The Impact Chain · Interactive model

1. What this means — for a household, at scale, and for the system

The framework's output is three lenses on the same investment. What it means for one household — the averages: cost, income gained, schooling, resilience. What it means at scale — the cohort totals: people reached, jobs created, dropouts prevented, mobility. What it means for the system — the platform leverage: government spend made more effective, total economic activity, return per $1 catalytic. Every number updates as you change inputs in Section 2 below.

①FOR ONE HOUSEHOLD Rita and households like hers, average across the reached cohort

Income gained per HH

$221

5-yr catalytic-attributable, avg across all reached HHs

Catalytic cost per HH

$1.96

one-time · pure arithmetic, no model assumptions

HH moving up ≥ 1 income tier

40%

probability for a HH reached by catalytic intensification

Extra child-years of schooling per HH

0.23

avg across all reached HHs — depends on Δα and decision-point share

Probability HH gains shock capacity

40%

moves from no buffer to 3-6 mo savings

②AT SCALE Cohort totals across all reached households

People reached

30.6M

direct: 600K · via platform: 30.0M

Durable jobs created (5-yr)

3.0M

growth-stage hires × yr-3 survival × induced multiplier

People lifted ≥ 1 income tier

0.9M

catalytic-attributable mobility, above NRLM-only baseline

Dropouts prevented

0.5M

children kept in school who would have dropped out

HH gaining first-time formal credit

4.4M

Findex baseline 11%; integrated programmes lift +25-40pp

③FOR THE SYSTEM What catalytic capital does to the platform

Platform spend made more effective (5-yr)

$3.4B

of $13.6B cohort-aligned 5-yr spend the catalytic layer touches

Per $1 catalytic → platform leverage

$57

of govt platform spend made more effective

Total economic activity (5-yr)

$17.1B

HH income + worker wages flowing through local economy

Per $1 catalytic → total economic

$285

of total economic activity per $1 of catalytic outlay

Per $1 catalytic → HH income

$113

catalytic-attributable HH income per $1 (above counterfactual)

④ The impact chain · in dollars per household

The same catalytic dollar moves through five steps. These are per-household figures — what each step looks like for one household in the reached cohort.

①

$1.96

Catalytic per HH

②

$111

Platform per HH

③

$337

HH income per HH
($221 attributable)

④

$221

Worker wages per HH

⑤

$558

Total econ per HH

Bottom line. Every $1 of catalytic philanthropy on India's integrated rural livelihoods platform makes approximately $57 of cohort-aligned platform spend more effective, reaches $172 of total household income (of which $113 is catalytic-attributable above the platform baseline), and generates $285 of total economic activity when worker wages are included. At 30.6M people reached, that means each household sees approximately $221 of catalytic-attributable income over 5 years.

Bottom line — platform off. With no integrated public platform to ride on, the catalytic dollar reaches 600K people through direct programming only. Per $1 catalytic, that produces approximately $8 of catalytic-attributable household income and approximately $14 of total economic activity over five years. Platform leverage is zero. The counterfactual baseline drops to 3% (secular rural-income trend). The chain still runs — through a narrower path, and at a fraction of the reach.

[INPUTS]

2. Inputs — every variable, with method and source

Edit anything in this section and the outputs in Section 3 update accordingly.

Each input below is editable. The documentation panel beside it explains the method, the calculation, the source, and the time horizon. Soft-yellow background means it is an input you can move; computed quantities are shown later in the Outputs section.

2A. Public livelihoods platform — on / off

Platform context

Platform on

What it is: Whether the catalytic dollar sits on top of an integrated public livelihoods platform (NRLM and equivalents) that does most of the actual reaching, or operates in a context where no such platform is available.
What changes when you switch it off: Indirect reach via system improvements goes to zero. Total reach drops to direct-only. Platform-leverage outputs go to zero. The counterfactual baseline drops from 12.5% (what NRLM-alone delivers) to 3% (secular rural-income trend in low-income contexts without integrated programme support). The catalytic dollar still produces real returns through direct programming — but at a fraction of the scale, and through a narrower chain.
When to use it off: For contexts without an integrated public livelihoods platform (most low-income countries). Also as a stress test — for any reader who thinks the platform-on leverage is too high, the platform-off mode shows what the catalytic dollar can produce on its own.

