Key Details
The RBI paper, Data Gaps in State-Level Inflation: An Assessment for the Covid Period, estimates urban Consumer Price Index (CPI) inflation for four missing months—not rural or combined State inflation.
Why four months are missing: State price indices could not be compiled for April and May 2020 because too few prices were collected. Although State indices were published for April and May 2021, their year-on-year inflation rates could not be calculated without the corresponding 2020 indices.
Coverage: The RBI’s Inflation Expectations Survey of Households covers 18 urban centres representing 17 States and UTs. Together, these account for 86.8% of India’s urban CPI weight.
Method: The study relates the distribution of households’ reported inflation perceptions and expectations to recent official State urban-inflation data, then adjusts the resulting estimates using historical forecast errors.
Aggregate comparison: When combined, the refined estimates differ from published all-India urban inflation by approximately 13–22 basis points across the four months. Simple interpolation produces much larger aggregate differences.
Household Expectations Offer a Way Across the Data Break
MoSPI published imputed all-India CPI figures for April and May 2020, but insufficient price quotations prevented it from compiling State indices. The gap carried into 2021: without an index from a year earlier, a year-on-year State inflation rate could not be calculated even when current prices were available.
The paper tests whether the RBI’s household survey can help recover that missing regional picture. It uses respondents’ current inflation perceptions for May estimates and three-month-ahead expectations for April estimates, when no April survey round was available. Rather than treating the average survey answer as inflation, it maps patterns in those responses against recent official urban CPI inflation.
A Close National Match Does Not Verify Every State Figure
After adjustment, the weighted aggregate of the estimated State figures sits close to official all-India urban inflation. The study also reports a substantially better aggregate match than a simple interpolation between available monthly indices.
That is useful evidence for the method, but it has a boundary: errors in individual State estimates can offset one another in a national average. The survey samples selected urban centres, and what households think prices are doing does not necessarily track the CPI consumption basket. The paper therefore presents a plausible reconstruction for research, not a replacement for the missing official observations.
Policy Relevance
The immediate value is continuity for regional inflation research: analysts can examine the pandemic period without simply dropping four months from the urban State series. The paper also shows how an existing household survey can provide supplementary evidence when routine price collection fails.
For statistical agencies, the distinction between estimated and observed inflation remains essential. Publishing such reconstructions with their methods and uncertainty clearly identified would make them more useful without implying that missing State prices were subsequently measured.
Follow the Full Working Paper Here: Data Gaps in State-Level Inflation: An Assessment for the Covid Period