Cost of Affordable Healthy Diet (CoAHD) in India

1. Introduction

This document explains how we calculate the Cost of an Affordable Healthy Diet (CoAHD)^[1] in India using the Household Consumer Expenditure Survey (HCES) 2011-12 & 2023-24 data.^[2]

1.1 What is a Recommended Diet?

Based on the Indian Council of Medical Research - National Institute of Nutrition (ICMR-NIN) guidelines^[3], a balanced daily diet for an adult woman (55 kg, moderate activity, non-lactating) should include:

Table 1: ICMR-NIN Recommended Balanced Diet^[3]

These quantities represent the minimum amounts needed to meet nutritional requirements for maintaining good health.

2. Methodology

2.1 Step 1: Calculate Food Prices

We calculate prices for each food category using household consumption data. The process involves three stages:

2.1.1 Price Calculation at Household Level

For each household, we calculate:

1. Quantity consumed (in grams per day)
2. Price per gram = Total expenditure ÷ Total quantity consumed^[4]

For example, if a household spends ₹150 on 5 kg of rice over 30 days: - Daily consumption = 5000g ÷ 30 = 167 grams - Price per gram = ₹150 ÷ 5000g = ₹0.03/gram

2.1.2 Aggregate Prices by State and Sector

We compute Quantity-weighted average prices at the state × sector level (rural/urban):

1. Mean price: Quantity-weighted average across all households

In addition to the mean we also considered:

1. Median price: 50th percentile of prices (middle value)
2. Modal price: Most frequently observed price

Why weight by quantity?

Weighting by consumption quantity ensures that our price estimates accurately reflect what people actually eat in each region, not just what’s available.

The Core Principle

When calculating category-level prices (e.g., “Cereals & Millets”), we don’t simply average the prices of all items in that category. Instead, we weight each item’s price by how much households actually consume it.

Why this matters

Different states have dramatically different consumption patterns within the same food category.

Price Aggregation Process:

1. Household Level
   → Calculate price per gram for each household
   
2. Item-State-Sector Level
   → Aggregate across households (weighted by consumption)
   
3. Category-State-Sector Level
   → Average across items within food category
   
4. Final Price
   → State × Rural/Urban price for each food category

2.1.3 Addressing Selection Bias: Why We Calculate Prices Across All Expenditure Quintiles

The Methodological Challenge

When estimating the cost of a nutritionally adequate diet, we face a fundamental question: Which market prices should we use? The intuitive answer—use prices paid by poor households—runs into a critical problem: consumption selection bias.

Poor households don’t consume all food items required for adequate nutrition. When they don’t purchase an item, we observe no price for that item from that income group. This creates systematically incomplete price data that understates the true minimum cost of achieving nutritional adequacy.

Understanding Consumption Selection Bias

Definition: Consumption selection bias occurs when certain income groups systematically avoid purchasing specific food items due to affordability constraints, resulting in missing or unreliable price data for those groups.

The Core Problem:

The recommended diet (based on ICMR-NIN guidelines^[3]) requires specific quantities from nine food categories. However:

1. Poor households don’t consume from all categories due to cost constraints
2. No consumption = No observed prices for that group
3. Missing prices prevent calculating complete diet cost
4. Using incomplete data systematically underestimates minimum cost

Our Methodological Solution

Approach: Calculate prices separately for each expenditure quintile, then take the minimum observed price across all quintiles for each state × sector × food category combination.

Why minimum across all quintiles?

This approach serves multiple purposes:

1. Ensures complete data coverage
   1. Uses bottom quintile prices when available
   2. Falls back to higher quintiles when lower quintiles lack data
   3. Guarantees we can calculate costs for all nine food categories
2. Represents true minimum market cost
   1. Not “what poor currently pay” (often incomplete)
   2. But “minimum achievable cost given market prices”
   3. Reflects most cost-effective way to obtain required nutrition
3. Captures market realities
   1. Some items are might not be consumed by poor
   2. But these items exist in markets at observable prices
   3. Higher-income consumption reveals these baseline prices
4. Addresses data availability constraints
   1. Bottom quintiles: Good price data for staples (cereals, vegetables)
   2. Middle quintiles: Fill gaps for items with moderate consumption (fruits, milk in some states)
   3. Top quintiles: Only source of data for rarely-consumed items (nuts, premium fruits)
   4. Method adapts to where reliable data exists
   5. Shows technically achievable minimum, not income-constrained choice

The Calculation Process

Step 1: Calculate prices for each quintile separately

For each expenditure quintile (Q1-Q2, Q3-Q4, Q5-Q6, Q7-Q8, Q9-Q10): - Identify households in that quintile within each state - Calculate weighted mean/median/mode prices for each food item - Aggregate items to food categories (weighted by consumption) - Result: Category-level price for that quintile

Step 2: Identify minimum price across quintiles

For each state × sector × food category:

1. We report prices which includes quantity of food purchased through the Public Distribution System (PDS) or provided free by the Government.

2. We also report prices which excludes Government support in the form of PDS or free food.