2B. Catalytic investment

Investment per year

$20M

$M/yr

What it is: Annual catalytic philanthropic outlay sustained over the investment cycle.
Time horizon: annual flow ($M/yr) Sustained for the number of years set in the next input.
Default rationale: $20M/yr × 3 years = $60M total. The slider now runs from $0.1M/yr (a small philanthropic experiment) to $200M/yr (a substantial multi-year commitment). The default sits at a credible mid-range catalytic intensification — large enough to fund pilots, evidence generation, playbooks, and system convergence work; small enough to be plausible as a single foundation's commitment.

Investment cycle

years

What it is: How many years the catalytic investment is sustained. The investment cycle ends in year 3 by default; outcomes are then measured over a 5-year horizon (years 1-5).
Time horizon: years (integer)
Default rationale: A 3-year investment cycle is typical for catalytic intensification work — long enough for evidence to compound, short enough to be operationally manageable.

2C. Direct and indirect reach engine

Share to direct programming

25%

% of budget

What it is: The share of the catalytic budget that goes to direct, multi-touch programming with the cohort. The remainder funds platform improvements that produce indirect reach.
Time horizon: % allocation (one-time)
Method: The 25/75 default reflects the empirical pattern in catalytic intensification: a small fraction goes to direct demonstration, the bulk goes to evidence, playbooks, MIS, and convening that work through the platform.

Cost per DIRECT person reached

$25

$ per person (one-time)

What it is: The amount the catalytic intervention spends to reach one directly engaged participant — pilot participant, new FPO member, household whose loan was restructured under a new design.
Time horizon: $ one-time per person
Source: Anchored to NRETP-IFC implementation cost ($18-24/HH) and BRAC graduation-lite multi-touch programmes ($30-50/HH). The default sits in the middle.

Cost per INDIRECT person reached

$1.50

$ per person (one-time)

What it is: The amount the catalytic intervention spends per person reached through platform improvements rather than direct intensification — better-targeted cadres, redesigned products, system convergence work that ripples to the household.
Time horizon: $ one-time per person
Source: Anchored to DAY-NRLM at-scale unit cost: Rs 15,047 crore for 100.5M women ≈ Rs 15/woman/yr ≈ $0.18/yr. Scaled up to ~$1.50/person to reflect catalytic load on top of recurring platform cost.

Indirect impact intensity

40%

% of full per-person value

What it is: The fraction of full per-person catalytic value received by an indirectly-reached person. They get platform improvements but not the bespoke intensification, so they get less than a directly-reached person.
Time horizon: % intensity (dimensionless)
Source: This is the most weakly evidenced parameter in the model. The 40% default sits in a defensible range (25-55%). Set to 25% for a conservative view; 55% for an optimistic one. Make it 0% and only direct reach counts (about 5% of the headline). Make it 100% and indirect reach is treated as fully equivalent to direct — which is the v0.5 behaviour and arguably too generous.

2D. Cohort stratification & counterfactual

Counterfactual α_no (without-catalytic lift)

12.5%

% income lift over 5 yrs

What it is: What the existing public platform delivers to the same cohort in household income lift over 5 years without any catalytic layer. The primary attribution baseline.
Time horizon: % lift, 5-yr cumulative
Source: Anchored to two NRLM evaluations: 3ie's 2018 study (+19% short-term income lift from baseline SHG participation) and 3ie's 2024 Model CLF evaluation (+12% sustained over the medium term). Midpoint adjusted to 12.5% for cohort effects.
Stress test: Drag this slider up to ~36% (the with-catalytic blended lift). Catalytic-attributable income collapses to zero. The framework is built to be falsifiable.

Tier A — Growth-stage entrepreneurs

17.5%

share of cohort · lift: 67.5%

Who they are: Women already running a business (average 7 years operating per LEAD Krea), looking for growth capital and market access.
Lift: ~68% income lift over 5 years. Range 60-75%.
Time horizon: 5-yr cumulative lift
Source: Kochar 2024 (3ie NRETP-IFC evaluation in Maharashtra) found +27.12% per-capita HH consumption uplift in high-NRETP markets (double-robust DiD, p<0.05). LEAD Krea micro-enterprise studies show consistent multi-year sustained growth.

