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Building State Capacity: Evidence
from Biometric Smartcards in India
by Muraldiharan, Niehaus and Sukhtankar
Discussion pr...
Co-creating insights:
academics and policy-makers
• Context:
– Large-scale roll-out of the Smartcards Project in Andra Pra...
Gigantic encouragement design
296 mandals across 8 districts
Treatment
112
mandals
Buffer
139
mandals
Control
45
mandals
E...
(Preliminary) Results
• Authentication: reduces leakage and increases
actual payments to beneficiaries
• Benefits accrue t...
Comment 1:
Incentives matter
• Delegation to Bank-TSP pair with a 2% commission rule,
once 40% threshold has been reached....
Comment 2:
Measurement and evidence
• Payments and leakage (T3): Recall bias, robust (?),
no change in total outlay (quota...
Comment 3:
Heterogeneous treatment effects
• ITT = core focus
• But still, interesting to evaluate the treatment
effect fo...
Comment 4:
Full Cost-benefit Analysis
• Sunk costs left out of the analysis (consultancy,
haggling and negotation costs wi...
To conclude
• Thorough, systematic analysis with loads of
robustness checks
• Authors combine various data sources (offici...
What change does the Programme
bring about in ‘carded villages’
• Authentication:
– Direct: Changes who receives the payme...
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Comments on "Building State Capacity: Evidence from Biometric Smartcards in India"

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Comments by Marieke Huysentruyt on paper "Building State Capacity: Evidence from Biometric Smartcards in India" presented by Sandip Sukhtankar at the SITE Corruption Conference, 31 August 2015.

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Comments on "Building State Capacity: Evidence from Biometric Smartcards in India"

  1. 1. Building State Capacity: Evidence from Biometric Smartcards in India by Muraldiharan, Niehaus and Sukhtankar Discussion prepared by Marieke Huysentruyt Marieke.Huysentruyt@hhs.se SITE, Stockholm School of Economics September 1, 2015
  2. 2. Co-creating insights: academics and policy-makers • Context: – Large-scale roll-out of the Smartcards Project in Andra Pradesh for making payments in 2 large welfare programs: NREGS and SSP (2006 - ...) • Opportunity: – 8 (out of 21) laggard districts who need a “restart” (late 2009) – Phase-in roll-out and delegate rigorous evaluation to academics – Collect data at an unusually large scale • Caveat: – Learnings once implementation model was “stable” (See comment 5: cost-benefit analysis)
  3. 3. Gigantic encouragement design 296 mandals across 8 districts Treatment 112 mandals Buffer 139 mandals Control 45 mandals Excluded 2 mandals A bank-TSP team is encouraged to roll-out the Programme • They essentially team up and try to get people in the villages to adopt a Smartcard (biometric authentication + photo) • They decide which villages to target first • Adoption of Smartcard is voluntary: beneficiaries dedide still • In any village, they need to get at leat 40% onto the Programme before they get paid according to the 2% rule. • So long as they don’t meet this threshold, the implementation system doesn’t change (status quo) and so in below threshold villages, all efforts trying to get villages ‘carded’ are not valorized.
  4. 4. (Preliminary) Results • Authentication: reduces leakage and increases actual payments to beneficiaries • Benefits accrue to those with Smartcards only • Payment system: improves efficiency of payment delivery • Benefits accrue to all those in a ‘carded GP’
  5. 5. Comment 1: Incentives matter • Delegation to Bank-TSP pair with a 2% commission rule, once 40% threshold has been reached. – Saturation point: On average 46% of beneficiaries are carded • Out of remaining 54%: some are still being left vulnerable to the ‘whim’ of Field Assistants, etc. – Cream-skimming villages: Prioritize villages with the most work, chase the “most active NREGS worker” first • Most able? Vs. best connected? • In the long-run, Bank-TSP-CSP may want to push for lower caseload, more work allocated to less people. • Collusion between Field Assistants and Community Service Providers. • Norms and expectation for Field Assistants to find other ways to ramp up their salary.
  6. 6. Comment 2: Measurement and evidence • Payments and leakage (T3): Recall bias, robust (?), no change in total outlay (quota, budget?) • Channels (T4): Ghosts (no change?), ‘Bribe to collect’ (truthful?) • Beneficiary opinions about the Smartcards (T6): select group; in reality, there are many more with Smartcards who never used it (no work) • Bank type fixed effect?: Banks operating in more than 1 mandal
  7. 7. Comment 3: Heterogeneous treatment effects • ITT = core focus • But still, interesting to evaluate the treatment effect for different subgroups – Women versus men – Young versus old
  8. 8. Comment 4: Full Cost-benefit Analysis • Sunk costs left out of the analysis (consultancy, haggling and negotation costs with service providers) • People want to work more than what they are offered: opportunity cost of time? • Technology left idle? – Average per capita costs of smartcards relative to annual actual welfare benefit received.
  9. 9. To conclude • Thorough, systematic analysis with loads of robustness checks • Authors combine various data sources (official, own survey, audits ....) – Evidence on income, assets, household balance sheets, consumption ...  suggests more promising research is on its way! Thanks!
  10. 10. What change does the Programme bring about in ‘carded villages’ • Authentication: – Direct: Changes who receives the payment (Field Assistant, ghosts, quasi-ghosts, women and men, .... ) – Indirect: • Changes how much intended beneficiaries actually receive • Household decision-making • Payment system: – Direct: Changes the ease of accessing pay as you now have community service providers (strict profile) at village level, frequency of collecting pay, – Direct: Changes in bank inclusion - In some villages (where new bank, not Post Office): Payment linked to a new ‘no frills’ bank account – Indirect: More savings, type of purchases made with pay, etc.

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