Core2: Need for Equitable Distribution of Public Goods

(Reproduced as-is from

Among the many fallacies of the #IOI regime in India, the second most important issue that #TeamCore is concerned about is that of (un)equitable distribution of public goods and resources. In the #Core hierarchy, therefore, this issue is termed #Core2 (#Core1 refers to discrimination with regard to Educational Rights).

A crisp, and to the point, definition of #Core2 is given by @realitycheckind in his blog, which I reproduce below

Sectarian Purse: No 2 on Core Right is to preserve the secular nature of the public purse if you are to function as a coherent whole. The issue oddly, is not that the state spends on minority only issues like Haj where only minorities have an interest but on public goods like scholarships, schools, public works (MSDP), loans, etc. Areas where everyone has aspirations and interest. This is not to take away minority scholarships but to absorb the part into the whole. The idea is to have common public goods and ensure equitable distribution within the program. Not to run separate programs.

In this post, I am attempting to elaborate a little more on why the current, favorite, method of distributing public goods is flawed, and why there is a pressing need to implement #Core2.

The nature of ‘Benefit Programs’

When any Government intends to distribute a public good, there are 3 high level attributes of the benefit program or ‘scheme’ that is devised.

  • Public good/resource
  • Beneficiaries
  • Distribution criteria & methodology

While there could be programs that could cater to a specific segment or class of people, such as say a program to perform eye surgeries for blind people, or say funding artificial limbs for those military personnel or police personnel who lost their legs on duty — the programs that are of concern to us in this post are those in which the goods being distributed are necessarily public — commonly applicable — in nature.

To borrow the words of @realitycheckind again

…. public goods like scholarships, schools, public works (MSDP), loans, etc. Areas where everyone has aspirations and interest.

So these goods are the ones which every individual citizen aspires for — resources which if one obtains — he or she can carve out a better future for oneself. The list includes scholarships, infrastructure like roads, highways, lighting, power, financial support for business, hospital facilities and so on. In a sense, all citizens have an equal Right over these public goods.

At the same time, one unfortunate reality of these public goods are that they are NOT infinite. In almost every society, scarcity of resources is an unavoidable reality. In fact, the fundamental business of an economy is to manage the scarcity of resources in the most efficient manner!

Given this reality of resources being scarce — two key questions open up when setting up a benefit scheme:

  • Who qualifies to benefit?
  • On what basis does one lose?

#IOI approach of distribution

In the #IOI approach, both the questions — who gets the benefit — and who doesn’t — get answered at the first stage of allocation of the resource itself. This mindset translates to creation of specific ‘schemes’ for targeted communities even if the resource is public in nature.

A higher level ‘identity’ — for e.g. religion, caste or gender — is typically used as the highest level filter in the #IOI approach. Let’s call this the ‘Identity Based Filter’.

So, for e.g, the Government of India can come with a scheme for ‘Post Matric Scholarships for Minority Students’. Even before the exact nature of the resource is identified, the beneficiary list gets finalised — only those students belonging to minority communities can get the scholarships — and all students who belong to the majority community stand disqualified.

I purposely say that the filtering of beneficiaries happens before the exact resource is identified because in the very same scheme, the nature of the goods being distributed can be varied and it will have no effect on who qualifies (or doesn’t qualify). Today the scholarships could be actual money being handed over to the students. Tomorrow the scheme can be changed to a ‘fee waiver’. We can then have a fee/books/uniform voucher system on the third day. Irrespective of the actual good, the beneficiaries are pre-decided.

A significant feature of the #IOI model is that the ‘Identity based filter’ has no connection, whatsoever, with the public-good being distributed!!

Let us say the Government comes up with a scheme to provide street lights in localities where at least 50% of residents are retired military personnel. It does not matter if you live in a poor locality where roads are in bad condition and completely unlit — you will not get the benefit if your locality does not have 50% military retirees — a factor completely unconnected with the need for the resource (street lights).

Once this high level filtering has been done, the scheme itself typically has several secondary ‘elimination filters’ which further decide who amongst the qualifying set of people actually get the resource. By its very nature, these ‘elimination filters’ are connected with the goods/resources. For e.g. in the same hypothetical ‘street light’ scheme, there could be further conditions imposed to determine who do not get the benefit — say those streets which have at least 4 lights already— or those streets in which at least half the households have UPS connections — and so on.

Thus in the IOI approach, the ‘Identity Based Filter’ is applied during allocation and the ‘Elimination Filter’ is applied during distribution.

#Core2 approach of distribution

In contrast with the #IOI approach — the two questions of who gets the resource — and who doesn’t — get answered only in the resource distribution stage of the scheme. Due to this, the programs constructed under this approach are by design ‘public schemes’.

For e.g. a ‘Post Matric Scholarship Scheme for All Students’. To start with, all students stand a chance to derive the benefit of this scheme.

In the #Core2 approach too, there are two types of ‘filtering’ that is possible. But it is inevitably the ‘Elimination Filters’ that are applied first. Some filters corresponding to the scholarship example.

  • Filter to identify the more needy — ‘All students who are in the Grade X or below do not qualify under this scheme’ — to ensure that the benefit is applicable to only post matric students
  • Filter to identify those who already have the resource — ‘All students whose parents’ income exceeds 3 lakh rupees per year’ — these students have an alternate source (own parents) for the equivalent amount.
  • Filter to identify repeat beneficiaries — ‘All students who already receive the benefit of another scholarship’ — to maximise the coverage of the beneficiaries
  • Filter to identify the undeserving — ‘All students who do not score 50% or more in their exams’

Depending upon the particular scheme — many such elimination filters could be devised — but even a cursory look shows that each filter is intricately connected with the resource being distributed.

