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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.
Der Potsdam Grievance Statistics File (PGSF) ist eine historische Datensammlung von Beschwerden, sog. Eingaben, die in der DDR von deren Bürgern eingereicht wurden. Die Eingaben wurden schriftlich oder mündlich gestellt und waren an staatliche Institutionen gerichtet. Der Staat zählte diese Eingaben und kategorisierte sie in Eingabenstatistiken.
Der PGSF enthält Eingabenstatistiken des Zeitraums 1970–1989 einer Wahrscheinlichkeitsstichprobe von im Jahr 1990 existierenden Kreisen. Zusätzlich finden sich Eingabenstatistiken eines Convenience-Samples von Kreisen aus dem Zeitraum 1970–1989.
Der Potsdam Grievance Statistics File (PGSF) ist eine historische Datensammlung von Beschwerden, sog. Eingaben, die in der DDR von deren Bürgern eingereicht wurden. Die Eingaben wurden schriftlich oder mündlich gestellt und waren an staatliche Institutionen gerichtet. Der Staat zählte diese Eingaben und kategorisierte sie in Eingabenstatistiken.
Der PGSF enthält Eingabenstatistiken des Zeitraums 1970–1989 einer Wahrscheinlichkeitsstichprobe von im Jahr 1990 existierenden Kreisen. Zusätzlich finden sich Eingabenstatistiken eines Convenience-Samples von Kreisen aus dem Zeitraum 1970–1989.
Leben in der ehemaligen DDR
(2020)
Leben in der ehemaligen DDR
(2019)
Variance Inflation Factor
(2015)
Cook’s Distanz
(2015)
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.
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.
Component-Plus-Residual Plot
(2015)
Homoskedastizität
(2015)
Added Variable Plot
(2015)
DFbeta
(2015)
Optimal Matching
(2015)
Sequenzanalyse [1]
(2015)
Regressionsdiagnostik
(2015)
Q-Q-Plot
(2015)
P-P-Plot
(2015)
Lowess
(2015)
Datenanalyse mit Stata
(2016)
Dieses Buch bietet eine Einführung in das Datenanalysepaket Stata und ist zugleich das einzige Buch über Stata, das auch Anfängern eine ausreichende Erklärung statistischer Verfahren liefert. „Datenanalyse mit Stata' ist kein Befehls-Handbuch sondern erläutert alle Schritte einer Datenanalyse an praktischen Beispielen. Die Beispiele beziehen sich auf Themen der öffentlichen Diskussion oder der direkten Umgebung der meisten Leser. Damit eignet sich diese Buch als Einstieg in Data Analytics in allen Disziplinen.
Die neue Auflage bietet einen systematischeren Zugang zum Datenmanagement in Gegenwart von „Missing Values' und behandelt die in der Stata-Programmversion 14 implementierte Unicode-Codierung.
Sunflower plot
(2015)
A review of all research papers published in the European Sociological Review in 2016 and 2017 (N = 118) shows that only a minority of papers clearly define the parameter of interest and provide sufficient reasoning for the selected control variables of the statistical analysis. Thus, the vast majority of papers does not reach minimal standards for the selection of control variables. Consequently, a majority of papers interpret biased coefficients, or statistics without proper sociological meaning. We postulate that authors and reviewers should be more careful about control variable selection. We propose graphical causal models in the form of directed acyclic graphs as an example for a parsimonious and powerful means to that end.
The US perennially has a far higher poverty rate than peer-rich democracies.1 This high poverty rate in the US presents an enormous challenge to population health given that considerable research demonstrates that being in poverty is bad for one’s health.2 Despite valuable contributions of prior research on income and mortality, the quantity of mortality associated with poverty in the US remains uknown. In this cohort study, we estimated the association between poverty and mortality and quantified the proportion and number of deaths associated with poverty.
Pioneering scholarship links retrospective childhood conditions to mature adult health. We distinctively provide critical evidence with prospective state-of-the-art measures of parent income observed multiple times during childhood in the 1970s to 1990s. Using the Panel Study of Income Dynamics, we analyze six health outcomes (self-rated health, heart attack, stroke, life-threatening chronic conditions, non-life-threatening chronic conditions, and psychological distress) among 40- to 65-year-olds. Parent relative income rank has statistically and substantively significant relationships with five of six outcomes. The relationships with heart attack, stroke, and life-threatening chronic conditions are particularly strong. Parent income rank performs slightly better than alternative prospective and retrospective measures. At the same time, we provide novel validation on which retrospective measures (i.e., father’s education) perform almost as well as prospective measures. Furthermore, we inform several perennial debates about how relative versus absolute income and other measures of socioeconomic status and social class influence health.
