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Displaying results 1 to 10 of 10.

  1. Thirty years of academic finance
    Author: Ardia, David; Bluteau, Keven; Meghani, Mohammad-Abbas
    Published: [2022]
    Publisher:  GERAD, HÉC Montréal, Montréal (Québec), Canada

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Les cahiers du GERAD ; G-2022, 34 (August 2022)
    Subjects: Finance literature; Structural Topic Model (STM); topic modeling; textual analysis; scientometrics
    Scope: 1 Online-Ressource (circa 52 Seiten), Illustrationen
  2. Induced innovation and international environmental agreements
    evidence from the ozone regime
    Author: Dugoua, Eugenie
    Published: June 2021
    Publisher:  Grantham Research Institute on Climate Change and the Environment, London

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Centre for Climate Change Economics and Policy working paper ; no. 391
    Grantham Research Institute on Climate Change and the Environment working paper ; no. 363
    Subjects: Induced innovation; environmental agreements; difference-in-differences; synthetic control; topic modeling
    Scope: 1 Online-Ressource (circa 35 Seiten), Illustrationen
  3. The geography of innovation and technology news
    an empirical study of the German news media
    Author: Ozgun, Burcu; Brökel, Tom
    Published: [2021]
    Publisher:  Utrecht University, Human Geography and Planning, [Utrecht]

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Papers in evolutionary economic geography ; # 21, 10
    Subjects: technology; news media; sentiment analysis; topic modeling
    Scope: 1 Online-Ressource (circa 41 Seiten), Illustrationen
  4. Parenting styles, socioeconomic status and (non-)cognitive skills
    Author: Kugler, Philipp; Kroczek, Martin; Zühlke, Anne
    Published: (Juli 2022)
    Publisher:  Institut für Angewandte Wirtschaftsforschung e.V., Tübingen, Germany

    This paper analyzes the role of parenting styles, a recent topic in the economic literature. Using a novel latent class model, we investigate which parenting styles can be observed in the data and how parenting styles are related to parents’... more

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    This paper analyzes the role of parenting styles, a recent topic in the economic literature. Using a novel latent class model, we investigate which parenting styles can be observed in the data and how parenting styles are related to parents’ socioeconomic status and household composition. We identify four parenting styles. An authoritarian and an authoritative style closely resemble the styles proposed by psychologists. The two other styles are variations of these styles. The parenting styles are strongly associated with household income, education and whether a child is an only child. The results suggest that constraints in both time and (non-)cognitive skills of the parents restrict their choice. We find that children’s skills, in particular non-cognitive skills, are strongly associated with the parenting style. Parenting styles that are associated with low household income and having more than one child are associated with lower skills of the child. Therefore, our results indicate that parenting styles might be an important factor in explaining the skill gap in early childhood between children from different socioeconomic origins.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/283167
    Series: IAW discussion papers ; no. 138 (July 2022)
    Subjects: human capital; skills; parenting; child rearing; parenting style; social mobility; socio-economic status; topic modeling
    Scope: 1 Online-Ressource (circa 28 Seiten), Illustrationen
  5. Inference for regression with variables generated from unstructured data
    Author: Battaglia, Laura; Christensen, Tim; Hansen, Stephen; Sacher, Szymon
    Published: May 2024
    Publisher:  CESifo, Munich, Germany

    The leading strategy for analyzing unstructured data uses two steps. First, latent variables of economic interest are estimated with an upstream information retrieval model. Second, the estimates are treated as “data” in a downstream econometric... more

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    The leading strategy for analyzing unstructured data uses two steps. First, latent variables of economic interest are estimated with an upstream information retrieval model. Second, the estimates are treated as “data” in a downstream econometric model. We establish theoretical arguments for why this two-step strategy leads to biased inference in empirically plausible settings. More constructively, we propose a one-step strategy for valid inference that uses the upstream and downstream models jointly. The one-step strategy (i) substantially reduces bias in simulations; (ii) has quantitatively important effects in a leading application using CEO time-use data; and (iii) can be readily adapted by applied researchers.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/300047
    Series: CESifo working papers ; 11119 (2024)
    Subjects: unstructured data; information retrieval; topic modeling; Hamiltonian Monte Carlo; measurement error
    Scope: 1 Online-Ressource (circa 61 Seiten), Illustrationen
  6. Nowcasting GDP using tone-adjusted time varying news topics
    evidence from the financial press
    Author: Dijk, Dorinth van; Winter, Jasper de
    Published: [2023]
    Publisher:  De Nederlandsche Bank NV, Amsterdam, The Netherlands