Even in #Core2 an ‘Identity based filter’ could be used secondarily. But this filter will only work to ensure the resources are distributed ‘pro-rata’ amongst the beneficiaries. This filter will act as a limiting filter rather than an eliminating filter.

So for e.g. in the scholarships example, in order to ensure that children of all religions get a fair chance at the scholarship, there could be quotas for each religion, based on the overall population numbers.

Again, using the same street-light-scheme example, there could be a quota that states how many unlit roads need to be lit-up within each district of a given state.

Thus, in #Core2, three main approaches stand-out

  • Everyone who aspires for a resource has a chance to stake a claim
  • The eliminating factors are exercised first and all of them necessarily relate to the resource being distributed
  • A group or class identity could be used — but only as a limiting factor vis-a-vis other groups — and not as an eliminating factor

Contrast between #IOI and #Core2 approaches

Fairness: The very purpose of a ‘separate’ or ‘sectarian’ scheme is to show bias. It is to show favor to a particular group or class. The harvest expected could be electoral advantages, or even (unannounced) social transformation.

If a particular scheme does not carry any bias — for e.g — a separate scholarship scheme which gives the same amount as the general scheme and has a pro-rata budget — it is just a badly designed scheme! Or even worse, it is a scheme designed to fool the target community.

Hence a ‘normal’ #IOI scheme is inherently biased and discriminatory.

In contrast, the #Core2 scheme is naturally fair. The nature and unit of distribution of the resource HAS TO BE uniform for all beneficiaries. A general scheme in which a Hindu student will get twice the scholarship amount of a Christian student, for e.g, will simply not stand social or legal scrutiny. Hence fairness is automatically built-in.

Appeasement Opportunity: Sectarian schemes are very good instruments for appeasement of the target group. The budgetary requirements are much lesser than the general scheme — and the attention and scrutiny it is subject to — is far less. Further, since it is targeted at a particular group — it is natural for the beneficiary group to feel a sense of thankfulness towards those who devised the scheme.

If a sectarian scheme has a budget of say 200 crores and a general scheme of say 600 crores, it is far more easier to effect a 10% increase in the budget of the sectarian scheme as against a 10% hike in the general scheme budget. This coupled with the fact that the appeasement effect is higher, the chances of budget increases/relaxation of restrictions is much more likely in a sectarian scheme.

On the other hand, #Core2 schemes are that much more appeasement proof. Any additional benefit proposed to be added to the scheme will have to address all sections of the beneficiaries. The cost in terms of resource allocation and implementation is higher — which means there is bound to be more review and due-diligence. Naturally, this leads to better thought out changes to the scheme, and is therefore less prone to misuse (for appeasement).

Categorization: The big challenge in the #IOI approach is to determine the right ‘identity’ to create the sectarian schemes. Due to the complexity, and the amount of effort, involved in such exercises, only those identities which bring electoral advantages and/or hidden social transformation benefits are likely to be used. In India, this inevitably translates to religion, caste and gender based schemes.

There are many infrastructure schemes which have been launched in districts which have a minimum concentration of ‘minority religion’ citizens — programs like MSDP and sub-schemes under JNURM. However, the connect between religion and economic status is a very weak one.

Let us say, a survey was conducted amongst all construction labourers in urban India, it is very likely that a similar pattern with regard to economic status, lifestyle and access to infrastructure will emerge — irrespective of the religion of the labourer.

Or if a survey of less-educated migrant workers who are resident in a city for less than 5 years is conducted — their problems are likely to be similar to the ones that led to MSDP and other schemes — irrespective of their religion.

There is no end to the number and types of classification that can be done — to arrive at the same criteria — that will warrant a dedicated scheme. Hence creation of such schemes will ONLY be attempted when there is an electoral or hidden social transformation benefit.

#Core2 methodology has no such misuse potential.

Redistribution: In the #IOI approach, if there is a shortfall of beneficiaries under a particular category, the only way to still utilize the allocated resource is to relax the elimination criteria and grant the benefit to lesser deserving beneficiaries.

For e.g. if under our hypothetical street light scheme for military retirees, if the target was to cover 100 streets, each of which had less than 4 street lights already — but during execution it was determined that there are only 90 such streets — the remaining lights have to necessarily go to streets which have 4 or more street lights.

In contrast, the #Core2 approach tends itself to always favor the ‘most deserving’ beneficiaries. In the same example, if a particular district has fewer streets which pass the ‘less than 4 street lights’ criterion, the excess budget can simply be routed to another district where there are more such streets.

Resentment: Even if the beneficiaries of the generic and sectarian schemes are handed out the same type and amount of resource, the creation of a separate scheme is bound to cause huge resentment amongst those who fall under the general scheme.

Consider a mother who has two kids. She feeds one kid personally — holding the child on her lap — and spoon feeding it. On the other hand, she asks the second kid to help himself to a meal kept in the kitchen. Even though the same preparation is being consumed by both kids, it is a no-brainer that the second kid will resent such treatment, and in fact may develop hatred towards the sibling.

The #IOI approach is bound to cause social unrest in the long-run. Needless to say, the #Core2 approach, being fair and non-discriminatory, will lead to no such resentment.

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