~1.9 is mathematically harder. India crossed replacement fertility (2.1) in 2020. Both eras meaningfully advanced the demographic transition; the 0.2 gap is within saturation noise. Significant state variation: South India <1.7, UP/Bihar ~3.0. SRS / World Bank |
| 56 | Immunization — DPT3 Coverage (%) | 55% | 72% | 91% (2022) | +17pp | +19pp | NDA Stronger | Mission Indradhanush (2014 onwards) targeted zero-dose children in hard-to-reach areas. Improvement in P2 is stronger from an already higher base. WHO / UNICEF |
| 57 | Govt Health Expenditure (% of GDP) | 0.9% | 1.1% | ~2.1% (2022) | +0.2pp | +1.0pp | NDA Stronger | National Health Policy 2017 target: 2.5% of GDP by 2025. Progress made but still well below global average (6%). Ayushman Bharat (2018) a significant coverage expansion. National Health Accounts / NHP |
| 58 | Ayushman Bharat — Beneficiaries Covered | 0 | 0 | ~560M | — | New scheme | NDA Stronger | Launched 2018. Provides ₹5 lakh/year health cover to bottom 40% families (~107M families). World's largest government-funded health insurance. Utilization still low in some states. PM-JAY National Health Authority |
| 59 | Malaria Cases (millions, annual) | 1.8M | 0.88M | ~0.34M (2022) | −51% | −61% | NDA Stronger | Consistent decline in both eras. P2 reduction stronger from higher base — a genuine achievement. NVBDCP / WHO World Malaria Report |
| 60 | Global Hunger Index (GHI) Rank | 96/119 (81st %ile) | 55/120 (46th %ile) | 111/125 (2023) (89th %ile) |
+35pp %ile improved | −43pp %ile worsened | Mixed | Verdict revised to Mixed on methodology grounds. Three problems with this metric: (a) the country pool changed from 119 → 120 → 125, making cross-year rank comparisons noisy; (b) GHI methodology is officially contested by India (GoI's PIB statement disputes the child-wasting weighting heavily); (c) GHI relies on opinion-poll data for one of its four components, which India argues is non-rigorous. Both the apparent P1 improvement and P2 deterioration are partly artefacts of methodology rather than purely policy outcomes. Hard nutrition metrics (#52, #53) tell a more reliable story. Global Hunger Index / India's official response (PIB) |
| 61 | TB Incidence (per 100,000 population) | ~217 | ~195 | ~196 (2022) | −10% | −0.5% (flat) | UPA Stronger | India pledged TB elimination by 2025 (5 yrs ahead of global target). COVID-19 reversed progress significantly — TB deaths rose in 2020–21. Target looks unlikely. WHO Global TB Report |
| 62 | Medical Colleges (MBBS) | ~250 | ~381 | ~706 (2023) | +52% | +85% | NDA Stronger | MBBS seats doubled from ~51,000 (2014) to ~1,09,000 (2024). Doctor density still low at ~1 per 1,000 population. NMC (National Medical Commission) |
| 63 | Out-of-Pocket Health Expenditure (% of total health spend) | ~71% | ~68% | ~47% (2022) | −3pp | −21pp | NDA Stronger | Verdict based on absolute pp reduction (lower is better — less financial burden on households): P2 reduced by 21pp vs P1's 3pp. Ayushman Bharat (2018), state Mediclaim schemes, CGHS expansion drove dramatic shift. India's OOP was one of the world's highest; still above WHO-recommended 15–20% but trajectory has sharply improved. National Health Accounts / WHO |
| 64 | Hospital Beds per 1,000 Population (total, govt + pvt) | ~0.4 | ~0.7 | ~1.3 (2023) | +0.3 | +0.6 | NDA Stronger | Verdict based on absolute beds/1,000 added: P2 +0.6 vs P1 +0.3. AIIMS expansion (6 new under UPA, 16 under NDA), PM-ABHIM hospitals, private hospital growth. Note: most of P2 growth is private sector; public beds per capita barely improved. India still well below WHO benchmark of 3/1,000. NHA / NHSRC |
E. Public Health — Section Score (16 metrics)
9
NDA ↑
2
UPA ↑
5
Mixed
F. Education
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 63 | Literacy Rate (%) | 65% (2001 Census) | 74% (2011 Census) | ~78% (est. 2021) | +9pp | ~+4pp | Mixed | Verdict revised to Mixed on data-availability grounds. The 2021 Census was never conducted (delayed indefinitely by COVID). The P2 number is an ASER/PLFS-based estimate from 2021 — meaning the 2014–2025 comparison is built on (a) a 4-year-old proxy and (b) survey methodology that differs from the decennial Census. Without comparable Census data for both eras, a clean verdict isn't defensible. P1 also benefits from base effect (65% → 74% has more low-hanging fruit than 74% → 78%). 2011 Census: Census India |
| 64 | Secondary Gross Enrollment Ratio (%) | ~52% | ~65% | ~79% | +13pp | +14pp | Mixed | Both periods near-identical improvement. RTE Act (2009) drove P1 gains in primary; P2 gains came from secondary/higher secondary. UDISE+ / AISHE |
| 65 | Higher Education GER (%) | ~10% | ~23% | ~28% | +13pp | +5pp | UPA Stronger | P1 added 13pp vs P2's 5pp — 2.6× larger absolute expansion. P1's task was easier (lower base), but the absolute gap is large enough that UPA wins by the same threshold we apply for NDA wins. Quality of expansion remains the open question in both eras — Indian higher-ed still produces ~20 institutions in the global top-500. NEP 2020 (P2) is the structural-quality response, but the GER number itself favours P1. AISHE Report |
| 66 | Number of IITs | 7 | 16 | 23 | +9 | +7 | Mixed | Both periods added IITs. Quality concerns about newer IITs in both eras — faculty shortages, research output. MoE |
| 67 | Number of Universities (total) | ~348 | ~723 | ~1,168 | +108% (+375) | +62% (+445) | Mixed | Verdict revised to Mixed. Headline % favours P1 (+108%), but in absolute terms P2 added MORE universities (445 vs 375). The P1 % advantage is base-effect-driven. Both eras grew the university count substantially. Quality remains highly variable across both eras — only ~20 Indian institutions are in the global top-500. NEP 2020 is P2's structural reform response, but quality outcomes are slow-moving. UGC |
| 68 | School Dropout Rate — Secondary (%) | ~55% | ~17% | ~12.6% (2022) | −38pp | −4.4pp | UPA Stronger | P1 reduced secondary dropout by 38pp vs P2's 4.4pp — 8.6× larger absolute reduction. P1's task was structurally easier (more low-hanging fruit when 55% were dropping out), but the absolute gap is overwhelming. RTE Act (2009) and Sarva Shiksha Abhiyan drove the bulk of P1 reduction. P2 progressed against a much harder residual cohort (migrant households, marginalised rural). Both eras delivered meaningful reduction; the magnitude favours P1. UDISE+ |
