I have blogged on the issue of deregulation as an organisational culture earlier. This post is an attempt to provide a framework for thinking about the bias within the Indian bureaucracy towards the prevention of inclusion errors and process abuse.
Two features of India’s bureaucracy are of relevance.
One, a welfare policy to support the needy and a promotional policy to incentivise something, comes filled with access barriers. Two, a regulatory policy to permit or regulate something comes tightly prescribed.
In the former, there is a reflex within the bureaucracy to prioritise waste/leak/abuse avoidance over inclusion, whereas in the latter, there is a tendency to over-prescribe so as to limit abuse even if it inconveniences genuine applicants. This is the rational choice arising from the institutional incentives.
In both cases, the precautionary effort detracts from the realisation of the primary objective. The pursuit of the ineligible (the false positive or the Type I error) comes at the exclusion or harassment of the eligible (the false negative or the Type II error).
All bureaucracies are prone to this precautionary bias. The clearest exemplar of this bureaucratic bias is cited in the oft-cited paper on regulatory economics concerning the invisible graveyard in the US FDA’s drug approvals process. The works of Sam Peltzman, Henry Miller, and Alex Tabarrok have shown that a drug regulator treats approving a harmful drug (visible deaths, Congressional hearings) as catastrophic and not approving a beneficial drug (invisible deaths among those who never got it) as costless, so it errs massively toward over-caution. Studies have estimated the ratio of Type II (delay) cost to Type I (bad-approval) cost in the thousands to one.
However, there are compelling reasons to argue that this bias is excessive in the Indian bureaucracy.
Root cause reforms aimed at deregulation should target this bias and not be confined tojust one-off changes to existing regulations. I blogged here and here on this issue.
There is an important contrast on this with the judiciary. There, the norm of the Blackstone ratio deliberately and explicitly instills that it is better to let ten guilty escape than allow one to suffer. The bureaucracy needs its equivalent norm.
As a conceptual framework to understand it, there are perhaps three drivers within the Indian bureaucracy of this bias.
1. The false positive is salient when detected, whereas the false negative is always a silent counterfactual. Even the oversight mechanisms focus on detecting and pursuing the false positives, while invariably staying silent on the false negatives. In public debates, too, media stories play up the false positives while largely overlooking the false negatives.
2. The bureaucrat gets personally hauled up in the case of a false positive that comes to light. Even if honest mistakes are safeguarded now, and they are finally exonerated, the public scrutiny and process harassment is a worse punishment.
3. The bureaucratic approvals process, especially the finance department concurrence (and also legal and personnel department concurrences), focuses far more on the false negative and mitigating them than on the efficiency and effectiveness of the achievement of its objectives.
These three drivers must be seen against the backdrop of a system with a very high level of trust deficit between the government and the beneficiaries (in the case of welfare and promotional policies) and the regulated (in the case of regulatory policies). In the Douglass-North sense, there is a low-trust institutional equilibrium inherited from the colonial control-state, which has hardened into a shared prior (“the applicant is a cheat”) and a norm (“process compliance is safety”).
There is also the historical inheritance of the colonial guardian bureaucracy built to maintain order and extract revenue, standing above and apart from the governed, and which elevates procedural purity over substantive correctness. At a social and political level, there is a stigmatisation of private benefit and a valorisation of public gain, which often views the two in binary zero-sum game terms. There is a widespread chalta hai (it’s alright) attitude that condones such delays, hassles, and exclusions, and does not provide credible enough channels to provide feedback and redress them. Finally, I am not sure whether ease of doing business and ease of living are yet the kind of electoral goods that generally force real, actual changes.
In contrast, the development trajectories of today’s advanced countries and China involved deliberate trade-offs that erred on the side of inclusion and lowering transaction costs. The regulatory excess in the US (captured in the so-called “everything bagel liberalism”) and the precautionary principles in the EU are more modern trends that emerged well after these countries reached their developed country status.
In contrast, the development trajectories of today’s advanced countries and China involve deliberate trade-offs that straddle a fine line between enabling and abuse. The regulatory excess in the US (captured in the discourse of everything bagel liberalism) and the precautionary principles in the EU are more modern trends that emerged well after these countries reached their developed country status.
As an analytical framework, the public loss function is to minimise social welfare loss by minimising inclusion and exclusion errors and compliance costs. The social optimum is when the marginal reduction in leakages and abuse is equal to the marginal increase in inclusion or convenience. Since abuse is generally rare and genuine cases are the overwhelming majority, the social optimum requires tolerating some leakage.