Tier B — Scaling smallholders

46%

share of cohort · lift: 37.5%

Who they are: Combining farm income with processing, dairy, market linkage. Have a livelihood; intensification helps them scale.
Lift: ~38% income lift over 5 years. Range 30-45%.
Source: 3ie NRLM 2018 (+19% short-term income lift); 3ie Model CLF 2024 (+12% medium-term lift). Mid-point 37.5%.

Tier C — Subsistence to stable livelihoods

36.5%

share of cohort · lift: 20%

Who they are: Subsistence farmers moving toward stable livelihoods through risk protection, scheme convergence, and early enterprise activity.
Lift: ~20% income lift over 5 years. Range 15-25%.
Source: 3ie 2018 baseline cells (no-treatment counterfactual + modest platform participation). This tier is hardest to lift; the catalytic intensification's contribution here is more about resilience than acceleration.

2E. Baseline & inflation

Baseline HH income (I₀)

$900

$ per household per year

What it is: The average household income of the cohort before any intervention.
Time horizon: $ per HH per year (annual)
Source: PLFS 2023-24 rural household average; ~Rs 75,000/yr converted to USD at market rates.

Income persistence factor (Σφ_I)

2.5

cumulative multiplier, 5-yr

What it is: The cumulative multiplier on the steady-state annual income lift, summed across years 1-5 with a ramp.
Time horizon: 5-yr cumulative (dimensionless)
Method: Built from a year-by-year ramp: Year 1 = 30% of full lift, Year 2 = 50%, Year 3 = 60%, Year 4 = 65%, Year 5 = 70%. Sum = 2.75; rounded down to 2.5 to stay conservative.
Source: de Mel, McKenzie & Woodruff (2012, Science) — 5-yr sustained profits from one-time grants. Field, Pande et al. (2013, AER) — profits nearly double at year 3 with flexible repayment.

Inflation rate (i)

% per year

What it is: Annual inflation rate applied to multi-year flows when adjusting nominal USD to real (today's USD).
Time horizon: % per year
Method: When > 0%, the model applies a midpoint discount factor over the 5-year window: factor = (1 − (1+i)^−n) / (i × n). At 5% × 5 yrs ≈ 0.87.
Default rationale: 0% by default — all outputs are nominal USD. Suggested India: 4-6% if you want to see real (today's USD) figures.

2F. Platform leverage

Cohort-aligned platform spend (5-yr cumulative)

$13.6B

$B over 5 years (cohort-aligned)

What it is: Total cohort-aligned non-credit public platform spend over 5 years (the field the catalytic dollar operates on). At defaults: NRLM + state SRLM ($9B) + MGNREGS asset/convergence cohort share ($2B) + PMFBY+PMKSY ($0.6B) + livestock/AHIDF ($0.6B) + MoMSME+skills ($1.4B) = $13.6B over 5-yr cohort-aligned.
Time horizon: $B over 5 years (cohort-aligned, not full national budget)
Source: DAY-NRLM programme component ~₹14,400 cr/yr × 5 yrs ($9B cohort-aligned); MGNREGS ₹86K cr/yr × 12% asset share × 30% cohort share × 5 yrs ($2B); other lines from Union Budget cohort-aligned shares. Matches integrated Theory-of-Action methodology.
Important note: This is cohort-aligned spend, not full national budgets. The full PM-KISAN program is ~$11B/yr but only a small fraction reaches the integrated cohort; we count only that share. Credit volume (~$20B+/yr through SHG-BLP, MUDRA, MoMSME) is excluded — credit is enabled volume, not platform cost.

Note: the previous version of this model used annual platform spend with an effectiveness-gain parameter (η). The current version uses cohort-aligned 5-yr cumulative spend scaled by catalytic intensity — a cleaner formulation that matches the integrated Theory-of-Action approach and avoids confusing apples-to-oranges ratios. Both produce similar headline numbers, but the new framing is honest about what the catalytic layer is doing to the platform.