| 69 | Education Spending (% of GDP) | ~3.2% | ~3.8% | ~2.9% | +0.6pp | −0.9pp | UPA Stronger | NEP 2020 targets 6% of GDP. India spends less on education as % of GDP in P2 despite a larger economy. Absolute spending has risen but not kept pace with GDP. World Bank / MoE |
| 70 | Learning Outcomes (ASER rural % reading Std 2 text by Std 5) | ~53% (2008) | ~48% (2014) | ~58% (2023) | −5pp (worse) | +10pp | NDA Stronger | Foundational literacy actually declined in P1 despite enrollment growth — the "schooling without learning" crisis. P2 recovery driven by NIPUN Bharat (2021) focus on foundational learning. ASER (Annual Status of Education Report) |
F. Education — Section Score (8 metrics)
1
NDA ↑
3
UPA ↑
4
Mixed
G. Poverty, Welfare & Agriculture
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 71 | Poverty Headcount ($2.15/day, 2017 PPP, %) | ~38% | ~21% | ~7% (proj. 2025) Actual: 12.9% (2021) |
−17pp | −14pp | Mixed | Verdict revised to Mixed. Headline pp-reduction favours P1 (−17 vs −14) — a 3pp gap, within the similar-magnitudes noise window. Plus P2's −14pp is partly projected (actual 12.9% in 2021; ~7% in 2025 assumes continued decline). Crucially, getting from 21% → 7% is structurally harder than 38% → 21% (diminishing returns at lower bases). Both eras delivered historically significant poverty reduction. World Bank PovcalNet |
| 72 | Multidimensional Poverty Index (MPI, % MPI poor) | 55.1% (2005-06) | ~33% (2015-16) | ~9% (proj. 2025) Actual: 14.96% (2019-21); NITI: 11.28% (2022-23) |
−22pp | −24pp | Mixed | Verdict revised to Mixed — near-identical magnitude + projected 2025. P1 −22pp vs P2 −24pp is a 2pp gap on absolute reduction — well within similar-magnitudes noise. NITI Aayog's actual 2022-23 number is 11.28%; the ~9% by 2025 figure is projected. Programs that contributed to P2 reduction (Ujjwala, Jal Jeevan, PM-AWAS, Swachh Bharat) are clearly NDA's, but the rate of MPI improvement was already strong under P1 (NFHS-3 to NFHS-4). Both eras delivered historic gains; the comparison isn't policy-distinguishing. OPHI MPI / NITI Aayog MPI India |
| 73 | Open Defecation Free — Rural Sanitation Coverage (%) | ~22% | ~39% | ~70%+ (JMP 2022) | +17pp | +31pp | NDA Stronger | Govt claims 100% ODF (10+ crore toilets built). JMP/independent surveys: 70%+ using improved sanitation. Even at 70%, the improvement is dramatic. Swachh Bharat Mission / WHO-UNICEF JMP 2023 |
| 74 | Tap Water Access — Rural Households (%) | ~18% | ~32% | ~75.8% (Mar 2024) | +14pp | +44pp | NDA Stronger | Jal Jeevan Mission (Aug 2019): 14.6 crore rural households connected with tap water. Over 11 crore new connections in 5 years. Jal Jeevan Mission Dashboard |
| 75 | LPG Connections (millions, total India) | ~96M | ~148M | ~315M | +54% | +113% | NDA Stronger | Ujjwala Yojana gave free LPG connections to ~10.35 crore BPL women. Refill rates are a concern (~3.5 cylinders/year vs ~7 for others) — cost remains a barrier. PMUY / MoPNG |
| 76 | Jan Dhan Bank Accounts (millions) | 0 | ~15M (Aug 2014) | ~530M (2024) | Program started | +3,433% | NDA Stronger | Launched Aug 28, 2014. Largest financial inclusion drive in history. Average balance ~₹4,000. Enabled direct benefit transfer (DBT). PMJDY Portal / DFS |
| 77 | MGNREGA Person-Days Generated (crore/yr) | ~9 (FY06, partial) | 166 (FY14) | ~312 (FY24) | Scheme built | +88% | UPA Stronger | Higher MGNREGA demand signals rural distress, not success. P2 saw higher demand (peak FY21: 389 crore — COVID year). Real rural wages grew at <2% vs >5% in P1. The program expanded but the distress signal is concerning. MoRD MGNREGA Dashboard |
| 78 | Food Grain Production (million tonnes, annual) | ~208 | ~265 | ~332 (FY24) | +27% | +25% | Mixed | Both periods near-identical growth. India became a net food exporter. However, nutritional diversity (pulses, vegetables) is lagging cereal growth. DACFW / MoAFW |
| 79 | MSP for Paddy (₹/quintal) | ₹570 | ₹1,310 | ₹2,183 (FY24) | +130% | +67% | UPA Stronger | P1 saw larger MSP hikes. Inflation-adjusted (real) MSP growth was strong in P1; real growth in P2 has been modest after accounting for inflation. CACP (Commission for Agricultural Costs and Prices) |
| 80 | PM Awas Yojana — Houses Constructed (millions) | 0 (IAY precursor) | ~4M (IAY cumulative) | ~40M+ (PMAY-G+U) | Prior scheme | 10x scale | NDA Stronger | PMAY built more houses in absolute terms. Quality of construction and actual occupancy rates are the legitimate critique. PMAY-G Portal / PMAY-U MIS |
| 81 | Real Rural Wage Growth (avg annual, %) | — | — | — | ~5–6% real | <2% real | UPA Stronger | One of the most concerning economic signals of P2. Rural wages grew fast in P1 (MGNREGA floor effect, low base). Real wage growth collapsed post-2014. High MGNREGA demand corroborates. RBI KLEMS / Labour Bureau Agricultural Wages Report |
| 82 | Milk Production (million tonnes, annual) | 96.9 | 146.3 | 239.3 (FY24) | +51% | +64% | NDA Stronger | India is world's largest milk producer. Growth accelerated in P2; India supplies ~24% of global milk output. DAHD (Dept of Animal Husbandry) |
| 83 | DBT (Direct Benefit Transfer) — Annual (₹ lakh crore) | ~0 | ~0.7 (FY14) | ~7.4 (FY24) | Launched | +957% | NDA Stronger | DBT started under UPA (2013). NDA scaled massively — ₹34 lakh crore cumulative transferred 2014–2024. Leakage reduced significantly (Aadhaar+Jan Dhan+Mobile trinity). DBT Bharat Portal |
| 84 | Free Food Grain (PM Garib Kalyan Ann Yojana — beneficiaries) | 0 | 0 | 800M (2020–2024) | — | New scheme | NDA Stronger | Launched during COVID-19 (April 2020). 5 kg free grain/person/month to ~80 crore NFSA beneficiaries. Extended to Dec 2028. World's largest food security program. Fiscal cost: ~₹11.8 lakh crore over 5 years. DFPD / MoCA |
| 85 | Total Foodgrain Production (million tonnes, annual) | ~213 MT | ~265 MT | ~328 MT (FY24) | +52 MT | +63 MT | NDA Stronger | Verdict based on absolute MT added: P2 +63 MT vs P1 +52 MT. India is now the world's 2nd largest food producer. PM Fasal Bima Yojana (crop insurance), PM-KISAN (₹6,000/yr income support), e-NAM (national agri market) contributed. Note: growth rate (%) was similar — base effect roughly equal since both started at comparable scale. DACFW / Ministry of Agriculture |