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: DNB working paper ; no. 766 (February 2023)
    Subjects: Factor models; topic modeling; nowcasting
    Scope: 1 Online-Ressource (circa 47 Seiten), Illustrationen
  7. Identification of innovation drivers based on technology-related news articles
    Author: Latifi, Albina; Lenz, David; Winker, Peter
    Published: [2024]
    Publisher:  Philipps-University Marburg, School of Business and Economics, Marburg

    Innovations contribute to economic growth. Hence, knowledge about drivers of innovation activities is a necessary input for economic policy making when it comes to implement targeted support measures. We focus on firms as potential drivers of... more

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    Innovations contribute to economic growth. Hence, knowledge about drivers of innovation activities is a necessary input for economic policy making when it comes to implement targeted support measures. We focus on firms as potential drivers of innovation and use a novel data-driven approach to identify them. The approach is based on news articles from a technology-related newspaper for the period 1996-2021. In a first step, natural language processing (NLP) tools are used to identify latent topics in the text corpus. Expert knowledge is used to tag innovation-related topics. In a second step, a named entity recognition (NER) method is used to detect firm names in the news articles. Combining the information about innovation-related topics and firms mentioned in news articles linked to these topics provides a set of firms linked to each innovation-related topic. The results suggest that the approach helps identifying drivers of innovation activities going beyond the usual suspects. However, given that the rate of false alarms is not negligible, at the end also human judgement is needed when using this approach.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/283532
    Series: Joint discussion paper series in economics ; no. 2024, 01
    Subjects: nnovation drivers; topic modeling; entity recognition
    Scope: 1 Online-Ressource (circa 42 Seiten), Illustrationen
  8. A topic model for 10-K management disclosures
    Author: Fengler, Matthias; Tri Minh Phan
    Published: [2023]
    Publisher:  School of Economics and Political Science, Department of Economics, University of St.Gallen, St. Gallen

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Discussion paper / University of St.Gallen, School of Economics and Political Science, Department of Economics ; no. 2023, 07 (August 2023)
    Subjects: 10-K files; MD&A; natural language processing; topic modeling
    Scope: 1 Online-Ressource (circa 54 Seiten), Illustrationen
  9. Enhancing literature review with NLP methods algorithmic investment strategies case
    Author: Łaniewski, Stanisław; Ślepaczuk, Robert
    Published: 2024
    Publisher:  University of Warsaw, Faculty of Economic Sciences, Warsaw

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Working papers / University of Warsaw, Faculty of Economic Sciences ; no. 2024, 16 = 452
    Subjects: trading; quantitative finance; neural networks; literature review; knowledge representation; natural language processing (NLP); topic modeling; model comparison; artificial intelligence
    Scope: 1 Online-Ressource (circa 36 Seiten), Illustrationen
  10. Language processing and knowledge in the web
    25th international conference, GSCL 2013, Darmstadt, Germany, September 25 - 27, 2013 ; proceedings
    Contributor: Gurevych, Iryna (Herausgeber); Biemann, Chris (Herausgeber); Zesch, Torsten (Herausgeber)
    Published: 2013
    Publisher:  Springer, Heidelberg

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    Content information
    Source: Union catalogues
    Contributor: Gurevych, Iryna (Herausgeber); Biemann, Chris (Herausgeber); Zesch, Torsten (Herausgeber)
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9783642407215; 3642407218
    Other identifier:
    9783642407215
    Series: Lecture notes in computer science ; 8105 : Lecture notes in artificial intelligence
    Subjects: Sprachverarbeitung; Computerunterstützte Kommunikation; Mehrsprachigkeit; Natürliche Sprache; Korpus <Linguistik>; Wissensextraktion; Content <Internet>
    Other subjects: (Produktform)Paperback / softback; (Zielgruppe)Fachpublikum/ Wissenschaft; (Zielgruppe)Research; (BIC Subject Heading)UYQ; computer-mediated communication; decision trees; hamilton cycles; lexical semantics; topic modeling; (VLB-WN)1635: Hardcover, Softcover / Informatik, EDV/Anwendungs-Software
    Scope: XVI, 212 S., Ill., graph. Darst., 24 cm
    Notes:

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