U.S. household energy costs increased rapidly from 1999 through 2009. The sharp increase in costs to heat or cool a residence forces some consumers to make difficult choices. The core finding from previous research suggests that many low-income households face an extremely difficult decision between heating a residence or eating. Rising prices and limited budgets of low-income households prevent them from choosing sufficient quantities of both fuel and food, leading them to a choice of “heat or eat.”
Previous studies support the existence of a food-fuel tradeoff for low-income households within the United States, but none have attempted to calculate the cross-price elasticities associated with this tradeoff. Elasticities are important because they provide a very simple, intuitive measure for how consumers react when prices change. Quantifying energy-food tradeoffs in low-income households provides policymakers with information needed to understand the impacts that energy price shocks have on household food security and to design assistance programs and other safeguards to protect vulnerable households.
This study generates own-price, cross-price, and expenditure elasticities using a quadratic almost ideal demand system (QUAIDS), a refinement that better estimates non-linear Engel curves compared to the original almost ideal demand system. These elasticity estimates are then used to examine how energy price shocks impact household food consumption. Poor households often face the most severe “heat or eat” decision and Southern households have unique demographic and climatic considerations. Therefore, elasticities are estimated separately for these sub-samples.
The study relies on several data sources. Household expenditure data from 1999 until 2009 is obtained from the Bureau of Labor Statistics’ Consumer Expenditure Survey (CES). Price data is collected from the American Chamber of Commerce Research Association (ACCRA, now the Council for Community and Economic Research) cost of living index, a proprietary price index, and the Energy Information Administration (EIA). Finally, State-level climate data are compiled from the National Oceanic and Atmospheric Administration (NOAA). Because of data limitations, the final sample for analysis includes 121,435 households from 35 States.
Elasticities are calculated from the parameter estimates using mean prices, expenditures, and demographics. All elasticity estimates are significant at conventional levels. Own-price elasticities are consistent with expectations. Food at home and food away from home show inelastic own-price elasticities. Own-price elasticities for natural gas and electricity, however, are more elastic. Cross-price elasticities are of particular importance because they describe the “heat or eat” tradeoffs made by households. Cross-price elasticity estimates reveal that expenditures on food fall when energy prices increase and expenditures on energy fall when food prices increase.
Poor households are the most likely to face the “heat or eat” dilemma. Elasticity estimates for poor households seem to confirm a more pronounced reaction to price changes. Own-price elasticity estimates for poor households are higher for food at home, natural gas, and electricity compared to nonpoor households. Thus, price increases reduce demand for basic commodity groups more in poor households than in nonpoor households.
Many cross-price elasticities also suggest poor households react differently to price changes than non-poor households. Cross-price elasticity estimates for poor households are lower for both natural gas-food at home and electricity-food at home. Lower cross-price elasticity estimates might imply extremely constrained budgets for poor households that operate at a minimum necessary expenditure level for survival. Reductions in expenditures below these levels might endanger the well-being of family members, making elasticity estimates smaller and masking a more dangerous underlying problem.
Southern households often are categorized as regionally different based on climate and regional preferences compared to the rest of the United States. Most elasticity estimates calculated for the Southern sub-sample, however, do not support this characterization. Both own-price and cross-price elasticity estimates for all commodity groups except natural gas are relatively similar to those estimated for the nation as a whole. The small differences in fuel-food cross-price elasticity estimates support the notion that Southern households react comparably when facing energy price shocks.
Poor households, which are those most susceptible to food and energy insecurity, exhibit “heat or eat” tradeoffs in consumption behavior. When an energy shock causes energy prices to rise, poor households reduce consumption of food expenditures as well as the directly impacted energy commodity. Specifically, estimates show that an energy price shock of 10 percent can lead to reductions in food at home expenditures of up to five percent. Policymakers must therefore realize that energy shocks have a significant impact on household food expenditures, especially food at home. On the other hand, policymakers do not need to make any special concessions or regulations for Southern households. Southern households adjust consumption similarly to the rest of the United States, even though they live in a unique climate with more cooling and less heating needs and have substantially more poor and rural households.
Policymakers could expand and improve upon Federal energy assistance programs. Future energy assistance programs can help safeguard poor households in ways not directly tied to utility bills. Energy assistance benefits that help poor households maintain food expenditure levels equal to pre-shock status would reduce the food or fuel tradeoffs that low-income households make and preserve household food security in the face of energy price shocks.