Vast racial inequalities continue to prevail across the United States and are closely linked to economic resources. One particularly prominent argument contends that childhood wealth accounts for black–white (BW) disadvantages in life chances. This article analyzes how much childhood wealth and childhood income mediate BW disadvantages in adult life chances with Panel Study of Income Dynamics and Cross-National Equivalent File data on children from the 1980s and 1990s who were 30+ years old in 2015. Compared with previous research, we exploit longer panel data, more comprehensively assess adult life chances with 18 outcomes, and measure income and wealth more rigorously. We find large BW disadvantages in most outcomes. Childhood wealth and income mediate a substantial share of most BW disadvantages, although there are several significant BW disadvantages even after adjusting for childhood wealth and income. The evidence mostly contradicts the prominent claim that childhood wealth is more important than childhood income. Indeed, the analyses mostly show that childhood income explains more of BW disadvantages and has larger standardized coefficients than childhood wealth. We also show how limitations in prior wealth research explain why our conclusions differ. Replication with the National Longitudinal Survey of Youth and a variety of robustness checks support these conclusions.
In times of educational expansion, privileged families are looking for new strategies of distinction. Referring to Pierre Bourdieu’s theory of distinction, we argue that choosing Latin at school – a language that is no longer spoken and therefore has no direct value – is one of the strategies of privileged families to set themselves apart from less privileged families. Based on two surveys we conducted at German schools, the paper analyzes the relationship between parents’ educational background and the probability that their child will learn Latin. Results indicate that historically academic families have the strongest tendency towards learning Latin, followed by new academic families, and leaving behind the non-academic families. We distinguish between four causal mechanisms that might help to explain these associations: cultural distinction, selecting a socially exclusive learning environment, beliefs in a secondary instrumental function of learning Latin, and spatial proximity between the location of humanist Gymnasiums and the residential areas of privileged families. The hypotheses are formalized by means of Directed Acyclic Graphs (DAG). Findings show that the decision to learn Latin is predominately an unintended consequence of the selection of a socially exclusive learning environment. In addition, there is evidence that especially children from historically academic families learn Latin as a strategy of cultural distinction.
Emerging evidence has highlighted the important role of local contexts for integration trajectories of asylum seekers and refugees. Germany's policy of randomly allocating asylum seekers across Germany may advantage some and disadvantage others in terms of opportunities for equal participation in society. This study explores the question whether asylum seekers that have been allocated to rural areas experience disadvantages in terms of language acquisition compared to those allocated to urban areas. We derive testable assumptions using a Directed Acyclic Graph (DAG) which are then tested using large-N survey data (IAB-BAMF-SOEP refugee survey). We find that living in a rural area has no negative total effect on language skills. Further the findings suggest that the "null effect" is the result of two processes which offset each other: while asylum seekers in rural areas have slightly lower access for formal, federally organized language courses, they have more regular exposure to German speakers.
Im Vergleich zu Umfragen an Wahrscheinlichkeitsstichproben bieten Umfragen an Access-Panels, die auf Nicht-Wahrscheinlichkeitsstichproben basieren, unbestreitbare wirtschaftliche Vorteile. Diese Vorteile gehen jedoch mit unvermeidbaren Qualitätseinbußen einher, die auch dann bestehen bleiben, wenn Erstere sehr niedrige Responseraten haben. Daher müssen die wirtschaftlichen Vorteile und die methodischen Einschränkungen gegeneinander abgewogen werden. Es wird argumentiert, dass diese Abwägung anhand normativer Festlegungen erfolgen muss. Unter Anwendung der hier vorgeschlagenen Maßstäbe kommt der Beitrag zu dem Schluss, dass die Qualitätsansprüche an über Massenmedien verbreitete Meinungsumfragen höher sein sollten als für rein (sozial)wissenschaftliche Zwecke.
Pulp Science?
