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403 results, from 1
  • Externe referierte Aufsätze

    Multiple Imputation of Ordinal Missing Not at Random Data

    We introduce a selection model-based imputation approach to be used within the Fully Conditional Specification (FCS) framework for the Multiple Imputation (MI) of incomplete ordinal variables that are supposed to be Missing Not at Random (MNAR). Thereby, we generalise previous work on this topic which involved binary single-level and multilevel data to ordinal variables. We apply an ordered probit ...

    In: AStA Advances in Statistical Analysis (2023), im Ersch. [online first: 2022-08-22] | Angelina Hammon
  • Weitere externe Aufsätze

    Unsupervised Methods: Clustering Methods

    In: Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu, Lars Lyberg (Eds.) , Handbook of Computational Social Science Vol 2
    London : Routledge
    S. 334-351
    | Johann Bacher, Andreas Pöge and Knut Wenzig
  • Externe referierte Aufsätze

    Data on Digital Transformation in the German Socio-Economic Panel

    Public debates and current research on “digitalization” suggest that digital technologies could profoundly transform the world of work. While broad claims are common in these debates, empirical evidence remains scarce. This calls for reliable data for empirical research and evidence-based policymaking. We implemented a data module in the Socio-Economic Panel to gather information on digitalization ...

    In: Jahrbücher für Nationalökonomie und Statistik 242 (2022), 5-6, S. 691–705 | Alexandra Fedorets, Stefan Kirchner, Jule Adriaans, Oliver Giering
  • Externe referierte Aufsätze

    Grenzen und Fortschritte indikatorengestützter Politik am Beispiel der Corona-Pandemie: Heinz-Grohmann-Vorlesung 2020/21

    Indikatoren sollen der Steuerung von (sozialen) Prozessen dienen. Sie beschreiben jedoch die Realität in der Regel nur deskriptiv und unvermeidlich mit mehr oder weniger großen und systematischen Messfehlern behaftet. Insofern ist es im Allgemeinen alles andere als einfach mit Hilfe von Indikatoren zu steuern; insbesondere dann, wenn für Problembereiche (fehlerbehaftete) Zielwerte vorgegeben werden, ...

    In: AStA Advances in Statistical Analysis 16 (2022), S. 171–187 | Gert G. Wagner
  • Externe referierte Aufsätze

    Do Words Hurt More than Actions? The Impact of Trade Tensions on Financial Markets

    We use machine learning techniques to quantify trade tensions between the United States and China. Our measure matches well-known events in the US-China trade dispute and is exogenous to the developments on global financial markets. Local projections show that rising trade tensions leave US markets largely unaffected, except for firms that are more exposed to China, while negatively impacting stock ...

    In: Journal of Applied Econometrics 37 (2022), 6, S. 1138-1159 | Massimo Ferrari Minesso, Frederik Kurcz, Maria Sole Pagliari
  • Externe referierte Aufsätze

    Measurement Equivalence in Probability and Nonprobability Online Panels

    Nonprobability online panels are commonly used in the social sciences as a fast and inexpensive way of collecting data in contrast to more expensive probability-based panels. Given their ubiquitous use in social science research, a great deal of research is being undertaken to assess the properties of nonprobability panels relative to probability ones. Much of this research focuses on selection bias, ...

    In: International Journal of Market Research 64 (2022), 4, S. 484–505 | Hafsteinn Einarsson, Joseph W. Sakshaug, Alexandru Cernat, Carina Cornesse, Annelies G. Blom
  • Externe referierte Aufsätze

    Assessing the Value of Data for Prediction Policies: The Case of Antibiotic Prescribing

    We quantify the value of data for the prediction policy problem of reducing antibiotic prescribing to curb antibiotic resistance. Using varying combinations of administrative data, we evaluate machine learning predictions for diagnosing bacterial urinary tract infections and the outcomes of prescription rules based on these predictions. Simple patient demographics improve prediction quality substantially ...

    In: Economics Letters 213 (2022), 110360, 4 S. | Shan Huang, Michael Allan Ribers, Hannes Ullrich
  • Externe Monographien

    Setting Priorities, Pooling Resources and Accelerating Transformation: New Approaches in Industrial and Technology Policy

    Bonn: Friedrich-Ebert-Stiftung, 2021, 32 S.
    (WISO Diskurs : Expertisen und Dokumentationen zur Wirtschafts- und Sozialpolitik ; 2021,14)
    | Heike Belitz, Martin Gornig, Claudia Kemfert, Ralf Löckener, Torsten Sundmacher
  • Externe referierte Aufsätze

    The Early Bird Catches the Worm! Setting a Deadline for Online Panel Recruitment Incentives

    The literature on the effects of incentives in survey research is vast and covers a diversity of survey modes. The mode of probability-based online panels, however, is still young and so is research into how to best recruit sample units into the panel. This paper sheds light on the effectiveness of a specific type of incentive in this context: a monetary incentive that is paid conditionally upon panel ...

    In: Social Science Computer Review (2023), im Ersch. [online first: 2022-05-10] | Sabine Friedel, Barbara Felderer, Ulrich Krieger, Carina Cornesse, Annelies G. Blom
  • Externe referierte Aufsätze

    Renewable Energy Targets and Unintended Storage Cycling: Implications for Energy Modeling

    To decarbonize the economy, many governments have set targets for the use of renewable energy sources. These are often formulated as relative shares of electricity demand or supply. Implementing respective constraints in energy models is a surprisingly delicate issue. They may cause a modeling artifact of excessive electricity storage use. We introduce this phenomenon as “unintended storage cycling”, ...

    In: iScience 25 (2022), 4, 104002, 30 S. | Martin Kittel, Wolf-Peter Schill
403 results, from 1
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