Food Demand Analysis
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. A complete demand system recognizes the interdependent relationships among all foods. ERS has estimated three sets of U.S. complete food demand systems covering 39 food categories and an aggregate nonfood sector:
Ordinary food demand system shows the amounts consumers will buy at given food prices and income and is useful for forecasting changes in food quantities demanded in response to changes in food prices and income.
Inverse food demand system shows the food prices consumers will pay at given food quantities and income and is useful for forecasting changes in food prices in response to variations in food quantities supplied.
Nutrient food demand system shows the effects of food prices and income on the nutrient content of diets and is useful for forecasting changes in nutrient availability in response to changes in food prices and income.
ERS researchers are currently updating and refining estimates of demand elasticities and will release this information in published reports and updated topic web pages.
Ordinary food demand system
ERS's ordinary food demand system for the United States contains 1,640 estimated demand elasticities covering 39 food categories and an aggregate nonfood sector. The demand system, in which food quantities demanded are functions of food prices and per capita income, is an effective model for forecasting food consumption and analyzing 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.
In table 1, each estimate of price elasticity shows the percentage change of a food quantity demanded in response to a 1-percent change in a food price or per capita income. For example, the own-price elasticities show that for a 1-percent increase in a food price, the demand for its own quantity would decrease by 0.621 percent for beef, 0.728 percent for pork, and 0.372 percent for chicken. The estimates of income elasticities in the last column show that for a 1-percent increase in per capita income, for example, the quantities demanded would increase by 0.392 percent for beef, 0.659 percent for pork and 0.077 percent for chicken.
For the estimates of cross-price elasticities, the positive signs imply substitution relationships and the negative signs imply complementary relationships. For example, the cross-price elasticity of beef in response to a 1-percent increase of the price of pork is 0.114, which means that the quantity of beef would increase by 0.114 percent to substitute for a decrease of pork because of its higher price. On the other hand, the cross-price elasticity of beef in response to a 1-percent increase in the price of cheese is -0.026, which means that the quantity of cheese would decrease causing beef consumption to decrease by 0.026 percent because of their complementary relationships.
Inverse food demand system
ERS's inverse food demand system for the United States contains 1,600 estimated price flexibilities covering 39 food categories and an aggregate nonfood sector. Agricultural economists have long recognized that lags between farmers' decisions on production and commodities marketed may predetermine quantities, with price adjustments providing the market-clearing mechanism. Therefore, the inverse food demand system, which takes food prices as functions of food quantities and income, can help explain marketing relationships and aid in forecasting food prices.
In table 2, each estimate of flexibility shows the percentage change of a food price in response to a 1-percent change in a food quantity demanded. For example, the own-price flexibilities show that for a 1-percent increase in a food quantity, its own price would decrease by 1.156 percent for beef, 1.142 percent for pork, and 1.239 percent for chicken. The income flexibilities are assigned to be 1, meaning that for the fixed amount of all quantities demanded, an increase in income will cause each commodity price to increase at the same rate.
For the estimates of cross-price flexibilities, the negative signs imply substitution relationships and the positive signs imply complementary relationships. For example, the price flexibility of beef in response to a 1-percent increase in the quantity of pork is -0.179, which means the quantity of beef consumption would decrease because of its substitution relationships; to keep the same quantity of beef, the price of beef would need to be reduced by 0.179 percent. On the other hand, the price flexibility of beef in response to a 1-percent increase in the quantity of cheese is 0.038. The means that the quantity of beef consumption would increase because of its complementary relationships, but to keep the same quantity of beef, the price of beef will need to be increased by 0.038 percent.
Nutrient food demand system
ERS's nutrient food demand system for the United States contains 1,008 estimated nutrient elasticities covering 36 food categories and 28 nutrients. This demand system shows that the changes in the availability of all 28 nutrients vary depending on how food price and income changes manifest themselves through the interdependent food demand relationships. For example, if the price of beef goes up while the price of chicken remains the same, consumers will likely buy less of the relatively more expensive beef and more of the relatively inexpensive chicken. Consumption of other foods could also be affected. If consumers buy less beef, such as hamburger meat, they might also buy less cheese and fewer hamburger rolls because of their complementary use in cheeseburgers. Because different foods provide different nutritional profiles, changes in food prices or in consumer income are likely to translate into changes in the food basket purchased, thereby affecting the quantities of nutrients available and the nutritional quality of consumer diets.
Measuring how economic factors influence the nutrient content of diets is increasingly important due to recent increases in obesity and overweight in the United States. Overweight and obesity are implicated as major risk factors for a number of chronic diseases, including cardiovascular disease, type 2 diabetes, hypertension, osteoporosis, and certain cancers. The 2001 report The Surgeon General's Call to Action to Prevent and Decrease Overweight and Obesity estimated that 61 percent of adults in the United States were overweight or obese, and the costs of overweight and obesity were as much as $117 billion a year. A poor diet and a sedentary lifestyle resulting in excessive food energy intake are the most important factors contributing to the problem of obesity and overweight in this country.
In table 3, each estimate of nutrient elasticity shows the percentage change of a nutrient in response to a 10-percent increase in a food price or a 1-percent increase in per capita income. According to nutrient elasticities for selected food categories, for example, a 10-percent increase in the prices of beef and cheese would substantially reduce the daily consumption of saturated fatty acids by 0.429 and 0.713 percent, respectively. The same price increases for beef and cheese would substantially reduce the daily consumption of cholesterol by 0.279 to 0.326 percent. The same price increase for beef, cheese, or milk would reduce the daily availability of calcium by a range of 0.43 to 0.82 percent. A 10-percent increase in the price of beef would decrease the daily availability of iron by 0.979 percent. A 10-percent increase in the price of oranges would decrease vitamin C daily availability by 0.993 percent.
According to the estimates, the increase of consumer income by 1 percent would increase energy by 0.272 percent, protein by 0.254 percent, saturated fats by 0.398 percent, and cholesterol by 0.312 percent. The same income increase would increase calcium by 0.307 percent, iron by 0.253 percent, and vitamin C by 0.325 percent. Obviously, the net nutritional effects of increasing consumer income are mixed. An increase in income affects all nutrients, and nutrient deficiencies such as calcium, iron, and various vitamins could be improved with increased incomes. The already excessive intakes of calories, saturated fats, and cholesterol, however, could increase with increased incomes.
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