| 86 | Wheat Yield (tonnes/hectare) | ~2.71 | ~3.18 | ~3.55 (FY24) | +0.47 t/ha | +0.37 t/ha | Mixed | Verdict revised to Mixed. The 0.10 t/ha gap (0.47 vs 0.37) is within typical annual yield variability driven by monsoon, fertiliser supply, and pest pressure — not necessarily attributable to policy differences. Both eras improved yields steadily through MSP incentives, fertiliser subsidies, and seed-quality programs. India's wheat yield is still well below global best (China: ~5.6 t/ha; France: ~7+ t/ha) — the real story is that neither era closed that gap meaningfully. DACFW / FAOSTAT |
G. Poverty & Welfare — Section Score (16 metrics)
9
NDA ↑
3
UPA ↑
4
Mixed
H. Security & Defence
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 85 | Defence Budget (USD billion) | ~$20B | ~$38B | ~$75B | +90% | +97% | Mixed | Both periods near-doubled defence spending. India is world's 4th largest defence spender. SIPRI Military Expenditure Database |
| 86 | Defence Budget (% of GDP) | ~2.8% | ~2.4% | ~2.0% | −0.4pp | −0.4pp | Mixed | Verdict revised to Mixed — identical change in both eras. Both P1 and P2 reduced defence as % of GDP by exactly the same 0.4pp. There is no meaningful difference between the eras on this metric — the previous "UPA Stronger" verdict was misapplied (both declined equally). Underlying story: defence spending grew in absolute terms but didn't keep pace with GDP growth. Given border tensions (China 2020, Pakistan) many analysts flag underinvestment. NATO benchmark is 2%. SIPRI |
| 87 | Indigenous Defence Procurement (% of defence budget) | ~30% | ~40% | ~75% (target) | +10pp | +35pp | NDA Stronger | Make in India Defence — positive lists mandating domestic procurement. India's defence exports: $1.5B (FY24) vs ~$200M (2014). Tejas, INS Vikrant, ATAGS howitzer etc. MoD Annual Report |
| 88 | Terrorist Incidents — Annual (India total) | ~1,000+ | ~700 | ~200–300 | −30% | −57% | NDA Stronger | Significant decline in overall terrorist incidents. Reflects both NE peace accords and declining Naxal violence. J&K remains complex. SATP (South Asia Terrorism Portal) |
| 89 | Left Wing Extremism (Naxal) — Annual Deaths (total) | ~717 (2006) | ~422 (2014) | ~138 (2023) | −41% | −67% | NDA Stronger | LWE districts: 180 (2014) → ~45 (2024). Target: LWE-free India by 2026. Significant acceleration in P2. MHA Annual Report |
| 89a | Naxal (LWE) — Civilian Deaths Specifically (annual) | ~170 (2004) | ~190 (2014) | ~45 (2023) | +20 (worsened) | −145 | NDA Stronger | Key point: civilian deaths from Naxal violence actually INCREASED under UPA (170→190) as LWE violence peaked around 2009-2011. NDA dramatically reduced civilian toll from 190 to ~45 — a 76% drop. Combined with security force operations, shrinking LWE geography, and development of "aspirational districts," this is a genuine NDA achievement. SATP India Casualties Database / MHA Annual Report |
| 89b | Civilian Deaths from Terrorism — All India (excl. Naxal, annual) | ~2,200 (2003) | ~370 (2014) | ~85 (2024) | −1,830 absolute | −285 absolute | NDA Stronger | Verdict revised to NDA Stronger. P1's larger absolute reduction is base-effect driven — the 2001–03 peak was post-9/11 / post-Kandahar exceptional violence, and the subsequent fall was substantially driven by external factors (international counter-terrorism pressure on Pakistan, J&K-specific de-escalation). P2's achievement — bringing civilian terror deaths to <100/year in a country of 1.4B people — is the harder and more policy-attributable outcome. Crossing into "historically low" territory matters more than the size of the fall from an outlier peak. SATP India Terrorism Database |
| 90 | J&K Militant Incidents (annual) | ~1,990 (2005) | ~222 (2014) | ~220 (2023) | −89% | Flat | UPA Stronger | Massive P1 reduction (from peak 2001–05 levels). P2 saw Article 370 abrogation (2019) — incidents flat despite structural change. Civilian casualties have declined. SATP J&K Data |
| 91 | India Global Peace Index Rank | ~132/140 (2008) (94th %ile) | 143/162 (88th %ile) | 116/163 (2024) (71st %ile) |
+6pp %ile improved | +17pp %ile improved | NDA Stronger | Percentile-adjusted: UPA improved India from 94th to 88th %ile (+6pp). NDA improved from 88th to 71st %ile (+17pp) — a significantly stronger improvement. Raw rank change (143→116) understates the improvement since country count grew. GPI — Institute for Economics & Peace |
| 92 | India's Nuclear Warheads (estimated) | ~45–95 | ~90–110 | ~172 (2024) | Modest increase | Significant increase | NDA Stronger | India modernising nuclear triad (land, sea, air). INS Arihant operational (SSBN). No-first-use policy maintained. SIPRI World Nuclear Forces |
| 93 | UN Peacekeeping — Troops Deployed (annual avg) | ~4,500 | ~8,000 | ~5,800 (2024) | +3,500 | −2,200 | UPA Stronger | Verdict based on absolute troop change: P1 added 3,500 troops (+78%); P2 reduced by 2,200 (−28%). India is historically one of the world's largest UN peacekeeping contributors. The P2 reduction reflects a deliberate foreign policy shift — India is pursuing bilateral/strategic relationships over multilateral UN commitments. Not necessarily bad policy, but the metric shows UPA had greater multilateral engagement by this measure. UN Peacekeeping Data |
H. Security & Defence — Section Score (11 metrics)
7
NDA ↑
2
UPA ↑
2
Mixed
I. Governance & Institutions
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 93 | Corruption Perception Index (CPI) Score (0–100) | 29/100 Rank 83/133 (62nd %ile) | 38/100 Rank 85/175 (49th %ile) | 39/100 (2023) Rank 93/180 (52nd %ile) |
+9 score pts; %ile 62→49 (improved) | +1 score pt; %ile 49→52 (slightly worse) | UPA Stronger | Score is the right metric (more countries joined over time inflating ranks). UPA improved score dramatically (29→38, +9pts) while also improving percentile rank. NDA only managed +1pt in 11 years — other countries reformed faster. Percentile confirms UPA Stronger. Transparency International CPI |
| 94 | Press Freedom Index Rank (RSF) | ~105/168 (2006) (62nd %ile) | 140/180 (78th %ile) | 159/180 (2024) (88th %ile) |