(2023)
Was sollten Mitarbeiter in einem empirisch ausgerichteten Forschungsprojekt können, und welche Kernkompetenzen sollte die Ausbildung an den Universitäten daher vermitteln? Die Antworten auf diese Fragen hängen – wie sollte es anders sein – von der inhaltlichen Fragestellung und methodischen Ausrichtung des jeweiligen Forschungsprojektes ab. Natürlich sollten Projektmitarbeiter über Vorkenntnisse zum Forschungsthema verfügen. Natürlich sollten Kenntnisse des projektspezifischen (statistischen) Methodenarsenals vorliegen.
The long term relationship between Medicaid expansion and adult life-threatening chronic conditions
(2023)
We test whether the expansions of children's Medicaid eligibility in the 1980s–1990s resulted in long-term health benefits in terms of severe chronic conditions. Still relatively rare in the field, we use prospective individual-level panel data from the Panel Study of Income Dynamics (PSID) along with the higher quality income measures from the Cross-National Equivalent File (adjusting for taxes, transfers and household size). We observe severe chronic conditions (high blood pressure/heart disease, cancer, diabetes, or lung disease) at ages 30–56 (average age 43.1) for 4670 respondents who were also prospectively observed during childhood (i.e., at ages 0–17). Our analysis exploits within-region temporal variation in childhood Medicaid eligibility and adjusts for state- and individual-level controls. We uniquely concentrate attention on adjusting for childhood income. A standard deviation greater childhood Medicaid eligibility significantly reduces the probability of severe chronic conditions in adulthood by 0.05 to 0.12 (16%–37.5% reduction from mean 0.32). Across the range of observed childhood Medicaid eligibility, the probability is approximately cut in half. Greater childhood Medicaid eligibility also substantially reduces childhood income disparities in severe chronic conditions. At higher levels of childhood Medicaid eligibility, we find no significant childhood income disparities in adult severe chronic conditions.
Is There a Rural Penalty in Language Acquisition? Evidence From Germany's Refugee Allocation Policy
(2022)
Emerging evidence has highlighted the important role of local contexts for integration trajectories of asylum seekers and refugees. Germany's policy of randomly allocating asylum seekers across Germany may advantage some and disadvantage others in terms of opportunities for equal participation in society. This study explores the question whether asylum seekers that have been allocated to rural areas experience disadvantages in terms of language acquisition compared to those allocated to urban areas. We derive testable assumptions using a Directed Acyclic Graph (DAG) which are then tested using large-N survey data (IAB-BAMF-SOEP refugee survey). We find that living in a rural area has no negative total effect on language skills. Further the findings suggest that the “null effect” is the result of two processes which offset each other: while asylum seekers in rural areas have slightly lower access for formal, federally organized language courses, they have more regular exposure to German speakers.
Is There a Rural Penalty in Language Acquisition? Evidence From Germany's Refugee Allocation Policy
(2022)
Emerging evidence has highlighted the important role of local contexts for integration trajectories of asylum seekers and refugees. Germany's policy of randomly allocating asylum seekers across Germany may advantage some and disadvantage others in terms of opportunities for equal participation in society. This study explores the question whether asylum seekers that have been allocated to rural areas experience disadvantages in terms of language acquisition compared to those allocated to urban areas. We derive testable assumptions using a Directed Acyclic Graph (DAG) which are then tested using large-N survey data (IAB-BAMF-SOEP refugee survey). We find that living in a rural area has no negative total effect on language skills. Further the findings suggest that the “null effect” is the result of two processes which offset each other: while asylum seekers in rural areas have slightly lower access for formal, federally organized language courses, they have more regular exposure to German speakers.
Since COVID-19 became a pandemic, many studies are being conducted to get a better understanding of the disease itself and its spread. One crucial indicator is the prevalence of SARS-CoV-2 infections. Since this measure is an important foundation for political decisions, its estimate must be reliable and unbiased. This paper presents reasons for biases in prevalence estimates due to unit nonresponse in typical studies. Since it is difficult to avoid bias in situations with mostly unknown nonresponse mechanisms, we propose the maximum amount of bias as one measure to assess the uncertainty due to nonresponse. An interactive web application is presented that calculates the limits of such a conservative unit nonresponse confidence interval (CUNCI).