Targeting, DBT, cash transfers and the UBI debate

Detail

1. Targeting vs universalism: the basic choice

• Targeting means giving a benefit only to people who pass a test, such as being BPL (Below Poverty Line) or owning land.
• Universalism means giving the benefit to everyone in a group, with no test.
• No targeting method is perfect. Every targeted scheme makes two kinds of mistakes, called targeting errors.

Exclusion error and inclusion error

• Exclusion error (Type I error in welfare): eligible poor people are left out.

• This is a welfare failure. The people who most need help do not get it.

• Inclusion error (leakage): people who are not poor still get the benefit.

• This is a fiscal waste. Public money goes to the wrong people.

• Formulas:

• Exclusion error rate = (eligible people left out ÷ all eligible people) × 100

• Inclusion error rate = (ineligible people included ÷ all beneficiaries) × 100

• Worked example:

• A village has 100 poor and 100 non-poor households. A scheme picks 120 beneficiaries: 80 poor and 40 non-poor.
• Exclusion error = 20 ÷ 100 = 20%, because 20 poor households are left out.
• Inclusion error = 40 ÷ 120 = 33.3%, because a third of the beneficiaries are not poor.

The trade-off

• Tighter targeting (stricter tests, more paperwork):
• fewer rich people slip in, so inclusion error falls;

• but more poor people fail the test or cannot produce documents, so exclusion error rises.

• Universal schemes do the reverse:

• exclusion error is close to zero;

• inclusion error is high, and so is the fiscal cost.

• Middle path: "universal minus" means everyone gets the benefit except a clearly rich group. The UBI proposal of 2016-17 uses this idea (see section 5).

2. Poverty estimation ≠ BPL identification

The two are often confused. Examiners like to test the difference.

	Estimation	Identification
Question answered	How many people are poor?	Which households are poor?
Who does it	Planning Commission (now NITI Aayog)	State governments, with guidelines from the Ministry of Rural Development (MoRD)
Data used	NSS sample surveys of consumer spending	Census-style surveys of every household
Output	Poverty ratio (for example, the Tendulkar ratio)	Named BPL lists and ration cards

• Why they don't match: the estimate gives a total, called a state "cap". The list is built with different indicators. So the number of names on the list can be larger or smaller than the estimate.
• BPL censuses: held in 1992, 1997 and 2002.
• The 1992 and 1997 rounds mostly used income or spending cut-offs.

• The 2002 round scored households on several parameters.

• N.C. Saxena Committee (2009): reviewed how the BPL census was done.

• It pushed for automatic inclusion of the poorest groups.

• It pushed for automatic exclusion of clearly well-off households.

• SECC 2011 (Socio-Economic and Caste Census, run by MoRD):

• Step 1, automatic exclusion filters: households with certain assets or incomes are left out at once.
• Step 2, automatic inclusion filters: the most destitute households are put in at once.
• Step 3: all other households are ranked on seven deprivation indicators (D1–D7).
• Used today for: PMAY-G (rural housing) and PM-JAY (Ayushman Bharat health insurance).

3. Direct Benefit Transfer (DBT)

• Definition: DBT means the government pays a subsidy or benefit straight into the beneficiary's bank account. It does not go through officials, dealers or middlemen.
• Launched: 1 January 2013.
• JAM trinity (set out in the Economic Survey 2014-15) is the base DBT runs on:
• J – Jan Dhan: bank accounts, so money has somewhere to go;
• A – Aadhaar: a unique biometric ID, so each person is counted once;

• M – Mobile: phones for alerts and mobile banking.

• PAHAL (DBTL): LPG subsidy paid through DBT. It was an early flagship.

• The consumer buys the cylinder at market price.
• The subsidy then goes into their bank account.

How DBT reduces leakage

• Aadhaar seeding cleans the lists:
• it removes ghost beneficiaries (people who don't exist);
• it removes duplicate beneficiaries (the same person listed twice);

• so money stops going to fake names.

• Electronic payment removes middlemen:

• no official handles the cash;
• so there are fewer cuts and bribes, and less delay.

Official savings claims (verify current figure: NCERT scaffold)

• Cumulative savings of ₹3.48 lakh crore from plugging leakages. This comes from an assessment by the BlueKraft Digital Foundation, covering data from 2009 to 2024, and was released by PIB (Ministry of Finance) on 21 April 2025 [2].

• Note: this is a study by an outside foundation that the government quotes, not an audited CAG figure.

• Subsidies as a share of total government spending: fell from an average of 16% (2009–2013), about ₹2.1 lakh crore a year, to 9% (2023-24) [2].

• Beneficiary coverage: rose about 16 times, from 11 crore to 176 crore (2014–2024) [2].
• Savings by sector [2]:

Sector	Saving	How it was saved
Food subsidy (PDS)	₹1.85 lakh crore (53% of total savings)	Aadhaar-linked ration card checks
MGNREGS	₹42,534 crore; 98% of wages paid on time	Payments linked to verified accounts
PM-KISAN	₹22,106 crore	2.1 crore ineligible beneficiaries removed
Fertiliser	₹18,699.8 crore	Sales cut by 158 lakh tonnes through targeted supply

• Welfare Efficiency Index (WEI): a composite score built in the same study [2].
• Weights: DBT savings 50%, subsidy reduction 30%, beneficiary growth 20%.