However, this public loss function comes up against the official’s private loss function. The aforesaid reasons amplify an accountability multiplier that forces his/her private loss function to minimise inclusions and abuse, even at the cost of exclusions and compliance costs.
The asymmetricity or gap between the two loss functions is the distrust wedge, the gap between the procedural strictness that the society would choose and the strictness that the incentive structure would produce.
Any remedy to address the root cause of the problem should revolve around shrinking the wedge, either by lowering the accountability multiplier (stop over-punishing honest false positives), making exclusion and compliance costs visible and costly, or lowering the compliance costs.
It is about internalising the implied shadow price of avoiding abuse or leakage. How many units of genuine exclusion or compliance cost is the system willing to incur to prevent one unit of abuse or leakage? This is the marginal trade-off that serious deregulation policy must target. There must be an institutional ownership (and bearing of the associated costs) of the cost of exclusion and harassment.
So, in terms of possible solutions, here are a few suggestions.
Efforts to change deeply entrenched norms and behaviours are complex endeavours. They are collective social and political choices that get adopted by the bureaucracy as strong and salient organisational narratives. They are best and most effectively done when they are done directly to change beliefs, norms, and behaviours.
The Indian state has generally struggled when it comes to instilling values to change collective behaviours.
It does better with specific interventions. But there is a risk in reducing such efforts to technical measures. The Ease of Doing Business ranking is a salutary example of the form taking over the substance and subverting the objective.
Nevertheless, the three-point conceptual framework articulated earlier can be the baseline for reforms.
The single highest-value and genuine root-cause fix to the problem is to make exclusion visible and costly. It is useful to have an institution, ideally within the Department (even with all the flaws or conflicts of interest), or one like the NITI Aayog, entrusted with the task of capturing/quantifying and updating the exclusion and compliance costs (the false negatives). This would include the publication of exclusion/rejection/non-uptake rates and median clearance times for every benefit and licence, by geography and office, as standard MIS. To also provide perspective, these metrics can be posted against some desirable benchmarks. This may be done for a prioritised set of activities for certain departments.
This may be an essential requirement to foster a culture that evaluates public services also in terms of their false negatives and compliance costs.
The first step is to quantify and make the costs salient and institutionally aware. An apprenticeship, a scholarship, or a credit-linked subsidy scheme should be evaluated primarily on its uptake. A welfare benefit should also be evaluated on the cost of access and the extent of its exclusions. The compliance cost of sectoral regulatory regimes (environment, development control regulations, building byelaws, land, labour, cyber security, etc.) should be quantified, as also those for various kinds of registrations and licensing (shops, schools, restaurants, clinics, visas, land, etc.).
This could be supplemented with an explicit articulation, for internal circulation, of an exclusion or compliance impact statement with every policy or regulation. This would provide policymakers and regulators the institutional freedom to account for convenience, access, and implementation flexibility, and avoid being exclusively hooked on loss prevention.
Auditors and oversight entities must explicitly incorporate this dimension in their audits, assessments, and investigations that tend to focus only on the false positives. This would offer the combination of deliberative process protection, the vigilance-intake filter that separates the honest error from corruption, and the avoidance of the ex-ante (not hindsight) audit standard.
Finally, the approval process should incorporate these principles across the gates. The financial, legal, and personnel concurrence/vetting should be circumscribed to ensure that the precautions and safeguards that are proposed don’t detract from the objectives.
There is a high risk of these efforts spawning more bureaucracy. So it must be done thoughtfully and not in a checklist-filling manner, as was done in the case of EoDB rankings.
Further, given that most policies and regulations are administered digitally, a low-hanging fruit would be extensive adoption of data analytics. The digital trails of administrative and transactional data could be analysed to detect abuses and address them. The emergence of AI-enabled applications equips us with the tools to do this easily and effectively. The challenge in each activity should be to define the likely problems and analyse to identify signatures of abuse.
To conclude, the stock of policies and rules with a precautionary bias is an output whose generator is the distrust wedge, or the asymmetric loss functions. The revision of rules one at a time merely empties the reservoir that the generator keeps replenishing. Therefore, the durable reform is to do a root cause analysis and recalibrate the generator with some of the aforesaid measures. This can shift the precautionary bias that is the current individual rational choice within the Indian bureaucracy.























