@article{ClassKoehlerKrawietz2018,
  author    = {Class, Fabian and K{\"o}hler, Ulrich and Krawietz, Marian},
  title     = {The Potsdam Grievance Statistics File},
  series = {Historical Methods},
  volume    = {51},
  journal   = {Historical Methods},
  number    = {2},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {0161-5440},
  doi       = {10.1080/01615440.2018.1429970},
  pages     = {92 -- 114},
  year      = {2018},
  abstract  = {The newly collected Potsdam Grievance Statistics File (PGSF) holds data on the number and topics of grievances (Eingaben) that were addressed to local authorities of the German Democratic Republic (GDR) in the years 1970 to 1989. The PGSF allows quantitative analyses on topics such as participation, quality of life, and value change in the German Democratic Republic. This paper introduces the concepts of the data set and discusses the validity of its contents.},
  language  = {en}
}
@article{BradyGiesselmannKohleretal.2018,
  author    = {Brady, David and Giesselmann, Marco and Kohler, Ulrich and Radenacker, Anke},
  title     = {How to measure and proxy permanent income},
  series = {The Journal of Economic Inequality},
  volume    = {16},
  journal   = {The Journal of Economic Inequality},
  number    = {3},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1569-1721},
  doi       = {10.1007/s10888-017-9363-9},
  pages     = {321 -- 345},
  year      = {2018},
  abstract  = {Permanent income (PI) is an enduring concept in the social sciences and is highly relevant to the study of inequality. Nevertheless, there has been insufficient progress in measuring PI. We calculate a novel measure of PI with the German Socio-Economic Panel (SOEP) and U.S. Panel Study of Income Dynamics (PSID). Advancing beyond prior approaches, we define PI as the logged average of 20+ years of post-tax and post-transfer ("post-fisc") real equivalized household income. We then assess how well various household- and individual-based measures of economic resources proxy PI. In both datasets, post-fisc household income is the best proxy. One random year of post-fisc household income explains about half of the variation in PI, and 2-5 years explain the vast majority of the variation. One year of post-fisc HH income even predicts PI better than 20+ years of individual labor market earnings or long-term net worth. By contrast, earnings, wealth, occupation, and class are weaker and less cross-nationally reliable proxies for PI. We also present strategies for proxying PI when HH post-fisc income data are unavailable, and show how post-fisc HH income proxies PI over the life cycle. In sum, we develop a novel approach to PI, systematically assess proxies for PI, and inform the measurement of economic resources more generally.},
  language  = {en}
}
@article{KohlerKreuterStuart2018,
  author    = {Kohler, Ulrich and Kreuter, Frauke and Stuart, Elizabeth A.},
  title     = {Nonprobability Sampling and Causal Analysis},
  series = {Annual review of statistics and its application},
  volume    = {6},
  journal   = {Annual review of statistics and its application},
  publisher = {Annual Reviews},
  address   = {Palo Alto},
  issn      = {2326-8298},
  doi       = {10.1146/annurev-statistics-030718-104951},
  pages     = {149 -- 172},
  year      = {2018},
  abstract  = {The long-standing approach of using probability samples in social science research has come under pressure through eroding survey response rates, advanced methodology, and easier access to large amounts of data. These factors, along with an increased awareness of the pitfalls of the nonequivalent comparison group design for the estimation of causal effects, have moved the attention of applied researchers away from issues of sampling and toward issues of identification. This article discusses the usability of samples with unknown selection probabilities for various research questions. In doing so, we review assumptions necessary for descriptive and causal inference and discuss research strategies developed to overcome sampling limitations.},
  language  = {en}
}
@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}
}
@article{HippKohlerLeumann2019,
  author    = {Hipp, Lena and Kohler, Ulrich and Leumann, Sandra},
  title     = {How to implement respondent-driven sampling in practice},
  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-2019-00009},
  pages     = {1 -- 13},
  year      = {2019},
  abstract  = {This article draws on the experience from an ongoing research project employing respondent-driven sampling (RDS) to survey (illicit) 24-hour home care workers. We highlight issues around the preparatory work and the fielding of the survey to provide researchers with useful insights on how to implement RDS when surveying populations for which the method has not yet been used. We conclude the article with ethical considerations that occur when employing RDS.},
