Two stories, one model. Story 1: what catalytic investment produces per entrepreneur reached — income, jobs, education, health. Story 2: how catalytic investment makes India's $17.5B/yr government livelihoods capital reach more women more effectively. Every slider can be set to zero. Every assumption is sourced below.
At these settings, each entrepreneur earns 30% more within 18 months on a $1,000/yr base, creating 1 job at $70/month with 70% of those jobs surviving to year 3. Children benefit from 25% more education spend, compounding over 30 years. Gross value over 5 years: $5,533/person. Attributed at 20%: $1,107/person → 111× return on upstream catalytic investment.
| Parameter | Symbol | Base value | Source |
|---|---|---|---|
| Baseline income | I₀ | $1,000/yr | Field baseline; India informal enterprise surveys |
| Income uplift at 18 months | α | 30% | Programme observation; consistent with BRAC graduation and Jeevika evaluations |
| Income persistence — year 1–5 | Σφ_I | 3.90 yr-equiv | 1.00+0.85+0.75+0.68+0.62 — J-PAL graduation meta-analysis and PRADAN follow-up |
| Jobs per entrepreneur at 18M | ε | 1.0 | Programme observation |
| Job survival at year 3 | φ_J(3) | 70% | BRAC 68–74%; J-PAL 65–72%; ILO 70–75% — conservative mid-range |
| Job persistence — year 1–5 | Σφ_J | 3.69 yr-equiv | 1.00+0.82+0.70+0.62+0.55 — slightly lower than income; hired workers more exposed to downturns |
| Hired worker annual wage | w | $840/yr | $70/month — programme observation |
| Induced employment multiplier | m | 1.3× | World Bank informal/rural MSME benchmark — conservative vs formal sector 2× |
| Education spend uplift | β | 25% | Harvard CID / UNFPA: women spend 25–35% of income gains on education — lower end |
| School year earnings return | r | 11.7%/yr | World Bank, Montenegro & Patrinos (2014) |
| NPV discount rate | δ | 8% | Standard development finance — 30-year working life; annuity factor = 11.26 |
| Annual health shock probability | π | 18% | NITI Aayog catastrophic spending data |
| Average shock cost | s | $600 | MoHFW / NITI Aayog hospitalisation data |
| Buffer rate improvement | Δγ | 0.25 | 30% income gain moves household shock absorption from ~40% to ~65% |
| Programme horizon | T | 5 years | Evaluation design |
| Catalytic cost per participant | X/Y | variable | The slider sets the per-entrepreneur upstream catalytic cost. Default $10 reflects innovation evidence, operational protocols, DPI integrations. At $20M/yr and 25M women reached by 2030, the implied cost per woman is ~$4 (cumulative $100M ÷ 25M women). Adjust using the investment & reach sliders above. |
| Attribution coefficient | d_attr | 20% | Standard for upstream catalytic work — major foundations and FCDO use 15–25% |
| Income out-years: conservative persistence | Σφ_I (conservative) | 85% yr3, 75% yr4, 62% yr6 | J-PAL graduation programme meta-analysis persistence factors. In practice: income ~Rs 88,000–90,000 by year 5 vs Rs 97,500 peak, remaining permanently above baseline |
| Income out-years: realistic trajectory | Σφ_I (realistic) | Rs 1.4–1.8L by yr7, Rs 2–2.5L by yr10 | NRLM/JEEViKA programme data for women staying connected to SHG federation, enterprise credit, and FPO market linkage. Consistent with BRAC graduation long-run follow-up |
| System effectiveness gain | η | 7.5% | Conservative: targeting improvement on NRLM (~$500M impact from one tool), product design (Field & Pande, AER 2013), DPI integration (ULI: 60–80% underwriting cost reduction), market facilitation |
| Government & bank capital | G | $17.5B/yr | NRLM SHG-BLP ~$9–10B/yr (NABARD 2024); MUDRA Shishu+Kishor ~$8B/yr (PIB FY24); CGTMSE ~$3B/yr; state NRLM ~$2.4B/yr; bank MSME micro ~$3–4B/yr |
| Value multiplier (μ) | μ | Removed | Previously used to convert capital into downstream economic value (IFC MSME benchmark 6.5×). Removed for clarity — the system story now measures additional capital unlocked directly, without projecting what that capital then multiplies into. This is more defensible and easier to explain. |