@techreport{GraeberHilbertKoenig2023,
  type      = {Working Paper},
  author    = {Graeber, Daniel and Hilbert, Viola and K{\"o}nig, Johannes},
  title     = {Inequality of Opportunity in Wealth},
  series = {CEPA Discussion Papers},
  journal   = {CEPA Discussion Papers},
  number    = {69},
  issn      = {2628-653X},
  doi       = {10.25932/publishup-60967},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-609673},
  pages     = {54},
  year      = {2023},
  abstract  = {While inequality of opportunity (IOp) in earnings is well studied, the literature on IOp in individual net wealth is scarce to non-existent. This is problematic because both theoretical and empirical evidence show that the position in the wealth and income distribution can significantly diverge.We measure ex-ante IOp in net wealth for Germany using data from the Socio-Economic Panel (SOEP). Ex-ante IOp is defined as the contribution of circumstances to the inequality in net wealth before effort is exerted. The SOEP allows for a direct mapping from individual circumstances to individual net wealth and for a detailed decomposition of net wealth inequality into a variety of circumstances; among them childhood background, intergenerational transfers, and regional characteristics. The ratio of inequality of opportunity to total inequality is stable from 2002 to 2019. This is in sharp contrast to labor earnings, where ex-ante IOp is declining over time. Our estimates suggest that about 62\% of the inequality in net wealth is due to circumstances. The most important circumstances are intergenerational transfers, parental occupation, and the region of birth. In contrast, gender and individuals' own education are the most important circumstances for earnings.},
  language  = {en}
}
@phdthesis{Krummenauer2022,
  author    = {Krummenauer, Linda},
  title     = {Global heat adaptation among urban populations and its evolution under different climate futures},
  doi       = {10.25932/publishup-55929},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-559294},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 161},
  year      = {2022},
  abstract  = {Heat and increasing ambient temperatures under climate change represent a serious threat to human health in cities. Heat exposure has been studied extensively at a global scale. Studies comparing a defined temperature threshold with the future daytime temperature during a certain period of time, had concluded an increase in threat to human health. Such findings however do not explicitly account for possible changes in future human heat adaptation and might even overestimate heat exposure. Thus, heat adaptation and its development is still unclear. Human heat adaptation refers to the local temperature to which populations are adjusted to. It can be inferred from the lowest point of the U- or V-shaped heat-mortality relationship (HMR), the Minimum Mortality Temperature (MMT). While epidemiological studies inform on the MMT at the city scale for case studies, a general model applicable at the global scale to infer on temporal change in MMTs had not yet been realised. The conventional approach depends on data availability, their robustness, and on the access to daily mortality records at the city scale. Thorough analysis however must account for future changes in the MMT as heat adaptation happens partially passively. Human heat adaptation consists of two aspects: (1) the intensity of the heat hazard that is still tolerated by human populations, meaning the heat burden they can bear and (2) the wealth-induced technological, social and behavioural measures that can be employed to avoid heat exposure. The objective of this thesis is to investigate and quantify human heat adaptation among urban populations at a global scale under the current climate and to project future adaptation under climate change until the end of the century. To date, this has not yet been accomplished. The evaluation of global heat adaptation among urban populations and its evolution under climate change comprises three levels of analysis. First, using the example of Germany, the MMT is calculated at the city level by applying the conventional method. Second, this thesis compiles a data pool of 400 urban MMTs to develop and train a new model capable of estimating MMTs on the basis of physical and socio-economic city characteristics using multivariate non-linear multivariate regression. The MMT is successfully described as a function of the current climate, the topography and the socio-economic