Consumer demand for food is an important element in the formulation of various agricultural and food policies. For consumers, changes in food prices and per capita income are influential determinants of food demand. Estimates of consumer demand quantify the effects of prices and total expenditures on the demand for food, which in turn, informs policymakers and researchers about how consumers make food purchasing decisions and helps policymakers design effective nutrition policy.
Consumer demand can be estimated within an unconditional demand system or within a conditional demand system. An unconditional demand system recognizes the interdependent relationships among all products purchased—food and nonfood products. A conditional demand system includes an interdependent relationship among a group of closely related foods—for example, milk, cheese, ice cream, and butter with the dairy group. Estimates from an unconditional demand system give a more complete picture of substitution between products, whereas estimates from a conditional demand system ignore substitution for products not within the group.
Consumer demand is often measured as an elasticity, which is a relative measure, providing a useful means of comparison across all ranges of quantities. The price elasticity of demand is a measure of the responsiveness of demand to a change in price.
- The own-price elasticity of demand is a measure of the responsiveness of demand for a product to change in the price of that product; in other words, the percent change in the quantity of a product resulting from a 1-percent change in its own price. For example, an own-price elasticity for apples of -0.58 means that a 1-percent increase in the price of apples decreases demand for apples by 0.58 percent.
- A food is said to be price inelastic—not responsive to price—when its own-price elasticity is greater than -1.0.
- A food is said to be price elastic—responsive to price—when its own-price elasticity is less than -1.0.
- The cross-price elasticity of demand is a measure of responsiveness of demand for one product to a change in the price of another product; in other words, the percent change in the quantity of a product resulting from a 1-percent change in the price of another product. The sign of the cross-price elasticity (positive or negative) indicates whether the two products are substitutes or complements.
- A positive cross-price elasticity means that the products are substitutes. For example, the cross-price elasticity for beef with respect to the price of pork is 0.33, meaning that a 1-percent increase in the price of pork increases demand for beef by 0.33 percent.
- A negative cross-price elasticity means that the products are complements. For example, the cross-price elasticity for coffee and tea with respect to milk is -0.04, meaning that a 1-percent increase in the price of milk decreases demand for coffee and tea by -0.04 percent.
- The expenditure elasticity of demand is a measure of the responsiveness of demand to changes in total expenditures—for conditional demand, this would be expenditures on a similar bundle of products, and for unconditional demand, this would be for all food and nonfood products. For example, the expenditure elasticity for foods from limited-service restaurants—restaurants with counter service—is 0.18, meaning that a 1-percent increase in total expenditures on all food and nonfood items increases demand for limited-service meals and snacks by 0.18 percent.
ERS conducts research on food demand in a domestic and international context.
ERS researchers are currently updating and refining estimates of demand for food in the United States, including price and expenditure elasticities. This information can be found in a recently published report, The Demand for Disaggregated Food-Away-From-Home and Food-at-Home Products in the United States.
In this report, ERS estimated unconditional own-price, cross-price, and total expenditure elasticities for 43 products, including:
- 3 food-away-from-home (FAFH) products:
- Limited-service restaurants;
- Full-service restaurants;
- Other FAFH venues, including vending machines and mobile vendors;
- 38 food-at-home (FAH) products:
- Flour and prepared flour mixes; breakfast cereals; rice and pasta; nonwhite bread; white bread; biscuits, rolls, and muffins; cakes and cookies; other bakery products;
- Beef; pork; other red meat; poultry; fish;
- Cheese; ice cream and frozen deserts; milk; other dairy;
- Apples; bananas; citrus; other fruits; potatoes; lettuce; tomatoes; other vegetables; processed fruits and vegetables;
- Carbonated drinks; frozen noncarbonated drinks; coffee and tea; soups; frozen meals; snacks; sauces and condiments; other miscellaneous; eggs; sugar and sweets; fats and oils;
- 1 nonfood composite.
The unconditional elasticities of demand in ERS's recent report can be used to forecast food consumption and analyze the effects of retail price changes on quantities of food purchased. For an outlook projection, information about changes in prices and income can be used to forecast food quantities demanded. For a program analysis, various scenarios of changes in prices and income can be used to evaluate the program effects on food quantities demanded. As an example, ERS used forecasted price changes of the Consumer Price Index (CPI) estimated by ERS (see Food Price Outlook) with the elasticities of demand to predict changes in expenditures on foods (see The Demand for Disaggregated Food-Away-From-Home and Food-at-Home Products in the United States).
ERS also estimates demand for food in an international context. In the recent report, Cross-Price Elasticities of Demand Across 114 Countries, ERS presents own- and cross-price and expenditure elasticities of demand for low-, middle- and high-income countries for aggregate products, including:
- Food, beverages, and tobacco;
- Clothing and footwear;
- Gross rent, fuel, and power;
- House furnishings and operations;
- Medical care;
- Transport and communications; and
- Other items.
The elasticities of demand in Cross-Price Elasticities of Demand Across 114 Countries were used to forecast food consumption in an international context in a recent ERS report, Global Drivers of Agricultural Demand and Supply.