[OUTPUTS]

3. Outputs — what the model produces, with formulas and dependencies

Read-only. Every figure here computes from the inputs in Section 2.

Each output below is computed in real time from the inputs above. The documentation panel beside each shows the formula, the assumption chain, and the time horizon. These are the catalytic-attributable returns on top of the platform productivity shown in Section 1.

Catalytic-attributable HH income

$6.8B

5-year cumulative · today's USD

Method: Income that flows to the cohort that would not exist without the catalytic layer. The primary attribution headline.
Formula: (α_w − α_no) × I₀ × Σφ_I × equivalent reach × inflation factor
Depends on: Cohort tier mix and tier-specific lifts (drive α_w). Counterfactual α_no. Baseline income I₀. Persistence factor. Direct + indirect reach × indirect intensity (equivalent reach). Inflation toggle.
Time horizon: 5-yr cumulative Set the horizon to 10 years on Sheet 8 of the workbook for a longer view.
Stress test: Set α_no = α_w (counterfactual = with-catalytic lift). This figure returns to $0. The catalytic case has to be defended.

Total HH income with catalytic

$10.3B

5-yr cumulative · platform + catalytic combined

Method: What the cohort earns over 5 years with the catalytic layer on top of the platform.
Formula: α_w × I₀ × Σφ_I × equivalent reach × inflation factor
Counterfactual baseline: $3.5B — what the same cohort would earn over 5 years from the platform alone, without any catalytic intensification.
Time horizon: 5-yr cumulative

Platform spend made more effective

$3.4B

5-yr cumulative

Method: How much of the existing non-credit public platform spend is made more effective per year by the catalytic work, summed across 5 years.
Formula: Cohort-aligned platform spend (5-yr) × catalytic intensity
Depends on: $13.6B of cohort-aligned platform spend over 5 yrs (NRLM + MGNREGS cohort + livestock + risk + skills) × catalytic intensity scale (current ÷ $80M/yr full design).
Time horizon: 5-yr cumulative (η is an annual rate applied to annual platform spend over 5 years)

Return per $1 catalytic — HH income

$113

5-yr cumulative

Method: Catalytic-attributable HH income per $1 of catalytic outlay over 5 years.
Formula: Catalytic-attributable HH income (5-yr) ÷ Total catalytic outlay
Important framing: This high leverage is possible because the catalytic dollar sits on a productive platform. Strip the platform away and the same catalytic dollar produces a fraction of this return.
Time horizon: 5-yr cumulative

Return per $1 catalytic — platform spend made more effective

$57

5-yr cumulative · additional effective public delivery per $1 catalytic

Method: Platform spend made more effective per $1 of catalytic outlay over 5 years. Step 2 of the impact chain.
Formula: Platform spend made more effective (5-yr) ÷ Total catalytic outlay
Why this is different from the income figure: This measures the public-delivery effectiveness gain, not the household income gain. Both flow from the same catalytic dollar via different mechanisms. They should not be added together.

Durable jobs created

3.0M

Surviving year 3 · induced multiplier included

Method: Hired-worker jobs created by Tier-A growth-stage entrepreneurs across the equivalent-impact reach.
Formula: share_A × equivalent reach × 1.5 workers/enterprise × 0.70 (year-3 survival) × 1.3 (induced multiplier)
Source: Bain & Company 2024 ('Powering the Economy with Her' — 1.5 workers per women-led growth-stage enterprise); de Mel/McKenzie/Woodruff 2012 (70% job survival to year 3); ILO and UNDP informal sector studies (1.3× induced employment multiplier, capped at 2×).
Time horizon: jobs at year 3 (durability check)

Per directly-reached person — value

$1,315

5-yr cumulative · indirect-reached: $526

Method: Sum of four streams of catalytic-attributable value per directly-reached person, over 5 years: income lift, hired-worker wages, education PV, health resilience.
Formula: (Δα × I₀ × Σφ_I) + (s_A × w_e × wage × 12 × φ_3 × m × Σφ_J) + (2 × β × I₀ × Δα × r × PV) + (π × s × Δγ × n)
Direct vs indirect: The indirect-reached value is the same per-person figure × indirect impact intensity (40% default).
Time horizon: 5-yr cumulative per person Education stream is 30-year PV.

