Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Social Welfare

First Advisor's Name

Mario De La Rosa

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Richard Beaulaurier

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Mark Macgowan

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

WeiWei Chen

Fourth Advisor's Committee Title

Committee Member

Keywords

social work

Date of Defense

11-2-2021

Abstract

This investigation contributed to the literature by advancing scientific inquiry and addressing the gap in the literature related to social and economic mobility among Hispanic female householders living in the United States. The dissertation achieved its proposed aims by conducting secondary data analysis of the Integrated Public Use Microdata Series – Current Population Survey, Annual Social and Economic Supplement dataset (Flood, Kind, Rodgers, Ruggles, & Warren, 2020). The investigator applied repeated cross-sectional design to make inferences at the aggregate population level and conceptually frame analysis of a nationally representative sample of Hispanic female householders' a decade after the Great Recession by analyzing ten years of data from 2009-2019.

All interpretations and inferences of results are based on an aggregated view of the target population. Findings were tested at a minimum of the .05 level of significance and 95% confidence intervals. Total sample for analysis includes (N= 58,135,354) participants, (N=33,323,878) Native-born, and Foreign-born (N=24,811,476). The framework for analysis includes descriptive analysis, univariate analysis of sociodemographic predictor variables, bivariate regression analysis, multivariate linear regression analysis, and moderation analysis to determine the impact of sociodemographic predictors (i.e., educational attainment, labor attachment, and geographic region of residence) and moderating variables (i.e., presence of children and presence of disability) on total pre-tax personal income (i.e., income attainment), the outcome variable.

Bivariate regression analysis of education and labor correlates on the total pre-tax income revealed significant (P

Identifier

FIDC010104

ORCID

https://orcid.org/0000-0002-0930-0347

Included in

Social Work Commons

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