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@article{ Lehmann2024,
 title = {Analyzing the Causal Effect of Obesity on Socioeconomic Status - the Case for Using Difference-in-Differences Estimates in Addition to Fixed Effects Models},
 author = {Lehmann, Judith},
 journal = {Methods, data, analyses : a journal for quantitative methods and survey methodology (mda)},
 number = {1},
 pages = {33-58},
 volume = {18},
 year = {2024},
 issn = {2190-4936},
 doi = {https://doi.org/10.12758/mda.2022.14},
 abstract = {Recent studies use Fixed Effects (FE) models to estimate the causal effect of obesity on socioeconomic status, the so-called obesity penalty. In this paper, I will illustrate the ad­vantages of using a Difference in Differences (DID) approach as an alternative method of causal analysis. Combining the German National Health Interview and Examination Survey 1998 (GNHIES98) and the German Health Interview and Examination Survey for Adults 2008 (DEGS1) allowed for a panel analysis of 3934 respondents. The dependent variable is a socioeconomic status score that integrates level of education, occupation and household income. The binary treatment variable is abdominal obesity. To estimate the causal effect of the treatment, FE and DID approaches were used. Both the FE model and the DID estimate show no statistically significant causal ef­fect of abdominal obesity on socioeconomic status for adults in Germany. However, both the respondents who became obese and those who stayed non-obese experience a rise in socioeconomic status over time. Nonetheless, the non-obese group had a more substantial increase in socioeconomic status than the obese group. Therefore, the obesity penalty does not necessarily have to be a decrease in socioeconomic status but could instead be a slowed growth or stagnation in status. The advantage of the DID approach is that the development in the control group is explicit. If obese individuals are more likely to have less favorable positive trends in socioeconomic status over time than other individuals, using DID esti­mates demonstrates the obesity penalty more effectively than using only FE models.},
 keywords = {Übergewicht; overweight; Fettsucht; adipositas; sozioökonomische Folgen; socioeconomic effects; Schätzung; estimation; Kausalanalyse; causal analysis; Längsschnittuntersuchung; longitudinal study}}