Reach diagnostics

30.6M

Total people · equiv-impact: 12.6M · cost/person: $1.96

Total reach: (I_tot × share_direct × 1M) ÷ cost_direct + (I_tot × (1−share_direct) × 1M) ÷ cost_indirect
Equivalent-impact reach: direct + indirect_intensity × indirect — the figure used for income and value calculations.
Cost per person (blended): Total catalytic outlay ÷ total reach — pure arithmetic, unaffected by any model assumption.
Direct reach: ≈ 600K people
Indirect reach: ≈ 30M people

⚠ Stress test built in

Drag the counterfactual α_no slider (Section 2C) up to match the with-catalytic blended lift (~36%). Catalytic-attributable HH income returns to zero, and per-$1 income return collapses to zero. The cost-per-person figure ($1.96) is unaffected — it depends only on investment and reach, not on any attribution assumption.

4. Downstream consequences — what the income gain translates to

The catalytic-attributable income figure above is the framework's headline. These markers translate it into outcomes leaders care about: children kept in school, families resilient to shocks, first-time savers and borrowers, households building productive assets. Each marker has a sourced coefficient and updates in real time with every input change.

Additional child-years of schooling

7.2M

across cohort children at education decision points

Method: The number of additional years of schooling that flow from the catalytic-attributable income lift across the cohort's children at education decision points (typically Class 5-12 transition).
Formula: equiv reach × 2 children/HH × 70% at decision points × 0.85 yrs/50pp lift × (Δα ÷ 50%)
Source: Filmer & Pritchett 1999 (Population & Development Review) and 2001 (Demography) — bottom-to-top quintile gap in years of schooling is ~3.6 years across countries. One-quintile-equivalent income move adds 0.6-1.0 years (default 0.85).

Dropouts prevented

0.5M

children staying in school who would have dropped out

Method: Children kept in school who would otherwise have dropped out, computed from baseline dropout rate × income elasticity × Δα.
Formula: equiv reach × 2 × 0.70 × (0.14 baseline × 0.40 elasticity × Δα / 0.50)
Source: Bhalotra & Heady (2003, World Bank Economic Review) — income elasticity of dropout prevention 0.3-0.5; ASER + NSSO 75th round — rural dropout baseline ~14% at upper-primary/secondary transition.

HH able to absorb a major health shock

5.0M

moved from no buffer to 3-6 months savings

Method: Households that move from having no shock-absorbing capacity to having a 3-6 month savings buffer, sufficient to absorb a catastrophic out-of-pocket health event without selling productive assets.
Formula: equivalent reach × 40% (buffer-capacity rate)
Source: Selvaraj, Karan et al. 2018 (WHO Bulletin) — 18.2% of rural HHs experienced catastrophic OOP in 2011-12, rising to 24.9% by 2014. SHG/CLF savings cycle data + NCAER-CMIE on rural HH financial buffers anchor the 40% rate. This is the most weakly evidenced parameter in the framework.

HH gaining first-time formal credit

4.4M

first formal credit relationship

Method: Households accessing formal credit (bank, NBFC-MFI, SHG-bank-linkage) for the first time, attributable to the catalytic layer.
Formula: equivalent reach × 35% (first-time-credit rate)
Source: World Bank Findex India 2021 — rural formal credit access baseline 11%. Integrated programmes typically lift this by 25-40pp in cohort.

HH building productive assets

3.8M

livestock, equipment, working capital — first time

Method: Households accumulating productive assets — livestock, equipment, working capital, producer-company shares — for the first time, attributable to the catalytic layer.
Formula: equivalent reach × 30% (first-time-asset rate)
Source: NCAER-CMIE rural household panel data on first-time productive asset transitions.

HH newly enrolled in health insurance

2.5M

PMJAY / state insurance scheme enrolment

Method: Households newly enrolled in PMJAY or state health insurance schemes through scheme-convergence work.
Formula: equivalent reach × 20pp (enrolment lift)
Source: NITI Aayog state-level data on PMJAY enrolment trajectories following integrated programme work.

Open model — move the sliders