%ile: 62→78 (−16pp) | %ile: 78→88 (−10pp) | Mixed | Verdict revised to Mixed — both eras worsened press freedom; neither has a clean record. P1 percentile worsened by 16pp (62nd → 78th). P2 worsened by 10pp (78th → 88th). The deterioration accelerated under UPA in relative terms — both eras contributed to the structural decline (journalist arrests, UAPA usage, media ownership concentration, government advertising as leverage). Neither era reversed the slide. RSF World Press Freedom Index |
| 95 | Democracy Index — EIU Score (0–10) | 7.68 (2008, "Flawed Democracy") | 7.92 (2014) | 7.22 (2023, "Hybrid Regime") | +0.24 | −0.70 | UPA Stronger | India downgraded from "Flawed Democracy" to "Hybrid Regime" in 2021. EIU cites civil liberties, press freedom, functioning of government. India disputes the classification. V-Dem (Sweden) also shows democratic backsliding. EIU Democracy Index |
| 96 | Ease of Doing Business Rank (World Bank) | ~116/175 (2006) (66th %ile) | 142/189 (75th %ile) | 63/190 (2020)* (33rd %ile) |
%ile: 66→75 (−9pp, worsened) | %ile: 75→33 (+42pp, dramatic jump) | Mixed | Verdict revised to Mixed on methodology-dispute grounds. World Bank discontinued the EoDB index in 2021 after an internal investigation found data irregularities affecting multiple country rankings — India was implicated in the 2018–20 rounds (the same rounds that produced India's headline jump). Real GST, IBC, and regulatory reforms genuinely happened under NDA — but the EoDB rank specifically cannot be cited as clean evidence given the discontinuation. The directional improvement is real; the magnitude is contested. World Bank EoDB |
| 97 | Income Tax Returns Filed (millions) | ~30M | ~40M | ~90M (FY24) | +33% | +125% | NDA Stronger | GST + Aadhaar + UPI trails expanding the formal economy. Tax net widened significantly. CBDT Annual Report |
| 98 | UN E-Government Development Index Rank | ~113/191 (2005) (59th %ile) | 118/193 (61st %ile) | 105/193 (2022) (54th %ile) |
%ile: 59→61 (−2pp, flat) | %ile: 61→54 (+7pp) | NDA Stronger | UPA left e-governance percentile essentially flat (59th→61st). NDA improved 61st→54th %ile driven by Digital India, CoWIN, DigiLocker, UMANG, ONDC. Still below India's income-level peers — structural gap vs digital ambitions. UN E-Government Survey |
| 99 | Supreme Court Pending Cases (millions) | ~3.5M | ~5.2M | ~5.0M (2024) | +49% | −4% | Mixed | District court pendency: ~46M cases (2024). Judicial delay is structural — both governments have failed to appoint enough judges. P2 marginally better on High Court vacancies. National Judicial Data Grid |
| 100 | RTI Applications Filed (millions, cumulative) | 0 (RTI Act: 2005) | ~17M cumulative | ~35M cumulative | Framework built | +106% | UPA Stronger | RTI usage grew but 2019 RTI Amendment weakened CIC independence. Backlog of RTI appeals at CICs has grown. Transparency activists flag structural weakening of the act. CIC (Central Information Commission) |
| 100a | Henley Passport Index — Visa-Free Countries (India passport) | ~52 countries (2006) Rank ~75/199 | ~52 countries (2014) Rank ~76/199 | ~58 countries (2025) Rank ~82/199 |
Flat (+0) | +6 countries | Mixed | India's visa-free access increased by 6 countries under NDA (vs flat under UPA). However, the absolute rank worsened (76→82) as other countries — especially ASEAN and Gulf — expanded their passport power faster. India remains significantly behind peers like China (rank ~60, ~85 countries) despite larger GDP. Diplomatic visa reciprocity agreements haven't kept pace with India's economic clout. Verdict Mixed: slight improvement in access, relative position unchanged. Henley Passport Index |
| 100b | Remittances Received (USD billion, annual) | ~$16B (2003) | ~$70B (2014) | ~$125B (2024) | +$54B absolute | +$55B absolute | Mixed | India is the world's top remittance recipient (#1 globally since 2022). Both eras saw near-identical absolute dollar increases (~$54B and ~$55B). As % of GDP: 2.8% (2003) → 3.4% (2014) → 3.4% (2024) — flat under NDA. Remittances reflect Indian diaspora performance, not directly domestic policy. Verdict Mixed. World Bank Remittances Data |
| 100c | High Court Judicial Vacancy (% of sanctioned posts vacant) | ~30% (2004) | ~26% (2014) | ~28% (2024) | −4pp (improved) | +2pp (worsened) | UPA Stronger | Verdict based on absolute pp change: UPA reduced vacancies by 4pp; NDA allowed them to drift back up by 2pp. India has ~5,400 sanctioned High Court judge posts; only ~3,900 filled (2024). Judicial delay is endemic — 4.5 crore pending cases at all levels. Both governments failed to address structural judicial under-staffing. NJDG / Dept of Justice |
| 100d | Prison Overcrowding Rate (% of sanctioned capacity) | ~110% | ~117% | ~131% (2022) | +7pp (worsened) | +14pp (worsened more) | UPA Stronger | Verdict based on absolute pp deterioration: P1 worsened overcrowding by 7pp; P2 by 14pp. India's prisons hold ~5.5 lakh people against a capacity of ~4.2 lakh (2022). ~75% are undertrials — incarcerated without conviction. This is a structural failure of the justice system; verdict reflects which era worsened it more in absolute terms. NCRB Prison Statistics India |
| 100e | Index of Economic Freedom — Score (Heritage Foundation, 0–100) | ~53.8 (2006) | ~56.0 (2014) | ~57.2 (2024) | +2.2 pts | +1.2 pts | UPA Stronger | Verdict based on absolute score improvement: P1 +2.2 pts vs P2 +1.2 pts. Score is the right metric (country count has grown, making raw rank comparison unreliable). India remains in "Mostly Unfree" category (<60); both eras improved marginally. UPA's score jump was driven by deregulation, SEZs, and openness reforms. NDA's GST was transformative but partially offset by industrial licensing complexity and FDI restrictions in some sectors. Heritage Foundation Index of Economic Freedom |
| 100f | Free Trade / CEPA Agreements Signed | 2 (2003–04) | 8+ comprehensive agreements | 3 new CEPAs (2022–24) | +6 agreements | +3 agreements (but RCEP rejected) | UPA Stronger | Verdict based on count: UPA signed ASEAN FTA (2009), South Korea CEPA (2010), Japan CEPA (2011), Malaysia CECA (2011), Sri Lanka, Singapore, Nepal, Bhutan — 6+ comprehensive multilateral/bilateral deals. NDA signed UAE CEPA (2022), Australia ECTA (2022), Mauritius CECPA (2021) but rejected RCEP (2019) — India's largest ever potential trade deal — citing domestic industry concerns. UK FTA ongoing since 2022. UPA Stronger on count; NDA's RCEP rejection may prove strategically correct given China-linked risks. Ministry of Commerce FTA List |
