Government Policy Initiatives to Address Regional Imbalance in India

Walk into a business park in Pune or Bengaluru and you will find sprawling tech campuses, ancillary industries, and a steady stream of investment. Travel a few hundred kilometres to parts of Bihar, Odisha, or the North-East, and the picture looks very different: thinner infrastructure, fewer factories, and a workforce that often migrates elsewhere for jobs. This gap between India’s advanced and lagging states did not happen by accident, and left entirely to market forces, it tends to widen rather than close. That is why the government has built a deliberate toolkit of fiscal transfers, industrial incentives, and area-specific programmes to nudge growth toward regions that private capital tends to ignore.

Why balanced regional growth needs deliberate policy 🔗

Businesses naturally gravitate toward locations with good roads, reliable power, skilled labour, and access to markets. States that industrialised early keep attracting fresh investment simply because the ecosystem already exists there, while backward regions stay backward precisely because they lack that ecosystem. Left unchecked, this creates a self-reinforcing cycle. Government intervention is meant to break that cycle through three broad instruments: transferring resources so poorer states can build capacity, using fiscal and locational incentives to pull industry toward underdeveloped areas, and running targeted programmes for the country’s most backward districts.

Central resource transfers and the Gadgil-Mukherjee formula 🔗

For decades, the single biggest lever for regional equity was the formula used to allocate central plan assistance to states. Before 1969, allocations were largely discretionary, which meant politically influential states often did better regardless of actual need. The Gadgil Formula, introduced during the Fourth Five-Year Plan, changed this by tying assistance to objective criteria: population, per capita income, tax effort, ongoing irrigation and power projects, and special problems faced by individual states.

How the formula evolved 🔗

The formula was revised more than once as its weaknesses surfaced. A modified version raised the weightage given to per capita income after critics pointed out that the original formula quietly favoured richer states through the irrigation and power component. In 1991, a committee headed by Pranab Mukherjee refined it further, and the resulting Gadgil-Mukherjee Formula stayed in use through the Eighth Five-Year Plan and beyond, until the Planning Commission itself was dissolved in 2015. Central transfers now flow mainly through Finance Commission recommendations on tax devolution, but the formula’s underlying logic, that need and performance should both count, still shapes debates on fiscal federalism today.

Special Category States: extra support where it is needed most 🔗

Within this framework, certain states were recognised as facing structural disadvantages too severe for a standard formula to address. States with hilly or difficult terrain, low population density, sizeable tribal populations, or sensitive international borders were classified as Special Category States, a status first granted to Assam, Nagaland, and Jammu and Kashmir. These states receive a far more generous funding mix, roughly 90 percent grant and 10 percent loan, compared to about 30 percent grant and 70 percent loan for general category states. The idea is simple: a state that cannot easily raise its own revenue or attract private investment because of geography should not be burdened with heavy loan repayments just to access development funds.

Priority to agriculture and infrastructure in backward regions 🔗

Fiscal transfers only work if the money reaches productive use, which is why planning has consistently prioritised agriculture and infrastructure spending in lagging regions. Irrigation, rural roads, power connectivity, and storage facilities were treated as prerequisites for any other kind of development, since a region without basic infrastructure cannot attract industry no matter how generous the subsidies on offer. Agriculture-focused investment mattered even more in backward states because a larger share of their workforce depended on farming, so improving irrigation coverage and market access directly raised rural incomes rather than waiting for industrial spillovers that might never arrive.

MSMEs: spreading industry beyond the metros 🔗

Large industry tends to cluster in a handful of established hubs, but micro, small, and medium enterprises behave differently. Because they need comparatively little capital and can operate close to raw materials or local markets, MSMEs have become one of the more effective tools for spreading industrial activity into tier-2 and tier-3 towns and rural clusters. Cluster-based development in sectors like handlooms, leather, and food processing has helped several backward districts build local value chains instead of depending entirely on migration for income. The One District One Product initiative, which now spans several hundred districts, builds on this same logic of turning local specialisation into an economic asset.

