TY  - JOUR
A1  - Sorgner, Alina
A1  - Fritsch, Michael
A1  - Kritikos, Alexander
T1  - Do entrepreneurs really earn less?
JF  - Small business economics : an international journal
N2  - Based on large representative German household survey data, we compare incomes of the self-employed with those of paid employees. We find that the entrepreneurial income gap is largest for those holding a tertiary degree, but in two directions: positive for employers (self-employed with further employees) and negative for solo entrepreneurs. Entrepreneurs holding a tertiary degree also face the greatest income variation. However, some solo self-employed earn more than their employed counterparts, in particular those with a university entrance degree as the highest level of education.
KW  - Income
KW  - Entrepreneurship
KW  - Self-employment
KW  - Germany
Y1  - 2017
U6  - https://doi.org/10.1007/s11187-017-9874-6
SN  - 0921-898X
SN  - 1573-0913
VL  - 49
SP  - 251
EP  - 272
PB  - Springer
CY  - Dordrecht
ER  - 
TY  - JOUR
A1  - Fliesser, Michael
A1  - De Witt Huberts, Jessie
A1  - Wippert, Pia-Maria
T1  - The choice that matters: the relative influence of socioeconomic status indicators on chronic back pain
BT  - a longitudinal study
JF  - BMC health services research
N2  - Background

In health research, indicators of socioeconomic status (SES) are often used interchangeably and often lack theoretical foundation. This makes it difficult to compare results from different studies and to explore the relationship between SES and health outcomes. To aid researchers in choosing appropriate indicators of SES, this article proposes and tests a theory-based selection of SES indicators using chronic back pain as a health outcome.
Methods

Strength of relationship predictions were made using Brunner & Marmot’s model of ‘social determinants of health’. Subsequently, a longitudinal study was conducted with 66 patients receiving in-patient treatment for chronic back pain. Sociodemographic variables, four SES indicators (education, job position, income, multidimensional index) and back pain intensity and disability were obtained at baseline. Both pain dimensions were assessed again 6 months later. Using linear regression, the predictive strength of each SES indicator on pain intensity and disability was estimated and compared to the theory based prediction.
Results

Chronic back pain intensity was best predicted by the multidimensional index (beta = 0.31, p < 0.05), followed by job position (beta = 0.29, p < 0.05) and education (beta = −0.29, p < 0.05); whereas, income exerted no significant influence. Back pain disability was predicted strongest by education (beta = −0.30, p < 0.05) and job position (beta = 0.29, p < 0.05). Here, multidimensional index and income had no significant influence.
Conclusions

The choice of SES indicators influences predictive power on both back pain dimensions, suggesting SES predictors cannot be used interchangeably. Therefore, researchers should carefully consider prior to each study which SES indicator to use. The introduced framework can be valuable in supporting this decision because it allows for a stable prediction of SES indicator influence and their hierarchy on a specific health outcomes.
KW  - Socioeconomic status
KW  - Indicators of socioeconomic status, Health inequality
KW  - Education
KW  - Job position
KW  - Income
KW  - Chronic back pain
Y1  - 2017
U6  - https://doi.org/10.1186/s12913-017-2735-9
SN  - 1472-6963
VL  - 17
PB  - BioMed Central
CY  - London
ER  -