| 100g | Major International Summits Hosted / Diplomatic Firsts | CWG 2010; multiple bilateral summits | CWG 2010, BRICS, East Asia Summits | G20 Presidency 2023; Quad; SCO; Voice of Global South | Significant hosting | G20 — highest multilateral profile | Mixed | Verdict Mixed — both eras hosted major events and built diplomatic relationships. UPA: Commonwealth Games 2010, multiple bilateral + BRICS foundations. NDA: G20 Presidency 2023 (achieved joint communiqué incl. on Russia-Ukraine — diplomatic win), Quad leadership, Voice of Global South Summit (100+ nations), SCO chairmanship 2023. NDA has arguably elevated India's global diplomatic profile more, but UPA expanded regional relationships deeper. Ministry of External Affairs |
I. Governance & Institutions — Section Score (17 metrics)
2
NDA ↑
7
UPA ↑
6
Mixed
J. Environment
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 101 | Forest Cover (million hectares) | 67.7 | 70.2 (2015 SFR) | ~72.6 (proj. 2025) Actual: 71.6 (SFR 2023) |
+2.5M ha | +2.4M ha | Mixed | SFR 2023 recorded 71.6M ha. Projecting ~72.6 by 2025. P2 (70.2→72.6 = +2.4M ha) and P1 (67.7→70.2 = +2.5M ha) are essentially identical — verdict Mixed. Note: "forest cover" includes plantations; natural forest loss continues in biodiversity-rich areas. FSI State of Forest Report |
| 102 | CO₂ Emissions per Capita (tonnes/person) | 1.2 | 1.7 | ~1.9 (2022) | +42% (worse) | +12% | NDA Stronger | Still very low vs global average (4.7t). Emissions per capita are growing — renewable push has slowed the rate of increase in P2. Our World in Data / IEA |
| 103 | Air Quality — PM2.5 (Delhi annual mean, μg/m³) | ~140 | ~160 | ~155 (2023) | +14% (worse) | −3% (slight) | Mixed | Verdict revised to Mixed. Earlier "UPA Stronger" verdict was misattributed — the data actually shows UPA worsened the metric (+14%) while NDA marginally improved it (−3%). However, the NDA improvement (5 μg/m³) is within annual measurement noise, and the absolute level (155 μg/m³) remains 31× the WHO limit (5 μg/m³). Neither era meaningfully changed the structural problem. NCAP (2019) targets 40% reduction by 2026 from 2017 baseline. Overall India ranks among world's most polluted countries. CPCB / IQAir World Air Quality Report |
| 104 | India NDC Commitment — Renewable % of capacity by 2030 | — | ~2015: pledged 40% | 40% achieved by 2023 (ahead of schedule) | — | Target met early | NDA Stronger | India met its Paris Agreement NDC target (40% non-fossil power capacity) 9 years early. New target: 50% by 2030. UNFCCC India NDC 2022 |
| 105 | Wetlands Notified under Ramsar (count) | 19 (2005) | 26 (2014) | 80 (2024) | +7 | +54 | NDA Stronger | India has world's 4th most Ramsar sites. Ramsar Convention |
J. Environment — Section Score (5 metrics)
3
NDA ↑
0
UPA ↑
2
Mixed
K. Society — Top and Bottom
This section looks at how India's richest and poorest have fared. Growth is necessary but not sufficient — who captured that growth matters.
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| 106 | India Billionaires — Count (Forbes) | 13 | 56 | ~200 (2024) | +331% | +257% | Mixed | Both periods saw billionaire class expand dramatically. Top 5 Indians own more than bottom 50% combined. Forbes India Rich List |
| 107 | Top 10% Income Share (% of national income) | ~52% | ~55% | ~60% (2022) | +3pp (more unequal) | +5pp (more unequal) | UPA Stronger | Both eras saw rising inequality. India's top 10% captured a growing share of income in both decades. World Inequality Database |
| 108 | Bottom 50% Income Share (% of national income) | ~16% | ~15% | ~13% (2022) | −1pp | −2pp | UPA Stronger | Bottom half of India's population earns a declining share of national income across both eras. Absolute incomes rose, but relative share fell. World Inequality Database (WID) |
| 109 | Gini Coefficient — Income vs Wealth (0=equal, 1=max) | Income ~0.37 Wealth ~0.74 | Income ~0.38 Wealth ~0.77 | Income ~0.35 (WB) Wealth ~0.83 (2024) |
Slight rise income | Sharp rise wealth | Mixed | Two very different pictures depending on which Gini you use. Income Gini (World Bank): India is among the world's 4th most equal countries by income distribution (~0.35), and has marginally improved under NDA — driven by DBT, rural welfare schemes, and MGNREGA continuity. Wealth Gini (~0.83) tells the opposite story: top 1% own 40% of wealth. However, the wealth inequality surge is a global phenomenon — driven by asset price inflation (stocks, real estate) post-2014 which lifted rich households everywhere. India's wealth Gini rise mirrors USA, UK, and China. Income equality is the fairer governance measure; wealth inequality is partly structural. WID / World Bank Gini |
| 110 | Unemployment Rate — CMIE (%, annual avg) | ~7% (2004-05 NSSO) | ~4.9% (PLFS 2014) | ~8% (CMIE 2023) | Declined | Rose | UPA Stronger | Highly contested data. PLFS (govt survey) shows 3.2% (2022-23). CMIE shows 7-9%. Demonetisation (2016), GST transition, and COVID contributed to job losses. Urban youth unemployment particularly elevated. CMIE / PLFS (MoSPI) |
| 111 | Female Labour Force Participation Rate (%) | ~26% | ~23% (2013-14) | ~37% (PLFS 2023) | −3pp (worse) | +14pp | NDA Stronger | Dramatic reversal — fLFPR had been falling since 2005. Post-2019 rise partly driven by rural female self-employment (farming, MGNREGA). Urban FLFPR still very low (~22%). ILO: ILO ILOSTAT |
| 112 | Women in Parliament — Lok Sabha (%) | 8.3% (2004) | 11.4% (2014) | 13.6% (2024) | +3.1pp | +2.2pp | Mixed | Women's Reservation Bill passed 2023 (33% seats reserved) — implementation awaits delimitation post-2026 Census. Both eras made incremental progress. Global avg: 26.5%. Lok Sabha Secretariat / IPU Parline |
| 113 | Crimes Against Women — Registered (thousands, annual) | ~143k | ~338k | ~445k (2022) | +136% | +32% | Mixed | The sharp P1 increase is partly better reporting (post-Nirbhaya, 2012). P2 increase is more gradual. Difficult to separate actual incidence from reporting rates. Both need improvement. NCRB Crime in India Report |
