Discrepancies in India’s Household Consumption Data
Recent data reveal a growing gap between two key measures of household consumption in India. Private Final Consumption Expenditure (PFCE) and Household Consumption Expenditure Survey (HCES) estimates differ by nearly 45 per cent in 2022-23. This divergence poses challenges for economic analysis and policy-making. About these differences is crucial for accurate measurement of consumption, poverty, and welfare.
About PFCE and HCES
- PFCE is a macroeconomic measure estimating the total value of goods and services consumed by households and non-profit institutions serving households. It uses the commodity flow method, incorporating data from production, trade, prices, and administrative sources. PFCE includes goods and services provided free or at subsidised rates, such as government healthcare or NGO support.
- HCES, in contrast, is a micro-level survey capturing self-reported household spending. It records actual out-of-pocket expenses on goods and services. HCES is vital for assessing poverty, inequality, and food security. However, it often misses free or subsidised consumption and underreports certain expenditure types.
Reasons for the Consumption Gap
- Methodological differences mainly explain the gap. PFCE values all consumed goods and services, including free ones, while HCES counts only paid expenses. For example, expensive medical treatments provided free by the state appear in PFCE but not fully in HCES.
- Price and valuation differences add to the gap. PFCE uses market prices from administrative data. HCES calculates prices from household reports, which may be inaccurate or inconsistent.
- Timing also matters – HCES covers an agricultural year; PFCE aligns with the financial year, causing mismatches. The gap has widened from 5 per cent in 1972-73 to about 45 per cent . This rise raises concerns about the reliability of consumption data for policy design and economic planning.
Changing Consumption Patterns
HCES data show a shift in household spending. Food expenditure share has declined in rural and urban areas. Non-food spending now dominates, driven by transport, healthcare, education, rent, and durable goods. Within food, cereals and pulses have decreased, while milk, fruits, processed foods, and proteins have increased. This shift reflects rising incomes and changing lifestyles. However, it also complicates consumption measurement since non-food services are often harder to capture accurately in surveys.
Policy Implications of the Discrepancy
If HCES underestimates consumption, poverty and deprivation may be overstated. This can lead to misdirected welfare programmes and inefficient targeting of subsidies or benefits. Conversely, if PFCE overestimates consumption, it may create an overly optimistic economic picture, affecting fiscal and social policies. Accurate consumption data are essential for programmes like the Public Distribution System and Direct Benefit Transfers. These rely on consumption estimates to identify beneficiaries and allocate resources effectively.
Measures to Bridge the Gap
- Improving HCES sampling is vital.
- Affluent households may be underrepresented due to non-cooperation.
- Comparing HCES with income tax data, digital payment records, and scanner data can identify under-reporting.
- Aligning income tax filings with HCES data helps adjust for top-income undercoverage.
- Scanner data from retail and digital platforms provide detailed purchase information and can supplement surveys.
- HCES questionnaires need updates to capture modern consumption modes like app-based services, online education, and digital subscriptions.
- PFCE compilation requires revising outdated assumptions and ratios. Regular surveys of non-profit institutions serving households can improve PFCE accuracy.
- Finally, a formal reconciliation mechanism combining PFCE’s broad coverage and HCES’s detailed household data is recommended to produce more reliable consumption estimates.
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