Reforming the law for land: State capacity, productivity and growth

Unlocking factors of production - land, labour and capital - is crucial for growth in an AI-driven economy. Reducing administrative frictions in land markets will attract investments

An AI-led cycle of creative destruction is well underway and it is expected to have a differential impact on various economic sectors. The question of which sectors will flourish and which will slow down is therefore occupying all state governments. As Prof Karthik Muralidharan has noted in his book Accelerating India's Development, rather than trying to predict winning “sectors”, governments can do more to boost jobs, productivity and economic growth by reducing the frictions that keep key factors of production: Land, labour, and capital stuck in low productivity uses. Unlocking these factors will make them available to all sectors in the economy, and accelerate economic activity and growth. 

NITI Aayog’s Investment Friendliness Index 2026, which was released this month, scored all states on a 100-point scale across eight pillars and 84 indicators, based on both secondary data and a survey of  investors. No state scored above 60. The gap cannot be explained by differences in natural endowments or policies alone. These point to cross-cutting governance frictions in the factor markets that Muralidharan has noted. Of these, capital regulation is largely under union purview, labour sits on the concurrent list, where land is on the state list. 

Traditionally, governments have treated land more as a revenue source and an asset to be monetised, rather than as a factor of production. Gulzar Natarajan recently said in his blog Urbanomics that while China subsidises industrial land, India focuses on the revenue. In the process, Indian manufacturers end up paying 5-15x more for land alone. The first point of interaction for land market transactions is the registration system, which generates between 5 and 20 per cent of states’ own taxes. It is however part of a much larger administrative apparatus fragmented across at least five departments, which maintain separate land-related data systems that do not always speak with each other. 

Consider the impact on the land market. The state sets a base value for all land parcels, which has implications for tax liabilities, land prices and market liquidity. Distortions are introduced when these guideline values or circle rates lag behind market rates or overshoot them. More importantly, registration does not ensure title. Land registration and land ownership data reside separately. This is a data-engineering as much as an administrative problem. 

Land acquisition, too, gets complicated in the current system since compensation is based on guideline values. Land acquisition-related disputes made up nearly 30 per cent of the cases in the Supreme Court, according to a 2019 report by the Centre for Policy Research’s Land Rights Initiative. If undervaluation is perceived, landowners may dispute the compensation. Title disputes make it murkier, as the government cannot say for sure who is to be paid at all. A foundational first step was taken with the Unique Land Parcel Identification Number (ULPIN), and states are making significant progress in deploying it. This is urgent. 

Ownership aside, converting land to a more valuable use can be slow and inconsistent, at times taking months against the ease of doing business target of weeks. The variation in policy around change of use of agricultural land itself is stark and can range from not needing any government approval at all to being effectively blocked. Delays only overlay the system. Both design and governance matter. 

Even after zoning permissions are given, building and other rules significantly reduce the extent of land that can be used, and these limits are regressive by size. Underutilisation of land is not only industrial. India is leveraging urban densification poorly. Natarajan finds (elsewhere) that only 31 per cent of urban Indian households live in flats or apartments (compared to, say, 85 per cent in urban Spain). This is not only due to preferences, but also restrictions. Low FSI limits how much can be built on any plot of land. The urban response is to sprawl, but this too is constricted. Roads occupy between 6 and 12 per cent of the surface area across five major metros, with the sixth, Delhi, being the outlier at 21 per cent. The absence of connectivity puts people physically out of reach of growing economic centres and jobs. In other words, seemingly unrelated restrictions cascade into further factor misallocation. Investments in mobility will have to be the backbone of an overdue densification programme. Infrastructure matters, but it is easier said than built. 

Infrastructure plays a significant role in improving productivity of land and is an important value driver itself. While the instinct is always to allocate more, execution capacity more than availability of resources constrains infrastructure creation. Business Standard’s analysis of Comptroller and Auditor General reports found that utilisation of funds was at 77 per cent across 20 states in the last fiscal year, leaving more than ₹2 trillion on the table. On the ground, low expenditure translates into slow completions. Data from the Ministry of Statistics and Programme Implementation’s “PAIMANA Flash Reports” for April-May 2026 suggests that, on average, between 30 per cent to over 90 per cent of 1,662 projects across seven key sectors — from power to irrigation — were delayed in May 2026. The average delay itself varied between 16 and 68 months. These are not just fiscal costs, but economic costs that households and firms internalise. 

Utilisation of created assets is a function of quality and pricing. The build-neglect-rebuild paradigm persists and maintenance expenditure lags. Pricing brings its own distortions. Industrial and commercial users pay more than 150 per cent of the efficient cost of supply respectively, while agricultural and domestic consumers pay 16 per cent and 61 per cent — a cross-subsidy that taxes exactly the investments states are trying to attract. In the AI world, distorted power markets pose significant barriers. Even with the cross subsidy, state utilities suffer persistent losses, which are eventually borne by the state exchequer. This crowds out the same infrastructure spending that states seek to prioritise, while impacting their overall financial health. The dominoes topple each other. 

None of this reflects a lack of government will or effort. Andhra Pradesh has already achieved full ULPIN coverage; Karnataka’s Kaveri platform has integrated registration and records. Many other states are progressing fast on these fronts. Policy instruments and tools are both available and already driving reforms. What may be missing is an analytical, market intelligence layer that brings real-time visibility and actionability. 

States already generate and possess enormous administrative data such as registered transactions, land records and works-management systems. They are now looking at linking these and adding analytical layers that not only help decide the future course, but also flag corrections needed — eg, widening valuation gaps, execution delays — to allow targeted action. All of these are unobjectionable governance fixes, which are cheaper and faster than policy reforms. For states seeking to attract private investors, investing in their own capacity to deliver better may bring the highest returns. 

The writer is vice-president, Centre for Effective Governance of Indian States. Views are personal