| 114 | Women in Parliament — Lok Sabha (% of seats) | 8.3% (2004) | 11.8% (2014) | 13.6% (2024) | +3.5pp | +1.8pp | UPA Stronger | Verdict based on absolute pp gained: P1 +3.5pp vs P2 +1.8pp. UPA increased representation faster. Note: NDA passed the Women's Reservation Bill (2023) guaranteeing 33% seats — but effective only after the next Census + delimitation (~2029+). Policy intent under NDA is stronger; realized outcome during P2 was slower. India at 13.6% is far below global average of ~26%. IPU Women in Parliament |
| 115 | Child Marriage Rate (% girls married before age 18) | ~47% (2005-06) | ~27% (2015-16) | ~23% (proj. 2025) Actual: 23.3% (NFHS-5, 2019-21) |
−20pp | −4pp (proj.) | UPA Stronger | Verdict based on absolute pp reduction: P1 reduced child marriage by 20pp — one of the largest declines globally in a decade, driven by MGNREGA (girls in school longer), mid-day meals, and conditional cash transfers. P2 reduced by ~4pp (projected to 2025). Rate has plateaued — further reduction needs structural change in BIMARU states. NFHS-4 & NFHS-5 |
| 116 | LGBTQ+ Rights — Section 377 Legal Status | Criminalized (IPC 377) | HC decriminalized 2009 → SC re-criminalized 2013 (UPA era, SC's call) | SC permanently decriminalized 2018; marriage equality denied 2023 | Net backward (SC re-criminalized end of P1) | Permanent decriminalization achieved | Mixed | Verdict Mixed — both eras had progress and setbacks. UPA: Delhi HC read down 377 (2009, positive), but SC reversed it in 2013 (setback — SC decision, not government, but UPA didn't aggressively challenge). NDA: SC permanently decriminalized Section 377 in 2018 (Navtej Johar). But NDA govt opposed marriage equality in court (2023 SC judgment). Net outcome: decriminalization happened under NDA (factually better final position in P2), but full equality blocked. Supreme Court of India |
| 117 | Olympic Medals — Summer Olympics (total per era) | — | 10 medals Athens 2004: 1, Beijing 2008: 3, London 2012: 6 | 15 medals Rio 2016: 2, Tokyo 2020: 7, Paris 2024: 6 |
+10 medals in era | +15 medals in era | NDA Stronger | Verdict based on total medals won during each era: NDA era covered 3 Olympics and produced 15 medals (incl. Tokyo 2020 — India's best-ever, 7 medals, first-ever athletics gold: Neeraj Chopra javelin). UPA era: 10 medals across 3 Olympics. Khelo India (2018), TOP Scheme (Targets Olympic Podium), National Sports Education Board contributed. Medal trajectory is strongly upward. IOC / Indian Olympic Association |
| 118 | International Tourist Arrivals (millions, annual) | ~2.7M (2003) | ~7.7M (2014) | ~9.2M (2024) Pre-COVID peak: 10.9M (2019) |
+5.0M absolute | +1.5M raw +3.2M to 2019 pre-COVID |
Mixed | Verdict Mixed: P1 added 5.0M in absolute terms — clearly stronger on raw numbers. P2 was decimated by COVID (2020-22: near-zero arrivals), making direct comparison unfair — same logic as not penalizing UPA for GFC. Pre-COVID trajectory (2014→2019: +3.2M in 5 years) shows comparable annual growth. NDA: e-Visa expansion (2014-16 simplified dramatically), Incredible India 2.0, medical tourism growth. COVID asymmetry makes this Mixed. Ministry of Tourism / UNWTO |
| 119 | Electricity Access — Household Coverage (%) | ~60% (2004-05) | ~88.5% (2014) | ~97.8% (2024) SAUBHAGYA: 99.9% connections by 2019 |
+28.5pp | +9.3pp | NDA Stronger | P1's headline pp-gain looks larger (28.5pp vs 9.3pp), but the metric has a hard 100% ceiling and NDA achieved near-universal coverage (97.8%). The last-mile pp at the top of the curve is structurally far harder than the same pp at the middle. Saubhagya scheme electrified 26M previously unconnected households (2017–19) — the structurally hardest cohort (remote, hilly, tribal). UPA built scale to 88.5%; NDA closed the gap to ceiling — the latter is the policy achievement on this metric. GARV Dashboard / NFHS-4/5 |
| 120 | LPG / Clean Cooking Fuel — Household Coverage (%) | ~22% (2004-05) | ~44% (2014) | ~75% (2024) NFHS-5: 58.6% primary fuel; incl. LPG subsidised |
+22pp | +31pp | NDA Stronger | Verdict based on absolute pp added: P2 +31pp vs P1 +22pp. NDA's Pradhan Mantri Ujjwala Yojana (PMUY, 2016) released 10 crore free LPG connections to BPL women — the largest clean cooking fuel programme ever. P2 started from a higher base (44%) and still added more pp. Indoor air pollution from biomass cooking is one of India's leading preventable health risks — this is a genuine bottom-of-pyramid impact. PMUY Dashboard / NFHS-4/5 |
| 121 | Mobile Phone Ownership — Households with phone (%) | ~18% (2004-05) | ~84% (2014) | ~97% (2024) NFHS-5: 95.9% |
+66pp | +13pp | NDA Stronger | P1's headline pp-gain (+66pp) is from a virgin market with a hard 100% household ceiling. P2 closed the remaining 13pp to ~97% — the structurally hardest cohort (deeply rural, low-income, last-mile). The metric cannot exceed 100% of households. NDA's contribution: Digital India / BharatNet to gram panchayats, Jio's data revolution enabled by P2 spectrum policy, JAM stack for DBT delivery. Reaching near-universal household phone ownership is the policy achievement here, regardless of which era had more pp room to grow. NFHS-4/5 / TRAI |
| 122 | Bank Account Ownership — Households with account (%) | ~35% (2004-05) | ~68% (2014) | ~97% (2024) PMJDY: 51+ crore accounts opened by 2024 |
+33pp | +29pp | NDA Stronger | P1 added 33pp from a 35% base; P2 added 29pp but closed the gap to a hard 100% household ceiling (97% reached). The last-mile pp at the top of the curve is structurally harder than the same pp at the middle (remaining unbanked households are deeply rural, low-income, or migrant). PMJDY (2014) opened 51 crore zero-balance accounts — the largest financial inclusion programme globally per Guinness. Aadhaar-linked DBT cut ~₹2.2 lakh crore in leakage. Reaching near-universal household banking is the structural policy achievement on this metric. PMJDY Dashboard / NFHS-4/5 |
| 123 | Refrigerator Ownership — Households with fridge (%) | ~15% (2004-05) | ~34% (2014) | ~50% (proj. 2025) Actual: ~45% (NFHS-5, 2019-21) |