State governments have layered their own incentives on top of central schemes. Uttar Pradesh, for instance, offers a higher capital subsidy in its more backward Bundelkhand and Purvanchal regions than in comparatively developed areas, a graded structure designed explicitly to pull investment toward the state’s weaker districts. This kind of differential incentive, offering more support where the need is greater rather than a flat subsidy everywhere, has become a common feature of state MSME policy.

Locating public enterprises to widen industrial reach 🔗

In the early decades after independence, public sector enterprises were one of the government’s most direct tools for regional balance, since the state controlled where these large units were built. The Industrial Policy Resolution of 1956 explicitly framed public enterprises as instruments for preventing the concentration of economic power and reducing regional disparities, alongside their role in core sectors like steel and mining. Major steel plants and heavy industries were deliberately located in relatively undeveloped areas rather than existing industrial centres, generating ancillary units and employment around them. Public sector location decisions still weigh backward-area considerations, though technical and economic viability remain the primary filters, since a project that fails economically helps no one.

The same logic extended to private industry through licensing-era incentives. A tax-exemption scheme introduced in 1994 for districts formally classified as industrially backward is a well-studied example: research on the programme found that it produced meaningful growth in manufacturing employment and firm numbers in the backward districts that qualified, particularly in light manufacturing. It is a useful reminder that well-targeted fiscal incentives, not just infrastructure spending, can genuinely shift where industry chooses to locate.

Area-specific development programmes 🔗

Beyond state-level formulas, the government has periodically run programmes targeted at the district level, since backwardness within a state can be just as uneven as backwardness between states. The Backward Regions Grant Fund, launched in 2007, channelled supplementary funds into 250 identified backward districts before being discontinued in 2016. Its successor, the Aspirational Districts Programme, launched by NITI Aayog in 2018, took a different approach: instead of simply providing extra grants, it ranks 112 of the country’s most underdeveloped districts every month on health, education, agriculture, financial inclusion, and infrastructure indicators, creating a mix of convergence, collaboration, and competition between district administrations. Several of these districts have since shown sharp improvements in poverty and human development indicators, suggesting that transparent, outcome-based monitoring can complement direct funding rather than replace it.

The Rajan Committee: rethinking how backwardness is measured 🔗

By the early 2010s, it was clear that the Special Category framework had grown politically contentious, with several states lobbying for a status that was never designed to expand indefinitely. The government asked a committee under economist Raghuram Rajan to design a more objective, needs-based method for allocating funds. Submitted in 2013, the Rajan Committee report proposed a Multi-Dimensional Index built from per capita consumption, the poverty ratio, and related socio-economic measures, classifying states as least developed, less developed, or relatively developed based on their score. It recommended that every state receive a small fixed base allocation, with the bulk of additional funds split between a state’s current development needs and its improvement over time, and suggested phasing out the Special Category label altogether in favour of this single, transparent index.

The recommendations were not adopted without pushback. Critics pointed out that weighting allocations partly on performance could paradoxically penalise the states that needed help most, since improving socio-economic indicators is naturally harder for states starting from a lower base. Some committee members themselves dissented from parts of the final report. Even so, the Rajan Committee’s core idea, that a transparent composite index should replace ad hoc political classification, continues to influence how policymakers think about identifying genuine backwardness rather than relying on historical labels.

What do you think? 🔗

What do you think? Do you think outcome-based programmes like the Aspirational Districts Programme are a more effective way to close regional gaps than direct fiscal transfers such as the old Gadgil-Mukherjee formula? And should performance be part of how funds are allocated to backward states, or does that risk working against the states that need help the most?

References

1. https://ies.gov.in/arthapedia/concept/gadgil-mukherjee-formula
2. https://www.drishtiias.com/daily-updates/daily-news-editorials/reinvigorating-india-s-msmes-sector
3. https://ies.gov.in/arthapedia/concept/public-sector-undertakingsenterprises
4. https://www.sciencedirect.com/science/article/abs/pii/S0304387820301966
5. https://www.niti.gov.in/node/694
6. https://www.business-standard.com/article/news-ians/end-special-category-status-for-states-rajan-committee-113092600713_1.html