Abstract
This is the third chapter of Part IV, focusing on the analysis of the Self-Assessed Measure (economic strain: difficulties in making ends meet) of economic vulnerability and its distinctiveness from the Objective Measure (income poverty). Understanding the relationship between the Self-Assessed Measure and economic resources is particularly relevant with regard to the hypothesis that the subjective difficulties in making ends meet may capture differences in the ability to cope with low monthly income. Wealth consumption has previously been mentioned as one of the coping strategies that moderates the level of economic strain an individual experiences at a given level of income. The question is in what way monthly household income and household wealth interact in their effect on self-assessed economic vulnerability. In the following, we will estimate multiple models in order to test competing concepts for the relationship between the three variables. The models were performed using maximum likelihood estimation since all variables follow a normal distribution.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The Stata command for this SEM option is > method(ml).
- 2.
In contrast to a mediator variable that explains the relationship between two variables, a moderator variable is one that influences the strength of a relationship between a predictor and a dependent variable. This influence is also referred to as a statistical ‘interaction effect’ (Baron and Kenny 1986). According to Holmbeck (1997), a mediational model attempts to respond to the following questions: how (by what means) does an effect occur or what accounts for the impact of A (predictor) on C (dependent variable). A mediational model is therefore a causal model, whereby it is hypothesized that A ‘causes’ B and that B then ‘causes’ C. In contrast, a moderational model examines the following: when (under what conditions) does the effect occur or under what conditions of B (moderator variable) is A (predictor) significantly associated with C (dependent variable) (Holmbeck 1997).
- 3.
This figure was drawn freehand because the Stata SEM-builder is unable to graphically represent this type of model.
- 4.
The standardized beta coefficients vary by a maximum of 0.03.
- 5.
Since the model is just identified, it is not possible to calculate any other fit statistics.
References
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.
Holmbeck, G. N. (1997). Toward terminological, conceptual, and statistical clarity in the study of mediators and moderators: Examples from the child-clinical and pediatric psychology literatures. Journal of Consulting and Clinical Psychology, 65(4), 599–610.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Henke, J. (2020). Exploring the Relationship Between Economic Resources and the Self-Assessed Measure of Economic Vulnerability. In: Revisiting Economic Vulnerability in Old Age. Life Course Research and Social Policies, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-030-36323-9_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-36323-9_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-36322-2
Online ISBN: 978-3-030-36323-9
eBook Packages: Economics and FinanceEconomics and Finance (R0)