India's Consumer Price Index (CPI) underwent its most significant modernization in over a decade with reforms formalized in January 2026. These updates brought meaningful improvements, including the incorporation of rural rents, exclusion of employer-provided accommodation, and expanded data dissemination. However, a critical structural flaw in how housing rents are measured persists, potentially distorting national inflation figures and impacting monetary policy.
The Problem of Rent Stickiness
The core issue lies in 'rent stickiness' embedded within housing leases. Most Indian rental agreements include predetermined annual escalation clauses, typically 5-10%. While these apply to continuing tenants, rents for new tenants reset based on prevailing supply and demand conditions in the market. The current CPI methodology primarily captures the average rent paid by incumbent tenants, rather than the marginal rent faced by new entrants.
This divergence means the index is more influenced by contractual escalations than by actual shifts in the housing market. As a result, the official CPI housing inflation can appear subdued even when brokers and new tenants report substantial, double-digit rent increases on the ground. This discrepancy can undermine the credibility of inflation signals.
Global Precedent and Policy Impact
International research reinforces these concerns. Studies in the United States, for instance, have shown that shelter indices can systematically underrepresent new tenants, lagging market rent indices by up to a year. During the Global Financial Crisis, this lag meant official inflation was overstated by significant percentage points because shelter inflation declined much slower than actual market rents, leading to delayed monetary easing.
In India, this lag has tangible consequences. Housing carries a substantial weight in the CPI basket. If housing inflation does not accurately reflect market dynamics, headline inflation will also lag at crucial cyclical turning points. This could lead to monetary policy tightening being delayed during periods of rapid rent increases or easing being postponed when markets soften. Over time, such inaccuracies can influence inflation expectations and erode the credibility of the inflation target itself.
Pathways to More Accurate Measurement
To mitigate this issue, experts propose several solutions. One immediate step involves explicitly identifying tenant changes within the sample and separating rent resets from continuing contracts. Statistical models could then infer current market rent for dwellings where leases haven't turned over, using nearby reset transactions as benchmarks. This combined approach of observed and model-implied market rents is already employed for commercial office rentals and could be extended to housing.
A longer-term redesign would embed tenant changes directly into the sampling methodology. Rent resets would be tracked as primary observations, with market rent for continuing leases estimated using comparable properties within the same micro-market. This approach recognizes the dynamic and spatial nature of rental markets, moving beyond static contractual averages.
Reforming the CPI's housing component is more than a technical exercise; it's crucial for effective monetary policy and public trust. By accurately capturing tenant turnover and treating rent resets as primary signals, India's inflation statistics can more faithfully track housing cycles, sharpening policy signals and strengthening public confidence that the CPI genuinely reflects the costs households face.