Identifying the Factors That Influence Changes in Aggregate Sentiment Among the Masses: An Analysis of the Measure of Consumer Sentiment Through a Conflict Analysis and Resolution Lens.

摘要

The University of Michigan's Survey Research Center developed a tool to quantify how people feel towards the state of the economy. Dr. George Katona, a psychologist and professor at the University of Michigan developed the Index of Consumer Sentiment (ICS) in the 1940s.;As decades of data were collected on aggregate consumer sentiment through the 50s and 60s, a discovery was made. The ICS seemed to indirectly predict the direction of the economy by accurately anticipating aggregate purchasing versus saving decisions. The index is even used today by the U.S. Government to measure consumer confidence and has been noted to give investors an unfair advantage if they have this information before others. The literature shows many researchers attempting to measure the index's predictive ability on consumer expenses, but little to none have conducted an in depth analysis on identifying which variables, experiences, and individual characteristics influence the ICS. This dissertation takes on a systems perspective to recognize that the economy is one large societal system; whereby, all members of society along all levels on the socioeconomic strata are interconnected and are in conflict with their needs and values.;A 45-question survey was distributed to a national sample of 535 participants. Participants from all states in the U.S. (except North Dakota), and including Puerto Rico were captured in the sample population. The survey identifies each participant's economic literacy, income levels, gender identities, political and religious affiliations, participant and parent's level of education, marital status, household size, employment status, news network preference, trust in the government, willingness to commit a crime in bad financial times, and personal experiences with foreclosure, bankruptcy and layoffs, among other variables. This quantitative methods research utilizes Spearman's rho correlation coefficient to identify the variables that are most statistically significant in influencing the ICS. The data show strong statistical significance among certain variables and the ICS (such as discretionary income, trust in the government, and news network preference), which further grounds the fact that consumers are easily conditioned and influenced by their environment.