Goodhart’s Law and the Cobra Effect in India’s Policy Making

 

Goodhart’s Law and the Cobra Effect in India’s Policy Making

Public policy in India often suffers from a gap between intention and outcome. At the heart of this paradox lie two concepts from economics and social sciences — Goodhart’s Law and the Cobra Effect. Both capture how well-meaning metrics and incentives can backfire, especially in a diverse democracy where welfare delivery faces challenges of scale, leakages, and local adaptation.

Goodhart’s Law and the Cobra Effect: A Primer

• Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.” Once metrics are linked to rewards, people start gaming the system rather than solving the real problem.
• Cobra Effect: Named after colonial India, when the British offered money for every dead cobra to reduce their population. Citizens began breeding cobras to kill and sell for reward. When the policy was scrapped, the cobras were released, worsening the problem.

Both highlight how poorly designed incentives distort behavior and create perverse outcomes.

Case Studies from Indian Policy and Welfare Schemes

1. Learning Outcomes in Education

India’s school education policy historically measured success by enrollment and infrastructure — number of classrooms, midday meals, teacher recruitment. As per Goodhart’s Law, once these became targets, states focused on inflating enrollment and building structures, while learning outcomes stagnated. The ASER reports (2005–2022) consistently showed that even after years of schooling, many children struggled with basic arithmetic and reading.

2. MGNREGA (Mahatma Gandhi National Rural Employment Guarantee Act)

The world’s largest employment guarantee scheme aimed at providing 100 days of work per household. But linking performance to “number of person-days generated” led to inflated work records, ghost workers, and incomplete assets. Instead of durable rural infrastructure, the incentive system sometimes encouraged quantity over quality.

3. Janani Suraksha Yojana (Maternal Health)

Cash incentives to institutionalize deliveries reduced home births dramatically. But in several cases, women were rushed into hospitals for monetary reasons without adequate facilities or postnatal care. The target — numbers of institutional deliveries — became more important than the quality of maternal and infant health services.

4. Toilet Construction under Swachh Bharat Mission

The ambitious mission reported near-total household toilet coverage by 2019. However, several surveys revealed issues of toilet functionality, water access, and behavioral usage. The rush to meet construction targets often overlooked sustainability — showing the classic Goodhart’s Law trade-off between numbers vs. actual sanitation outcomes.

5. Fertilizer and Subsidy Policies

Incentives to increase foodgrain production during the Green Revolution led to overuse of urea subsidies, distorting soil health and groundwater tables. Farmers optimized to maximize subsidies and yields, not long-term sustainability — an unintended “cobra effect” that still burdens Indian agriculture today.

Why These Effects Persist in India

1. Target-driven bureaucracy — Officers are evaluated on achieving measurable outputs, not nuanced outcomes.
2. Political pressures — Short-term results look better in electoral cycles.
3. Scale of welfare schemes — With hundreds of millions of beneficiaries, central monitoring relies heavily on metrics.
4. Weak feedback loops — Ground-level realities are often masked by inflated reporting.
5. Resource constraints — Quantity becomes easier to track than quality.

The Way Forward: Designing Better Policies

1. Focus on outcomes, not just outputs — Eg. measuring literacy and numeracy skills instead of only school enrollments.
2. Build feedback loops — Independent social audits, community scorecards, and civil society participation.
3. Use technology smartly — Aadhaar-linked DBTs, geotagging assets, real-time dashboards to reduce gaming.
4. Align incentives with behavior change — Example: moving Swachh Bharat from construction to sustained usage through campaigns.
5. Flexibility and local adaptation — One-size-fits-all metrics often fail; decentralization can ensure context-specific outcomes.

Conclusion

India’s welfare architecture is massive and ambitious, but the lessons of Goodhart’s Law and the Cobra Effect remind us that badly designed metrics can derail even the best policies. True success lies not in ticking boxes but in improving lived realities — healthy mothers, educated children, sustainable agriculture, and dignified rural employment.

As India moves towards becoming the world’s third-largest economy, its governance must also mature from counting numbers to measuring impact.

NITI Aayog vs. Planning Commission: A Tale of Bias, Misdirection, and Missed Opportunities

 

NITI Aayog vs. Planning Commission: A Tale of Bias, Misdirection, and Missed Opportunities

When NITI Aayog replaced the Planning Commission in 2015, it was pitched as a bold reboot — swapping centralized control for cooperative federalism, rigid five-year plans for flexible policy advice. A decade later, the shift feels less like evolution and more like a pivot with trade-offs. Both institutions have shaped India’s development, but their approaches, powers, and pitfalls — especially around bias and misdirection — reveal stark contrasts. Let’s break it down with data and evidence.