  language  = {en}
}
@article{GerhardsSawertKohler2019,
  author    = {Gerhards, J{\"u}rgen and Sawert, Tim and Kohler, Ulrich},
  title     = {Des Kaisers alte Kleider: Fiktion und Wirklichkeit des Nutzens von Lateinkenntnissen},
  series = {K{\"o}lner Zeitschrift f{\"u}r Soziologie und Sozialpsychologie},
  volume    = {71},
  journal   = {K{\"o}lner Zeitschrift f{\"u}r Soziologie und Sozialpsychologie},
  number    = {2},
  publisher = {Springer},
  address   = {Wiesbaden},
  issn      = {0023-2653},
  doi       = {10.1007/s11577-019-00624-8},
  pages     = {309 -- 326},
  year      = {2019},
  abstract  = {Obwohl Latein eine nicht mehr gesprochene Sprache ist und ihr deswegen kein kommunikativer Nutzen zukommt, ist die Anzahl der Latein als Schulfach w{\"a}hlenden Sch{\"u}ler im Zeitverlauf angestiegen. Mehrere Studien haben zudem gezeigt, dass Lateinkenntnisse weder das logische Denken, noch den Erwerb anderer Sprachen, noch das Gesp{\"u}r f{\"u}r die grammatikalische Struktur der Muttersprache verbessern. Auch wenn sich empirisch keine Vorteile des Erwerbs alter Sprachen nachweisen lassen, k{\"o}nnen Menschen subjektiv an solche Vorteile glauben und ihr Verhalten an ihrer Konstruktion von Wirklichkeit ausrichten. Auf der Basis einer unter Eltern von Gymnasialsch{\"u}lern durchgef{\"u}hrten Befragung zeigen wir, dass Latein umfassende Transfereffekte zugeschrieben und Personen mit Lateinkenntnissen positiver bewertet werden als Personen mit Kenntnissen moderner Sprachen. Weiterhin zeigt sich, dass die „Illusio" der Vorteile von Latein zwar in allen Bildungsgruppen wirksam ist, doch besonders von den Hochgebildeten vertreten wird. Sie arbeiten damit an der Konstruktion einer Realit{\"a}t, von der sie selbst die gr{\"o}ßten Nutznießer sind, indem sie Latein als symbolisches Kapital verwenden.},
  language  = {de}
}
@misc{KrawietzGoebelAlbrechtetal.2019,
  author    = {Krawietz, Marian and Goebel, Jan and Albrecht, Sophia and Class, Fabian and Kohler, Ulrich},
  title     = {Leben in der ehemaligen DDR},
  publisher = {German Institute for Economic Research (DIW Berlin)},
  address   = {Berlin},
  doi       = {10.5684/soep.ddr18},
  year      = {2019},
  language  = {en}
}
@misc{Kohler2020,
  author    = {Kohler, Ulrich},
  title     = {Editorial: Survey Research Methods during the COVID-19 Crisis},
  series = {Survey Research Methods},
  volume    = {14},
  journal   = {Survey Research Methods},
  number    = {2},
  address   = {Konstanz},
  issn      = {1864-3361},
  doi       = {10.18148/srm/2020.v14i2.7769},
  pages     = {93 -- 94},
  year      = {2020},
  language  = {en}
}
@misc{KrawietzKohlerClassetal.2020,
  author    = {Krawietz, Marian and Kohler, Ulrich and Class, Fabian and Albrecht, Sophia and Feuerstein, Collin},
  title     = {The potsdam grievance statistic File (PGSF)},
  doi       = {10.4232/1.12993},
  year      = {2020},
  abstract  = {Der Potsdam Grievance Statistics File (PGSF) ist eine historische Datensammlung von Beschwerden, sog. Eingaben, die in der DDR von deren B{\"u}rgern eingereicht wurden. Die Eingaben wurden schriftlich oder m{\"u}ndlich gestellt und waren an staatliche Institutionen gerichtet. Der Staat z{\"a}hlte diese Eingaben und kategorisierte sie in Eingabenstatistiken. Der PGSF enth{\"a}lt Eingabenstatistiken des Zeitraums 1970-1989 einer Wahrscheinlichkeitsstichprobe von im Jahr 1990 existierenden Kreisen. Zus{\"a}tzlich finden sich Eingabenstatistiken eines Convenience-Samples von Kreisen aus dem Zeitraum 1970-1989.},
  language  = {de}
}
@misc{AlbrechtClassFeuersteinetal.2020,
  author    = {Albrecht, Sophia and Class, Fabian and Feuerstein, Collin and Kohler, Ulrich and Krawietz, Marian},
  title     = {The Potsdam grievance statistics file (PGSF)},
  doi       = {10.4232/1.13615},
  year      = {2020},
  abstract  = {Der Potsdam Grievance Statistics File (PGSF) ist eine historische Datensammlung von Beschwerden, sog. Eingaben, die in der DDR von deren B{\"u}rgern eingereicht wurden. Die Eingaben wurden schriftlich oder m{\"u}ndlich gestellt und waren an staatliche Institutionen gerichtet. Der Staat z{\"a}hlte diese Eingaben und kategorisierte sie in Eingabenstatistiken. Der PGSF enth{\"a}lt Eingabenstatistiken des Zeitraums 1970-1989 einer Wahrscheinlichkeitsstichprobe von im Jahr 1990 existierenden Kreisen. Zus{\"a}tzlich finden sich Eingabenstatistiken eines Convenience-Samples von Kreisen aus dem Zeitraum 1970-1989.},
  language  = {de}
}