Investigating American Optimism: Evidence from 2022 General Social Survey (GSS) Data

Oregon Convention Center 

In this cross-sectional study, we delve into how a person's characteristics contribute to their degree of optimism, in terms of happiness, how exciting their life is, and how fair they perceive the world around them, drawing on data from the most recent wave of the General Social Survey conducted in 2022. Our exploration is motivated by the findings of Smith (2005), who examined various dimensions of "troubles in America," including health, work, finances, material hardships, family/personal, law and crime, housing, and miscellaneous domains. Our underlying hypothesis posits that specific characteristics of a person (or group of people) may be able to predict their degree of optimism. We screen potential predictors using preliminary tests for association to see if there is any significance among the specific factors prior to including them in the model. Utilizing ordinal logistic regression and leveraging a substantial volume of survey responses, we scrutinize the intricate relationships among these domains. The model incorporates demographic variables and various personal characteristics to estimate their effects on degree of optimism and provided the bootstrap confidence interval for the estimates. We studied the interaction effects of different characteristics on the response variables and found significant interactions. In response to the large amounts of missing-at-random data, this study investigates the extent to which data imputation techniques can be utilized for further analysis.

Ordinal Logistic Regression

Data-Imputation

Optimism

General Social Survey (GSS)

Categorical Data

Cross-sectional 

Section on Statistical Computing