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On the NIPFP Response-Reetika Khera
-Economic and Political Weekly

Before I take issue with some of the points made in the NIPFP response to this comment, it may be useful to recapitulate a few points on which there appears to be agreement: (1) Aadhaar-integration can resolve only certain types of leakages, for which reliable data is unavailable; this was not adequately accounted for in the cost-benefit exercise; (2) the NIPFP study has a fragile basis (in particular, the estimated “rate of return” on unique identification (UID) number builds on a whole series of ad hoc assumptions); (3) the study is conducted by a research group that receives funds from Unique Identification Authority of India (UIDAI), “without disclosure”.

In spite of these limitation, the conclusions (“50% rate of return”) were handsomely played up in the media, including a newspaper in which one of the principal authors is a consulting editor (see “Large Returns Expected from Aadhaar”, Indian Express, 10 November 2012). The main purpose of the comment was to draw attention to the details of the NIPFP study which, unfortunately, were swept aside in the public discusssion. Instead, the ad hoc assumptions were repeatedly termed “conservative” or “modest”.

On Benefits: Lack of Data

The NIPFP study and the response use “overall leakages” (total corruption due to, say, leakage at the state food depot, at the ration shop, due to duplicates, in the case of the public distribution system (PDS)) and “Aadhaar-relevant leakages” (i e, leakages that Aadhaar-integration can resolve, e g, duplication) interchangably. Using estimates of overall leakages has the effect of exaggerating the benefits of Aadhaar-integration, so the assumptions are not “conservative”.1 When estimates of Aadhaar-relevant leakages exist, the study and response admit, they are outdated.2

The NIPFP response states “The study has steered away from relying exclusively on analyses of isolated and small sample sets”. I would like to draw attention to the evidence that the NIPFP study relied on. For ASHAs, Janani Suraksha Yojana and scholarships, no analysis,large or small has been used. For the Indira Awaas Yojana, the three analyses relied on exclusively are a Times of India news report, a press release based on a discussion in Parliament and a “Scheme Brief” by the Institute for Financial Management and Research (IFMR). Interestingly, the corruption estimate in the IFMR brief cross-refers to the Times of India article (apart from a CAG report)! Similar issues arise with the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) data which generally relies on small, often single-state, samples drawn from one to three districts. An all India average of “overall leakages” (not Aadhaar-relevant leakages) relies on these small sample estimates. Nationally representative estimates of overall leakages using National Sample Survey Office data were published in 2011 (see Imbert and Papp 2011).

The fact remains that, at the moment, we do not have reliable estimates of “Aadhaar-relevant leakages” for most schemes. This is acknowledged in the NIPFP study and response.3 The lack of reliable information on these issues was the crux of the problem and the main point of my comment.

Other Issues

The NIPFP response claims that I am selective in citing PDS corruption data, even though they themselves extensively cite my estimates of PDS (overall) leakages published elsewhere. All of my estimation of corruption in several welfare schemes is in the public domain. Further, the low leakages in Chhattisgarh and Tamil Nadu were discussed in the context of the availability, and benefits, of alternate technologies (end-to-end computerisation, in this case, used in these two states).

The NIPFP response brushes aside the question of alternate technologies. But as they ascribe benefits that accrue from other technologies (e g, real time monitoring of the number of labourers requires computerisation and is possible without Aadhaar) to Aadhaar-integration, they have to take alternatives into account. Further, the NIPFP response states that the government had to undertake a cost-benefit analysis after the National Identification Authority of India Bill (NIDAI Bill) was rejected in totality by the relevant Standing Committee (on Finance). Apart from the oversight regarding the disclaimer on the “affiliation” between UIDAI and the Macro/Finance group of NIPFP, a larger question on the process of policymaking also arises.4

The authors’ proposal on material corruption in NREGA is without merit. They suggest controlling material corruption in NREGA by linking material costs with number of labourers. The share of material in total costs depends, not on the number of labourers (as they suggest), but on the nature of the project. Material costs per labourer are very high for wells, but close to zero for land-levelling. If, as NIPFP proposes, there should be a fixed ratio between labourers and material costs, then in the case of wells, their proposal will lead to collapsed wells and for land-levelling, it would open the door to material corruption.5

Even on the cost side, which I completely ignored earlier, there are problems. The NIPFP study budgets Rs 1,200/year for connectivity (Table 2, NIPFP study) for payments of each Aadhaar-enabled scheme. As each authentication is likely to cost Re 1, only 1,200 beneficiaries per gram panchayat are envisioned to be paid each year. This translates to 100 transactions each month – which is certainly too few for the PDS and NREGA.

In Conclusion

I agree with the NIPFP authors that the way forward is “careful analysis that is mindful of difficulties in available research”. When available research is fraught with problems acknowledged throughout the NIPFP study and response, the “path to rational policymaking” lies in doing the hard work, i e, undertaking more and larger studies to estimate Aadhaar-relevant leakages.

Notes

1 Here is an example: “Automating the maintenance of muster rolls, and carrying out authentication through Aadhaar, will help deal with corruption arising from embezzlement of funds on account of fake names and inflated days of work”. “Inflated days of work” is due to collusion which is not an Aadhaar-leakage. “Fake names” can either be non-existent persons with bank accounts operated by living persons (highly unlikely) or collusion (local officials collude with a worker to defraud the system without doing any work).

2 To apply a “discount” factor (to account for recent improvements), also requires some factual data which are not available.

3 For instance, in the NIPFP response they admit that “the study could not have relied on contemporary data for some of the assumptions, as leakage studies that are nationally representative do not exist”. (This also contradicts an earlier statement that they “steered away from relying exclusively on analyses of isolated and small sample sets”.)

4 I leave aside the minor issue of authorship (which the NIPFP response concedes) only by stating that every other publications of the group authorship has been clearly stated on their website.

5 Further, there are peaks and ebbs in material use for any work.

Reference

Imbert, Clement and John Papp (2011): “Estimating Leakages in India’s Employment Guarantee” in Reetika Khera (ed.), The Battle for Employment Guarantee (New Delhi: Oxford