Title: Variations in Consumer Sentiment across Demographic Groups
Abstract: Introduction and summary Consumer sentiment is one of the many macroeconomic indicators tracked by policymakers. Consumer sentiment--as measured by indexes such as the Index of Consumer Sentiment (ICS) and the Consumer Confidence index (CCI)--is seen as a barometer of economic activity, one that is a reliable indicator of the way people plan to spend their money. Consumer sentiment is important because it affects household spending. Nationally, household spending on final goods and services (retail sales) represents about 65 percent of all expenditures for final goods and services, the nation's gross domestic product (GDP). Since private consumption expenditure accounts for such a large proportion of GDE consumer sentiment can signal changes in the direction of the economy. Numerous studies have assessed the extent to which consumer sentiment is related to fluctuations in GDP, the stock market, and other outcomes. While the overall index scores, so closely watched by the public, are important, these aggregate numbers conceal a wealth of demographic-specific information contained in the survey data. Analyzing the survey data at disaggregated levels enhances the indexes' informative power (Dominitz and Manski, 2004). Consumers' expectations about specific sectors of the economy, such as expectations of inflation, income, employment, and home values, usually differ by demographic group and often move in opposite directions by group. These disparities in expectations translate into distinct spending patterns by different groups. Additionally, personal spending patterns vary across demographic groups. For example, older consumers tend to spend more on health care; also, poor consumers spend a higher proportion of their income on food and shelter. Because of these and other differences, examining disaggregated consumer sentiment survey data can provide us a more detailed picture of future expenditure. Beyond predicting expenditure, household-level sentiment data tell us something about the current welfare of vulnerable populations. There is increasing evidence that consumer expectations vary systematically across demographic and socioeconomic groups. As policymakers seek to better understand the economic experiences of various societal groups over the business cycle, disaggregated consumer sentiment data can be a useful tool. For example, if a certain subpopulation expresses pessimism about general business conditions during an economic recovery or growth period, there is good reason to think that the benefits of economic expansion may not be reaching that group. These insights can inform policy initiatives aimed at assisting these populations. In this article, we use household micro-level data to investigate the determinants of consumer sentiment. We use data from the University of Michigan's Storeys of Consumers, grouping respondents by characteristics such as race, ethnicity, gender, and income, among others. (1) We examine responses to the questions that go into calculating the University of Michigan's Index of Consumer Sentiment, as well as responses to other questions in the survey. One important finding is that sentiment differences across groups persist regardless of whether the question asks about personal situations or general situations--that is, groups have different views not only of their own outlook, but of the outlook for the country as a whole. We look into consumers' explanations of their sentiment to investigate why this is, considering group-level subjective experiences and differences in information sets across individuals as possible explanations for this gap in sentiment. We proceed with a brief literature review that outlines the basic theoretical framework for understanding the relationship between consumer sentiment and consumer behavior. Then we provide a description of how consumer sentiment is measured. After this, we continue with an analysis of the variations in sentiment across groups, while exploring explanations for the differences. …
Publication Year: 2006
Publication Date: 2006-03-22
Language: en
Type: article
Access and Citation
Cited By Count: 10
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot