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Displaying results 1 to 7 of 7.

  1. State institutions and tax capacity
    an empirical investigation of causality
    Author: Akanbi, Olusegun A.
    Published: 2019
    Publisher:  International Monetary Fund, [Washington, DC]

    Would better state institutions increase tax collection, or would higher tax collection help improve state institutions? In the absence of conclusive guidance from theory, this paper searches for an empirical answer to this question, using a panel... more

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    Would better state institutions increase tax collection, or would higher tax collection help improve state institutions? In the absence of conclusive guidance from theory, this paper searches for an empirical answer to this question, using a panel dataset covering 110 non-resource-rich countries from 1996 to 2017. Employing a panel vector error correction model, the paper finds that tax capacity and state institutions cause and reinforce each other for a wide range of country groups. The bi-directional causality results suggest that developing tax capacity and building state institutions need to go hand in hand for best results, particularly in developing countries. Based on the impulse response analyses, the paper also finds that the causal effects in advanced economies are generally low in both directions, while in developing countries, both tax capacity and institutions shocks have larger positive impacts on institutions and tax capacity, respectively

     
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  2. Machine learning and causality
    the impact of financial crises on growth
    Author: Tiffin, Andrew
    Published: 2019
    Publisher:  International Monetary Fund, [Washington, DC]

    Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of... more

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    Universitätsbibliothek Braunschweig
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    Bibliothek der Pädagogischen Hochschule Freiburg/Breisgau
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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Technische Universität Hamburg, Universitätsbibliothek
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    Duale Hochschule Baden-Württemberg Heidenheim, Bibliothek
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    Thüringer Universitäts- und Landesbibliothek
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    Fachhochschule Kiel, Zentralbibliothek
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Universitätsbibliothek Leipzig
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    Leuphana Universität Lüneburg, Medien- und Informationszentrum, Universitätsbibliothek
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    Duale Hochschule Baden-Württemberg Mosbach, Bibliothek
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    E-Book Nationallizenz IMF
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    Hochschule Offenburg, University of Applied Sciences, Bibliothek Campus Offenburg
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    E-Book International Monetary Fund
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    Hochschulbibliothek Pforzheim, Bereichsbibliothek Technik und Wirtschaft
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    e-Book International Monetary Fund eLibrary
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    Hochschule Albstadt-Sigmaringen, Bibliothek Sigmaringen
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    Duale Hochschule Baden-Württemberg Villingen-Schwenningen, Bibliothek
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    Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of causality. This paper gently introduces some leading work in this area, using a concrete example-assessing the impact of a hypothetical banking crisis on a country's growth. By enabling consideration of a rich set of potential nonlinearities, and by allowing individually-tailored policy assessments, machine learning can provide an invaluable complement to the skill set of economists within the Fund and beyond

     
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  3. The confidence interval of the cross-sectional distribution of durations
    Author: Dixon, Huw; Tian, Maoshan
    Published: August 2022
    Publisher:  Cardiff Business School, Cardiff University, Cardiff, United Kingdom

    Tian and Dixon (2022) derived the variance of the estimator of cross-sectional distribution of durations (CSD). In this paper, we apply both Fieller's method and the Delta method to derive confidence interval of CSD using this variance formula. (CSD)... more

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    Tian and Dixon (2022) derived the variance of the estimator of cross-sectional distribution of durations (CSD). In this paper, we apply both Fieller's method and the Delta method to derive confidence interval of CSD using this variance formula. (CSD) is a new estimator derived by Dixon (2012). It can be applied in general Taylor model (GT E) by Dixon and Bihan (2012) and hospital waiting times by Dixon and Siciliani (2009). We use Monte Carlo simulations to evaluate the empirical size of Fieller's method and delta method among different sample sizes. The empirical results show that both Fieller's method and the delta method are valid in terms of estimating the confidence interval of CSD. Finally, we use both methods for real data set: the UK CPI micro-price data. Depending on the application, we see that both methods provide reasonable CIs for CSD estimators.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/284158
    Edition: Updated January 2023
    Series: Cardiff economics working papers ; no. E2022, 15
    Subjects: Fieller's Method; Delta Method; Confidence Interval
    Scope: 1 Online-Ressource (circa 48 Seiten), Illustrationen
  4. Einführung in die Ökonometrie
    Author: Huschens, Stefan
    Published: 2017
    Publisher:  Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, Dresden ; Technische Universität Dresden

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  5. Einführung in die Ökonometrie
    Author: Huschens, Stefan
    Published: Februar 2017
    Publisher:  Technische Universität Dresden, Fakultät Wirtschaftswissenschaften, [Dresden]

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    Content information
    Source: Union catalogues
    Language: German
    Media type: Book
    Format: Print
    RVK Categories: SK 980 ; QH 300 ; QH 310 ; QH 400 ; QH 400
    DDC Categories: 330
    Series: Dresdner Beiträge zu quantitativen Verfahren ; Nr. 69 (17)
    Subjects: Ökonometrie; Theorie
    Other subjects: (stw)Ökonometrie; (stw)Theorie; Econometric models; Econometrics; Lehrbuch; Lineares Einfach-Regressionsmodell; Konfidenzintervall; Multiples lineares Regressionsmodell; Autokorrelation; Heteroskedastie; Multikollinearität e; Linear Simple Regression Model; Confidence Interval; Multiple Linear Regression Model; Autocorrelation; Heteroscedasticity; Multicollinearity; Graue Literatur; Lehrbuch
    Scope: VI, 113 Seiten, Illustrationen, 30 cm
  6. State institutions and tax capacity
    an empirical investigation of causality
    Author: Akanbi, Olusegun A.
    Published: 2019
    Publisher:  International Monetary Fund, [Washington, DC]

    Would better state institutions increase tax collection, or would higher tax collection help improve state institutions? In the absence of conclusive guidance from theory, this paper searches for an empirical answer to this question, using a panel... more

    Access:
    Verlag (kostenfrei)
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    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Unter den Linden
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    Would better state institutions increase tax collection, or would higher tax collection help improve state institutions? In the absence of conclusive guidance from theory, this paper searches for an empirical answer to this question, using a panel dataset covering 110 non-resource-rich countries from 1996 to 2017. Employing a panel vector error correction model, the paper finds that tax capacity and state institutions cause and reinforce each other for a wide range of country groups. The bi-directional causality results suggest that developing tax capacity and building state institutions need to go hand in hand for best results, particularly in developing countries. Based on the impulse response analyses, the paper also finds that the causal effects in advanced economies are generally low in both directions, while in developing countries, both tax capacity and institutions shocks have larger positive impacts on institutions and tax capacity, respectively

     
    Export to reference management software   RIS file
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  7. Machine learning and causality
    the impact of financial crises on growth
    Author: Tiffin, Andrew
    Published: 2019
    Publisher:  International Monetary Fund, [Washington, DC]

    Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of... more

    Access:
    Verlag (kostenfrei)
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)
    Verlag (kostenfrei)

    Location:
    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Unter den Linden
    Inter-library loan:
    Unlimited inter-library loan, copies and loan

     

    Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of causality. This paper gently introduces some leading work in this area, using a concrete example-assessing the impact of a hypothetical banking crisis on a country's growth. By enabling consideration of a rich set of potential nonlinearities, and by allowing individually-tailored policy assessments, machine learning can provide an invaluable complement to the skill set of economists within the Fund and beyond

     
    Export to reference management software   RIS file
      BibTeX file