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      The effect of central bank communication on sovereign bond yields: The case of Hungary

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      PLoS ONE
      Public Library of Science

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          Abstract

          In this article we investigate how the public communication of the Hungarian Central Bank’s Monetary Council (MC) affects Hungarian sovereign bond yields. This research ties into the advances made in the financial and political economy literature which rely on extensive textual data and quantitative text analysis tools. While prior research demonstrated that forward guidance, in the form of council meeting minutes or press releases can be used as predictors of rate decisions, we are interested in whether they are able to directly influence asset returns as well. In order to capture the effect of central bank communication, we measure the latent hawkish or dovish sentiment of MC press releases from 2005 to 2019 by applying a sentiment dictionary, a staple in the text mining toolkit. Our results show that central bank forward guidance has an intra-year effect on bond yields. However, the hawkish or dovish sentiment of press releases has no impact on maturities of one year or longer where the policy rate proves to be the most important explanatory variable. Our research also contributes to the literature by applying a specialized dictionary to monetary policy as well as broadening the discussion by analyzing a case from the non-eurozone Central-Eastern region of the European Union.

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          Bounds testing approaches to the analysis of level relationships

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            Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts

            Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have hindered their use in political science research. Here lies the promise of automated text analysis: it substantially reduces the costs of analyzing large collections of text. We provide a guide to this exciting new area of research and show how, in many instances, the methods have already obtained part of their promise. But there are pitfalls to using automated methods—they are no substitute for careful thought and close reading and require extensive and problem-specific validation. We survey a wide range of new methods, provide guidance on how to validate the output of the models, and clarify misconceptions and errors in the literature. To conclude, we argue that for automated text methods to become a standard tool for political scientists, methodologists must contribute new methods and new methods of validation.
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              When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: ResourcesRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2021
                4 February 2021
                : 16
                : 2
                : e0245515
                Affiliations
                [001] Centre for Social Sciences, ELKH, Budapest, Hungary
                Sam Houston State University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-9107-6777
                Article
                PONE-D-20-21266
                10.1371/journal.pone.0245515
                7861405
                33539389
                dcf68b30-bc6e-45a0-bce9-b603db67afe5
                © 2021 Máté et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 July 2020
                : 1 January 2021
                Page count
                Figures: 9, Tables: 10, Pages: 28
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Social Sciences
                Economics
                Finance
                Public Finance
                Monetary Policy
                Social Sciences
                Economics
                Finance
                Public Finance
                Money Supply and Banking
                Social Sciences
                Economics
                Macroeconomics
                Social Sciences
                Economics
                Finance
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Test Statistics
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Test Statistics
                Social Sciences
                Economics
                Macroeconomics
                Inflation Rates
                Social Sciences
                Economics
                Financial Markets
                Social Sciences
                Economics
                Development Economics
                Economic Growth
                Custom metadata
                The data underlying this study are available on Figshare ( https://doi.org/10.6084/m9.figshare.13526156.v1). This repository contains all the neccesary code and data to replicate our results as well as a detailed Readme file.

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