@article{Kohler2019,
  author    = {Kohler, Ulrich},
  title     = {Possible uses of nonprobability sampling for the social sciences},
  series = {Survey methods : insights from the field},
  journal   = {Survey methods : insights from the field},
  publisher = {Swiss Found. for Research in Social Sciences},
  address   = {Lausanne},
  issn      = {2296-4754},
  doi       = {10.13094/SMIF-2019-00014},
  pages     = {13},
  year      = {2019},
  abstract  = {This paper compares the usability of data stemming from probability sampling with data stemming from nonprobability sampling. It develops six research scenarios that differ in their research goals and assumptions about the data generating process. It is shown that inferences from data stemming from nonprobability sampling implies demanding assumptions on the homogeneity of the units being studied. Researchers who are not willing to pose these assumptions are generally better off using data from probability sampling, regardless of the amount of nonresponse. However, even in cases when data from probability sampling is clearly advertised, data stemming from nonprobability sampling may contribute to the cumulative scientific endeavour of pinpointing a plausible interval for the parameter of interest.},
  language  = {en}
}
@phdthesis{Tuebbicke2020,
  author    = {T{\"u}bbicke, Stefan},
  title     = {Essays on start-up subsidies for the unemployed and methods for causal inference},
  doi       = {10.25932/publishup-47793},
  school      = {Universit{\"a}t Potsdam},
  pages     = {191},
  year      = {2020},
  abstract  = {This thesis offers new insights on the effects of Start-Up Subsidies (SUS) for unemployed individuals as a special kind of active labor market program (ALMP) that aims to re-integrate individuals into the labor market via the route of self-employment. Moreover, this thesis contributes to the literature on methods for causal inference when the treatment variable is continuous rather than binary. For example, this is the case when individuals differ in their degree of exposure to a common treatment. The analysis of the effects of SUS focuses on the main current German program called "Gr{\"u}ndungszuschuss" (New Start-Up Subsidy, NSUS) after its reform in 2011. Average Effects on participants' labor market outcomes - as measured by employment and earnings - as well as subjective well-being are estimated mainly based on propensity score matching (PSM) techniques. PSM aims to achieve balance in terms of observed characteristics by matching participants with at least one comparable non-participant in terms of their probability to receive the treatment. This estimation strategy is valid as long as all relevant characteristics that explain selection patterns into treatment are observed and included in the estimation of the propensity score. To make our analysis as credible as possible, we control for a large vector of characteristics as observed through the combination of rich administrative data from the Federal Employment Agency as well as through survey data. Chapters two to four of this thesis puts special emphasis on aspects regarding (the evaluation of) SUS programs that have received no or only limited attention thus far. The first aspect relates to the interplay of institutional details of the program and its effectiveness. So far, relatively little is known about the importance of SUS program features such as the duration of support. Second, there is no experimental benchmark evaluation of SUS available and thus, the reliability of non-experimental estimation techniques such as PSM is of crucial importance as estimates are biased when relevant confounders are omitted from the analysis. Third, there may be potentially detrimental effects of transitioning into (relatively risky) self-employment on subjective well-being among subsidized founders out of unemployment. These were to remain undetected if the analysis would focus exclusively on labor market outcomes of participants. The results indicate positive long-term effects of SUS participation on employment and earnings among participants. These effects are substantially larger than what estimated before the reform, indicating room for improvement in program design via changes in institutional details. Moreover, non-experimental estimates of treatment effects are remarkably robust to hidden confounding. Regarding subjective well-being, this thesis finds a positive long-run impact on job satisfaction and a detrimental effect on satisfaction with social security. The latter appears to be driven by adverse effects on social insurance contributions. In chapter five, a novel automated covariate balancing technique for the estimation of causal effects in the context of continuous treatments is derived and assessed regarding its performance compared to other (automated) balancing techniques. Although binary research designs that only differentiate between participants and non-participants of some treatment remain the most-common case in empirical practice, many applications can be adapted to include continuous treatments as well. Often, this will allow for more meaningful estimates of causal effects in order to further improve the design of programs. In the context of SUS, one may further investigate the effects of the size of monetary support or its duration on participants' labor market outcomes. Both Monte-Carlo investigations and analysis of two well-known datasets suggests superior performance of the proposed Entropy Balancing for continuous treatments (EBCT) compared to other existing estimation strategies.},
  language  = {en}
}
@article{HelbigBaierKroth2012,
  author    = {Helbig, Marcel and Baier, Tina and Kroth, Anna},
  title     = {The Effect of Tuition Fees on Enrollment in Higher Education in Germany. Evidence from a Natural Experiment},
  series = {ZEITSCHRIFT FUR SOZIOLOGIE},
  volume    = {41},
  journal   = {ZEITSCHRIFT FUR SOZIOLOGIE},
  number    = {3},
  publisher = {LUCIUS LUCIUS VERLAG MBH},
  address   = {STUTTGART},
  issn      = {0340-1804},
  pages     = {227 -- 246},
  year      = {2012},
  abstract  = {In this paper we estimate the effect of tuition fees on the intentions of high school graduates in Germany to enroll in higher education. Based on representative survey data collected by the HIS institute between 2002 and 2008, we are able to analyze the effect of tuition fees using a quasi-experimental design. We take advantage of the variation between the German federal states in the introduction of tuition fees to examine the impact of tuition fees and employ a difference-in-differences estimation strategy. We do not find empirical evidence that tuition fees lower the intentions to enroll in higher education among high school graduates. This holds true for both the whole sample and for different subgroups, such as women or high school graduates with no family background of higher education.},
  language  = {de}
}