Research Publications

Understanding how consumption patterns affect the environment and shape well-being hinges on the rationale that the data collected on what is consumed, who consumes it, and where are indeed accurate. To identify such consumption patterns and recommend policies as a result, researchers and policymakers often rely on national surveys. Studies have explored the accuracy of individual surveys and the level of agreement across surveys of the same type (e.g., household expenditures), but no studies have compared representative, national surveys measuring consumption in different ways. This study compares household consumption measured as expenditures and as material consumption (i.e., physical units) to assess how well we measure what we consume. We used multiple rigorous, national surveys to estimate meat consumption, household energy use, and private automobile use in the United States, with consumption profiles parsed by affluence, race/ethnicity, and education. We find that commonly used surveys may not accurately track important aspects of household consumption. For meat consumption, which included 30 consumption profiles detailing the consumption patterns across different demographic characteristics and meat types (e.g., kilograms of beef consumed per capita for Caucasians), we found considerable disagreement between data sources for 20 profiles. By contrast, national surveys accurately measured household energy and transport (disagreement for four profiles). These results suggest that national surveys are much better at measuring goods consumed in standard forms under constant monitoring (e.g., electricity) than they are at measuring goods consumed in heterogeneous forms with inconsistent monitoring (e.g., food). These results cast doubt on studies that use national surveys to draw conclusions about how the environmental impacts of food, and, potentially, other goods (e.g., manufactured goods) vary across demographic groups. Overcoming this challenge will necessitate new surveys, updating legacy databases, and harnessing innovative methods.