Structure: Power vs. Persuasion

The Planning Commission, born in 1950, was a heavyweight. Chaired by the Prime Minister, it included a Deputy Chairperson, full-time members, and a robust secretariat, wielding authority to design and fund five-year plans. It allocated resources — ₹20.7 lakh crore across 12 plans from 1951 to 2012, per adjusted 2011–12 prices — directly influencing state budgets. States had a say via the National Development Council (NDC), where Chief Ministers could negotiate allocations, though the Centre often held sway.

NITI Aayog, launched on January 1, 2015, is leaner and toothless by design. Also chaired by the PM, it includes a Vice-Chairperson (currently Suman Bery), full-time members, and state CMs in its Governing Council. But unlike its predecessor, it has no financial muscle — its budget peaked at ₹339 crore in 2023–24, a speck against the Planning Commission’s heft. It advises, not mandates, relying on persuasion over power. Critics argue this makes it a cheerleader for central agendas, not a partner to states.

Function: Plans vs. Projections

The Planning Commission’s hallmark was its five-year plans, setting ambitious targets — like reducing poverty from 45% in 1994 to 27% by 2007 (Tendulkar methodology) — and backing them with funds. It wasn’t flawless: the 11th Plan (2007–12) aimed for 9% GDP growth but hit 7.9%, per World Bank data, hampered by global recession and domestic bottlenecks. Yet its data-driven approach, rooted in NSSO surveys and state inputs, gave it credibility, even if execution lagged.

NITI Aayog ditched plans for indices and vision documents — think SDG India Index or the 2017 “India@75” roadmap. Its 2024 poverty claim, asserting a drop from 29.17% in 2013–14 to 11.28% in 2022–23 (lifting 24.82 crore people), showcases its style: bold projections over concrete action. Unlike the Planning Commission’s reliance on consumption surveys, NITI leans on the Multidimensional Poverty Index (MPI) and NFHS data, projecting gains through COVID-19 disruptions despite halted NFHS-5 surveys in 22 states and a slashed education budget (2.9% of GDP in 2023, per UNESCO). This optimism feels like misdirection when 80 crore Indians still need free rations.

Bias: Centralized Control vs. Political Alignment

The Planning Commission wasn’t immune to bias. Its top-down model favored Congress-ruled states during its heyday — Maharashtra and Andhra Pradesh often bagged bigger shares in the 1970s and 80s, per NDC records. Yet it had checks: the NDC forced dialogue, and its funding power gave states leverage to push back. A 2011 CAG audit criticized its “one-size-fits-all” approach, but it rarely hid inconvenient data — like the 37% poverty rate in 2011–12.

NITI Aayog’s bias tilts differently. Lacking allocation authority, it’s accused of amplifying BJP priorities. The 2024 Governing Council boycott by seven opposition-ruled states (Tamil Nadu, Kerala, etc.) over Budget snubs highlights this: central scheme funds disproportionately flow to BJP states — Uttar Pradesh got ₹1.79 lakh crore for highways (2014–2023), while Kerala lagged. NITI’s Health Index ranks states competitively but glosses over resource gaps — Kerala funds 70% of its top-ranked health system, while poorer BJP states lean on central aid. Its reliance on non-official sources (27 of 94 footnotes in a 2018 water report from media/blogs) further fuels perceptions of narrative-driven spin.

Misdirection: Underselling vs. Overselling

The Planning Commission’s misdirection was subtle — underselling failures to protect political egos. The 8th Plan (1992–97) targeted 5.6% growth but hit 6.8%, yet rural poverty lingered at 44% (1993–94), per NSSO data, masked by urban gains. It rarely hyped unverified wins, sticking to measurable (if flawed) outcomes.

NITI Aayog excels at overselling. Its “95% rural electrification” claim in 2018 counted villages with 10% household coverage — a 2021 CAG audit found 2.5 million homes still dark. The Global Innovation Index jump (81st in 2015 to 40th in 2022) is touted as a win, but R&D spending stagnates at 0.7% of GDP (World Bank), far below China’s 2.4%. NITI’s rosy reports distract from structural woes — 22% child stunting in 2023 (UNICEF) contradicts its poverty “miracle.”

Impact: Legacy vs. Limelight

The Planning Commission built dams, schools, and industries — its irrigation push lifted coverage from 17% of farmland in 1951 to 45% by 2011, per Ministry of Agriculture data. Its clout came at a cost: bureaucratic inertia and a Delhi-centric lens. NITI Aayog’s legacy is less tangible — indices and advisories don’t fill potholes. India’s press freedom rank (150th in 2024) and rising Gini coefficient (35.7 in 2021) suggest its cheerleading hasn’t tackled inequality or accountability.

The Verdict

The Planning Commission was a flawed giant — biased, but grounded; directive, but deliverable. NITI Aayog is a nimble narrator — flexible, but flimsy; cooperative in name, but often a megaphone for power. One misdirected through silence, the other through hype. India needs a hybrid: NITI’s agility with the Commission’s authority, minus the politics. Until then, both remind us — data can inform, but intent decides what we see.