standard, independently of daily mortality data for cities around the world. The city-specific MMT estimates represents a measure of human heat adaptation among the urban population. In a final third analysis, the model to derive human heat adaptation was adjusted to be driven by projected climate and socio-economic variables for the future. This allowed for estimation of the MMT and its change for 3 820 cities worldwide for different combinations of climate trajectories and socio-economic pathways until 2100. The knowledge on the evolution of heat adaptation in the future is a novelty as mostly heat exposure and its future development had been researched. In this work, changes in heat adaptation and exposure were analysed jointly. A wide range of possible health-related outcomes up to 2100 was the result, of which two scenarios with the highest socio-economic developments but opposing strong warming levels were highlighted for comparison. Strong economic growth based upon fossil fuel exploitation is associated with a high gain in heat adaptation, but may not be able to compensate for the associated negative health effects due to increased heat exposure in 30\% to 40\% of the cities investigated caused by severe climate change. A slightly less strong, but sustainable growth brings moderate gains in heat adaptation but a lower heat exposure and exposure reductions in 80\% to 84\% of the cities in terms of frequency (number of days exceeding the MMT) and intensity (magnitude of the MMT exceedance) due to a milder global warming. Choosing a 2 ° C compatible development by 2100 would therefore lower the risk of heat-related mortality at the end of the century. In summary, this thesis makes diverse and multidisciplinary contributions to a deeper understanding of human adaptation to heat under the current and the future climate. It is one of the first studies to carry out a systematic and statistical analysis of urban characteristics which are useful as MMT drivers to establish a generalised model of human heat adaptation, applicable at the global level. A broad range of possible heat-related health options for various future scenarios was shown for the first time. This work is of relevance for the assessment of heat-health impacts in regions where mortality data are not accessible or missing. The results are useful for health care planning at the meso- and macro-level and to urban- and climate change adaptation planning. Lastly, beyond having met the posed objective, this thesis advances research towards a global future impact assessment of heat on human health by providing an alternative method of MMT estimation, that is spatially and temporally flexible in its application.},
  language  = {en}
}
@article{BoewingSchmalenbrockJurczok2011,
  author    = {B{\"o}wing-Schmalenbrock, Melanie and Jurczok, Anne},
  title     = {Multiple Imputation in der Praxis : ein sozialwissenschaftliches Anwendungsbeispiel},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-58111},
  year      = {2011},
  abstract  = {Multiple Imputation hat sich in den letzten Jahren als ad{\"a}quate Methode zum Umgang mit fehlenden Werten erwiesen und etabliert. Das gilt zumindest f{\"u}r die Theorie, denn im Angesicht mangelnder anwendungsbezogener Erl{\"a}uterungen und Einf{\"u}hrungen verzichten in der Praxis viele Sozialwissenschaftler auf diese notwendige Datenaufbereitung. Trotz (oder vielleicht auch wegen) der stetig fortschreitenden Weiterentwicklung der Programme und Optionen zur Umsetzung Multipler Imputationen, sieht sich der Anwender mit zahlreichen Herausforderungen konfrontiert, f{\"u}r die er mitunter nur schwer L{\"o}sungsans{\"a}tze findet. Die Schwierigkeiten reichen von der Analyse und Aufbereitung der Zielvariablen, {\"u}ber die Software-Entscheidung, die Auswahl der Pr{\"a}diktoren bis hin zur Modell-Formulierung und Ergebnis-Evaluation. In diesem Beitrag wird die Funktionsweise und Anwendbarkeit Multipler Imputationen skizziert und es wird eine Herangehensweise entwickelt, die sich in der schrittweisen Umsetzung dieser Methode als n{\"u}tzlich erwiesen hat - auch f{\"u}r Einsteiger. Es werden konkrete potenzielle Schwierigkeiten angesprochen und m{\"o}gliche Probleml{\"o}sungen diskutiert; vor allem die jeweilige Beschaffenheit der fehlenden Werte steht hierbei im Vordergrund. Der Imputations-Prozess und alle mit ihm verbundenen Arbeitsschritte werden anhand eines Anwendungsbeispiels - der Multiplen Imputation des Gesamtverm{\"o}gens reicher Haushalte - exemplarisch illustriert.},
  language  = {de}
}