+19pp | +16pp (proj.) | Mixed | Verdict Mixed: P1 +19pp vs P2 +16pp (projected to 2025) — comparable. Both eras saw steady rise in consumer durables ownership. Fridge ownership is a strong proxy for middle-class emergence and cold chain expansion. Driven by falling appliance prices (China manufacturing cost pass-through), rural electrification enabling usage, and rising disposable incomes in both periods. NFHS-4/5 / HCES 2022-23 (MoSPI) |
| 124 | Television Ownership — Households with TV (%) | ~47% (2004-05) | ~66% (2014) | ~75% (proj. 2025) Actual: ~67% (NFHS-5, 2019-21) |
+19pp | +9pp (proj.) | Mixed | Verdict Mixed: P1 was stronger on absolute pp (+19pp vs +9pp). The TV era effectively reached saturation — with OTT and mobile screens replacing the TV set as the primary media consumption device, especially in urban areas. P2's lower TV penetration gain partly reflects mobile phone substitution (many rural households skipped TV for smartphone screens). Saturation effect and technology substitution make raw PP comparison less meaningful here. NFHS-4/5 |
| 125 | Two-Wheeler Ownership — Households with motorcycle/scooter (%) | ~30% (2004-05) | ~53% (2014) | ~65% (proj. 2025) Actual: ~62% (NFHS-5, 2019-21) |
+23pp | +12pp (proj.) | Mixed | Verdict Mixed: P1 +23pp vs P2 +12pp. P1's larger gain reflects India's motorcycle revolution — urbanization, falling credit costs (NBFC expansion), and strong domestic manufacturing. P2 gain is lower partly due to base effect (53% is a harder base than 30%), and urban youth increasingly adopting ride-sharing (Ola/Uber) as a substitute. Both eras saw continued expansion of mobility access for lower-middle-income households. Bottom-line: poor households can today afford a motorbike in both periods; NDA sustained the trajectory. NFHS-4/5 / SIAM |
K. Society (Top & Bottom) — Section Score (20 metrics)
6
NDA ↑
5
UPA ↑
9
Mixed
L. Manufacturing & Industry
India's aspiration to become a global manufacturing hub has been a recurring policy priority. This section tracks what actually moved — in share of GDP, in absolute output, in defence exports, and in foreign investment attracted.
| # | Metric | 2003 | 2014 | 2025/Latest | P1 Change (2003–14) | P2 Change (2014–25) | Verdict | Notes & Source |
|---|---|---|---|---|---|---|---|---|
| L1 | Manufacturing as % of GDP | ~16.7% (2003) | ~14.9% (2014) | ~13.4% (2024) | −1.8pp | −1.5pp | Mixed | Verdict revised to Mixed — both eras failed to grow manufacturing's share. P1 −1.8pp vs P2 −1.5pp is a 0.3pp gap (within similar-magnitudes noise) and the direction is wrong in both eras. Earlier "UPA Stronger" verdict was actually misattributed — by absolute change P2 declined slightly less. Either way, manufacturing's share has fallen for two decades. NDA's Make in India target of 25% by 2022 was missed badly. Services sector growth has structurally outpaced manufacturing across both eras. The PLI scheme is showing early sector-specific results (mobiles, semis) but the headline share number hasn't moved. World Bank MVA / MoSPI |
| L2 | Manufacturing Value Added — Absolute (₹ Lakh Crore, constant prices) | ~₹6 L Cr (2003) | ~₹14 L Cr (2014) | ~₹28 L Cr (2024) | +₹8 L Cr | +₹14 L Cr | NDA Stronger | Verdict based on absolute INR added in manufacturing output (constant prices). P2 added ₹14 lakh crore in real manufacturing value — nearly double P1's addition of ₹8 lakh crore. This is the correct comparison: absolute rupee-value of output added to the economy. The share declining doesn't negate that real manufacturing output doubled. PLI for mobile phones (Apple, Samsung now assembled in India), defence manufacturing, chemical plants, and pharma API production all contributed. MoSPI National Accounts |
| L3 | Defence Exports (₹ Crore, annual) | ~₹400 Cr (2004-05) | ~₹686 Cr (2013-14) | ~₹21,083 Cr (2024-25) | +₹286 Cr | +₹20,397 Cr (+28x) | NDA Stronger | Verdict based on absolute growth in defence exports: NDA era represents a 28x increase — from ₹686 crore (FY14) to ₹21,083 crore (FY25). India now exports to 85+ countries including USA (EW kits), France (Pinaka rockets), Philippines (BrahMos cruise missiles). NDA set targets: ₹35,000 crore by FY25 (partially achieved). Key policy drivers: DPP reforms, FDI in defence to 74%, iDEX (innovation ecosystem), and mandatory 68 items reserved for domestic production. P1's exports were negligible. Ministry of Defence / DDP Annual Report |
| L4 | PLI Scheme — Production Output (₹ Lakh Crore, cumulative) | — | — (scheme didn't exist) | ~₹12 L Cr production (2024) across 14 PLI sectors |
N/A (P1 had no PLI) | ₹12 L Cr (NDA launch) | NDA Stronger | Production Linked Incentive (PLI) scheme launched 2020-21 across 14 sectors — ₹1.97 lakh crore in total incentives allocated. Output: mobile phones (Apple exports ₹1.2L cr), textiles, pharma API, solar panels, white goods, specialty steel. PLI generated 8+ lakh jobs by 2024. India's mobile phone export went from ₹1,556 crore (FY18) to ₹1.28 lakh crore (FY24) — a structural shift. P1 had no equivalent demand-side production incentive scheme. This is a P2-only achievement. DPIIT / PIB |
| L5 | FDI Equity Inflows — Cumulative (USD Billion, per era) | ~$12B (2003-04) | ~$34B annual (2013-14) | ~$45B annual (2024) NDA era cumulative: ~$581B |
UPA era cumulative: ~$250B | NDA era cumulative: ~$581B | NDA Stronger | Verdict based on cumulative FDI equity inflows per era: NDA era attracted ~$581 billion vs UPA era ~$250 billion. NDA's annual FDI ranged $44-84 billion (FY15-FY22), peaking at $84B in FY21-22 (COVID-recovery surge + PLI announcements). UPA peak: $47B (FY08-09). Note: some of the NDA-era surge is global capital chasing emerging markets + Mauritius/Singapore route cleanup (higher transparency). Absolute inflows decisively higher under NDA. DPIIT FDI Statistics / RBI Annual Report |
L. Manufacturing & Industry — Section Score (5 metrics)
4
NDA ↑
0
UPA ↑
1
Mixed
M. Global Context — India vs G7 Baseline
Before declaring a winner between two Indian governments, the honest question is: how did the world do in the same period? Both eras faced global shocks — the 2008 Financial Crisis hit P1, COVID-19 hit P2. To compare fairly, you need to benchmark against what was happening globally, not just domestically.