• Movement: rose from 0.32 (2014) to 0.91 (2023).

• Shock-time use: during the COVID-19 lockdown (2020), more than ₹36,659 crore reached the bank accounts of 16.01 crore beneficiaries through DBT, using PFMS (Public Financial Management System) [6].

• Limits of DBT:
• Aadhaar authentication failures: fingerprints may not match, especially for old people and manual labourers. This can cause exclusion errors.
• Last-mile problems: bank branches or banking correspondents may be far away.

• Inflation: cash does not rise with prices unless the amount is revised. In-kind grain keeps its value.

• Payment rails (NPCI, APBS, UPI): see payment-systems-digital-finance.

4. Cash transfers: conditional and unconditional

Conditional cash transfers (CCTs)

• Definition: a conditional cash transfer is cash paid to poor households only if they follow a stated behaviour, such as sending children to school or going for health check-ups.
• Aim: to build human capital, meaning people's health, skills and education, which raise their future earnings.
• Logic:
• the condition changes today's behaviour (the child stays in school);
• the child earns more as an adult;
• so poverty does not pass to the next generation.

Scheme	Country / year	Condition or purpose
Progresa / Oportunidades	Mexico, 1997	School attendance, health visits
Bolsa Família	Brazil, 2003	Schooling, vaccination
Janani Suraksha Yojana (JSY)	India, 2005	Institutional delivery (giving birth in a hospital or clinic)
PMMVY (Pradhan Mantri Matru Vandana Yojana)	India, 2017	₹5,000 for pregnant and lactating women
Ladli Laxmi	Madhya Pradesh, 2007	Girl child's education
Kanyashree	West Bengal, 2013	Girls staying in school and marrying later; UN Public Service Award 2017

• Criticism of CCTs:
• checking conditions costs money;
• the poorest may fail the conditions because schools or clinics are missing, not because they don't care;
• so conditions can cause exclusion.

Unconditional cash transfers (UCTs)

• Definition: cash is paid without any behaviour condition. Being eligible (land, gender, income) is enough.
• PM-KISAN (2019): ₹6,000 a year to landholding farmer families, paid in three instalments.

• Limitation: tenant farmers and landless labourers are left out, because the test is land ownership. This is a built-in exclusion error.

• State cash support for women: for example Ladli Behna (Madhya Pradesh) and Ladki Bahin (Maharashtra). These are monthly transfers to adult women that meet only an eligibility test.

The "freebies vs welfare" debate

• The question: where does useful welfare end and a pre-poll "freebie" begin?
• Welfare / merit goods: spending on health, education, nutrition and the PDS builds capability and has long-term returns.

• Freebies: free goods or cash with no clear long-term return, often announced near elections.

• Supreme Court: heard the issue in the Ashwini Upadhyay case, a petition against poll-time promises of freebies.

• RBI: its state-finance reports have warned that these schemes put pressure on state budgets.
• The RBI Bulletin (June 2022), "State Finances: A Risk Analysis", added up cash transfers, utility subsidies, loan and fee waivers and interest-free loans announced in state budgets. It estimated spending on freebies at 0.1% to 2.7% of GSDP, depending on the state [4].

• GSDP (Gross State Domestic Product) is the total value of goods and services produced in a state in a year.

• Why it matters:

• more spending on freebies means less money for capital spending (roads, schools, irrigation);
• it also means more borrowing and higher interest bills;
• so the state grows more slowly over time.

5. Universal Basic Income (UBI): Economic Survey 2016-17

• Source: Chapter 9 of the Economic Survey 2016-17 (Vol. I), titled "Universal Basic Income: A Conversation With and Within the Mahatma" [5].
• Definition: UBI is a regular cash payment from the state to every individual. It is unconditional and needs no means test.

Three features (from the Survey)

• Universality: everyone gets it. No BPL list is needed, so exclusion error is low.
• Unconditionality: no behaviour is required. It differs from CCTs here.
• Agency: the poor are treated as able to decide for themselves how to spend the money. They are not treated as passive receivers of goods.

Why the Survey considered it: the misallocation problem

• The Survey studied the six largest Central Sector and Centrally Sponsored sub-schemes across districts.
• Finding: the districts with the greatest need are the ones where state capacity is weakest. So welfare money reaches the poorest districts least [3].
• Conclusion: giving resources directly through UBI can get around weak local administration [3].

Cost arithmetic

• ₹7,620 a year per person (2016-17 prices) would lift a person to the Tendulkar poverty line.
• "Universal minus": covering 75% of the population (the top 25% by income left out) would cost about 4.9% of GDP.

• PIB's summary of the Survey: a UBI that cuts poverty to 0.5% would cost 4–5% of GDP, assuming the top 25% do not take part [3].