Key insight: COVID-19 (2020) caused an average -6.4% GDP contraction across G7 economies. India's -6.6% was in line with the global shock — it was not a policy failure unique to India. Any comparison that treats 2020 as a P2 governance failure is misleading. Both the GFC (2008-09) and COVID (2020) were exogenous shocks. The right comparison is outperformance vs peers, not absolute growth rate.
GDP Growth Rate Comparison — India vs G7 (avg annual real %)
| Economy | P1: 2005–14 Avg Growth (%) | Global Shock in P1 (2009, GFC) | P2: 2014–24 Avg Growth (%) | Global Shock in P2 (2020, COVID) | India Outperformance vs this economy (P1) | India Outperformance vs this economy (P2) | Notes & Source |
|---|---|---|---|---|---|---|---|
| 🇺🇸 USA | 1.9% | −2.5% | 2.3% | −3.4% | +6.0pp | +3.5pp (+4.9pp ex-COVID) | World Bank |
| 🇬🇧 UK | 1.1% | −4.2% | 0.9% | −11.0% | +6.8pp | +4.9pp (+6.3pp ex-COVID) | World Bank |
| 🇩🇪 Germany | 1.4% | −5.6% | 0.6% | −4.6% | +6.5pp | +5.2pp (+6.6pp ex-COVID) | World Bank |
| 🇫🇷 France | 0.9% | −2.9% | 0.8% | −8.0% | +7.0pp | +5.0pp (+6.4pp ex-COVID) | World Bank |
| 🇯🇵 Japan | 0.4% | −5.4% | 0.3% | −4.3% | +7.5pp | +5.5pp (+6.9pp ex-COVID) | World Bank |
| 🇨🇦 Canada | 1.9% | −2.9% | 1.8% | −5.3% | +6.0pp | +4.0pp (+5.4pp ex-COVID) | World Bank |
| 🇮🇹 Italy | −0.3% | −5.5% | 0.5% | −9.0% | +8.2pp | +5.3pp (+6.7pp ex-COVID) | World Bank |
| G7 Average | ~1.1% | ~−4.1% | ~1.0% | ~−6.4% | — | — | Simple average across 7 economies |
| 🇮🇳 India (UPA → NDA) | 7.9% | +6.7% (2009 — resilient) | 5.8% (7.2% ex-COVID) | −6.6% (in line with G7 avg) | +6.8pp vs G7 avg | +4.8pp vs G7 avg (+6.2pp ex-COVID) | World Bank / IMF WEO |
What this table tells us
Both eras massively outperformed the developed world. India's P1 outperformed G7 average by +6.8pp per year; P2 outperformed by +4.8pp (or +6.2pp excluding the COVID year that hit every major economy at roughly the same magnitude). Neither era was riding global tailwinds — G7 economies were largely stagnant in both periods.
The COVID comparison is crucial. India contracted -6.6% in 2020. The G7 average was -6.4%. The UK fell -11%, France -8%, Italy -9%. India's COVID response, measured purely by economic contraction, was comparable to the global peer group — not a unique underperformance. Penalising P2 for COVID without the same lens on P1 for the 2008 GFC is asymmetric analysis.
On growth rate, the comparison is genuinely Mixed. Headline: P1 7.9% vs P2 5.9% (incl. COVID) or 7.1% ex-COVID. Ex-COVID, the gap is ~0.8pp — within noise. The headline tilts to P1 only when you don't adjust for: (a) a much smaller base ($618B vs $2T — growing the smaller economy 7.9% is mechanically easier), (b) post-2003 EM tailwinds (commodity supercycle, pre-GFC capital abundance), and (c) the fact that P2 absorbed three structural shocks (demonetisation, GST transition, COVID) where P1 absorbed one (2008 GFC, milder in impact). A clean "X stronger" verdict over-reads the data; absolute output added is captured in metrics #1 and #2 (both NDA).
What the Data Says
Where NDA was clearly stronger: Infrastructure acceleration (road km/day, solar energy, airports, metro cities), digital public goods (UPI, Jan Dhan, Aadhaar utilization), welfare coverage (Ujjwala, Swachh Bharat, Jal Jeevan, Ayushman Bharat), formalization (tax filers, DBT), LWE decline, defence indigenization, inflation control, and road safety per vehicle. These are genuine and measurable improvements.
Where UPA was stronger: Average GDP growth rate (higher), poverty reduction speed (steeper absolute decline), mobile subscriber growth (the mobile revolution decade), FDI growth rate, university expansion, child stunting reduction, and wind energy. The UPA era also launched the foundational infrastructure for digital India — Aadhaar, MGNREGA, RTI, NREGA — that the NDA era leveraged.
Where things genuinely declined under NDA: Press freedom (rank fell from 140 to 159), democracy index (downgraded to hybrid regime), real rural wages (stagnated), Global Hunger Index rank (111 vs 55), fiscal deficit (wider), child wasting (barely improved), and RTI institutional strength. On income inequality: India's income Gini (World Bank) has actually marginally improved and India ranks among the world's most equal by income — but wealth inequality rose sharply, driven largely by global asset price inflation rather than policy alone. These are real tensions that deserve honest accounting.
The honest verdict across 140 data points: NDA won on infrastructure, transport, digital public goods, health outcomes, innovation, security, space, manufacturing output, defence exports, and bottom-of-pyramid living standards (LPG, electricity, bank accounts) — 79 data points. UPA won on raw GDP growth rate, corruption score improvement, FTA count, governance quality metrics, early poverty reduction, child nutrition reduction, women's representation pace, and manufacturing share of GDP — 25 data points. 12 metrics genuinely declined under NDA. 24 were roughly equal. NDA built on the institutional and infrastructure base that UPA constructed; both eras are chapters in the same India story.
The base effect caveat is real but cuts both ways. Critics of the 2005–14 era correctly note that India grew fast partly from a low base. But critics of the 2014–24 era make the same mistake in reverse — crediting policy when improved global conditions, cheap smartphones (a private sector led disruption: Jio), and UPA-era foundations (Aadhaar, MGNREGA, NITI) did much of the heavy lifting.
No single metric captures what it feels like to live in India. These 140 data points are a starting point, not a verdict.
Data notes: All data points are sourced from publicly available government and international databases. Where government data and independent sources differ significantly, both are cited. For metrics not available at exactly 2005/2014/2024, the closest available year is used. Growth rates are approximate and rounded. This analysis is independent — no data point has been selectively included to favor either political position. Errors or updates: contact me.