• Worked check (rounded, for illustration only):

• Assume a population of about 130 crore. Then 75% ≈ 97.5 crore people.
• Cost ≈ 97.5 crore × ₹7,620 ≈ ₹7.4 lakh crore a year.

• With nominal GDP of about ₹150 lakh crore, cost ÷ GDP ≈ 4.9%. This matches the Survey.

• Two prerequisites named by the Survey [3]: 1. a working JAM system, so cash reaches each account directly; 2. Centre–State agreement on cost-sharing.

Precedents

• SEWA–UNICEF pilot, Madhya Pradesh (2011–13): unconditional monthly cash in selected villages.
• Sikkim: proposed a UBI.
• International trials: Finland and Kenya (unconditional cash experiments).

For and against

For	Against
Less leakage and fewer exclusion errors. No BPL list, so nobody is wrongly left out	High fiscal cost. About 4.9% of GDP (2016-17)
Respects autonomy and choice. The "agency" principle	Possible work disincentive (people may work less). Evidence for this is weak
Low administrative cost. No need to check conditions or eligibility	Inflation in thin local markets. In remote villages with few sellers, extra cash can push up prices
Insures against shocks. It protects people who fall into poverty for a short time after a flood, illness or job loss (transient poverty)	Replace or top up? If UBI is added on top of existing schemes, the cost explodes. Cutting the PDS or subsidies to pay for it is politically hard

• Transient poverty: poverty that lasts only for a while, for example after a crop failure. Chronic poverty lasts over long periods.
• Other practical risks:
• Gender control of cash: paying the male head of the house may cut women's say. Paying each individual avoids this.

• Food vs cash: where markets are weak, grain from the PDS may protect nutrition better than cash.

• Outcome: India has not adopted a national UBI.

• PM-KISAN and state schemes for women are targeted UCTs. They are sometimes called "quasi-UBI" (partly like a UBI).

Prelims Hooks

• Exclusion error = eligible poor left out (a welfare failure). Inclusion error = non-poor included (fiscal leakage). Tighter targeting cuts inclusion error but raises exclusion error.
• Poverty estimation is done by the Planning Commission/NITI Aayog from NSS samples. BPL identification is done by the states through household surveys.
• SECC 2011 was run by the Ministry of Rural Development. It uses automatic exclusion and inclusion filters plus 7 deprivation indicators. It is the beneficiary base for PMAY-G and PM-JAY.
• DBT was launched on 1 January 2013. JAM trinity comes from the Economic Survey 2014-15. PAHAL is the LPG subsidy DBT.
• DBT savings claim: ₹3.48 lakh crore (BlueKraft study, 2009–2024 data; PIB, April 2025). PDS gives the largest share (53%). Subsidy share of spending fell from 16% to 9% [2].
• Trap: JSY (2005) is a CCT for institutional delivery. PMMVY (2017) gives ₹5,000 to pregnant and lactating women. Kanyashree (West Bengal) won the UN Public Service Award 2017.
• Progresa is from Mexico (1997). Bolsa Família is from Brazil (2003). Don't swap them.
• UBI's three features in the Economic Survey 2016-17: universality, unconditionality, agency. Cost is about 4.9% of GDP at 75% coverage and ₹7,620 a year per person (Tendulkar line).
• The UBI chapter is Chapter 9 of ES 2016-17, "A Conversation With and Within the Mahatma" [5]. Its prerequisites are JAM + Centre–State cost-sharing [3].
• RBI (June 2022): state spending on freebies was estimated at 0.1–2.7% of GSDP [4].

Mains Points

• Targeting vs universalism (GS-II/III):
• India's welfare state trades exclusion error against inclusion error.
• SECC-style filters and Aadhaar-based DBT have cut leakage: ₹3.48 lakh crore claimed savings, and subsidy share down from 16% to 9% [2].
• But biometric failures and land-based eligibility (PM-KISAN leaves out tenants) create new exclusion.

• Best answer: the "universal minus" design plus grievance redress and offline fall-backs.

• Misallocation and state capacity:

• The Survey found that the neediest districts have the weakest administration [3].
• So direct cash through JAM can reach people that scheme machinery cannot.

• This links poverty policy to governance reform and cooperative federalism (Centre–State cost-sharing).

• Freebies vs welfare (fiscal federalism):

• Separate merit goods (health, education, nutrition) from untargeted poll-time transfers.
• RBI's estimate of 0.1–2.7% of GSDP [4] shows the pressure on capital spending and debt.

• Suggest fiscal-responsibility disclosure of the cost of each promise, not a ban on welfare.

• UBI as insurance vs cost:

• UBI protects against transient poverty and respects agency.
• But at about 4.9% of GDP it is only affordable if it replaces subsidies such as food, fertiliser and LPG, and that is politically hard.
• Targeted UCTs (PM-KISAN, women's cash schemes) and CCTs for human capital (JSY, PMMVY, Kanyashree) are the practical middle path.