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Displaying results 1 to 7 of 7.

  1. Fast computation of reconciled forecasts for hierarchical and grouped time series
    Author: Hyndman, Rob J.; Lee, Alan; Wang, Earo
    Published: June 2014
    Publisher:  Monash University, Department of Econometrics and Business Statistics, Victoria

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Working paper / Monash University, Department of Econometrics and Business Statistics ; 14, 17
    Subjects: combining forecasts; grouped time series; hierarchical time series; reconciling forecasts; weighted least squares
    Scope: 1 Online-Ressource (circa 26 Seiten), Illustrationen
  2. Efficient estimation of regression models with user-specified parametric model for heteroskedasticty
    Author: Chaudhuri, Saraswata; Renault, Eric
    Published: [2023]
    Publisher:  University of Warwick, Department of Economics, Coventry, United Kingdom

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    VS 623
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Edition: This version: September 13, 2023.
    Series: Warwick economics research papers ; no: 1473 (September 2023)
    Subjects: asymptotic optimality; misspecification; nuisance parameters; weighted least squares
    Scope: 1 Online-Ressource (circa 50 Seiten)
  3. Openness to international trade and economic growth : A cross-country empirical investigation
    Author: Ulaşan, Bülent
    Published: 2012
    Publisher:  Kiel Institute for the World Economy (IfW), Kiel

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  4. Resurrecting weighted least squares
    Author: Romano, Joseph P.; Wolf, Michael
    Published: 2014
    Publisher:  Univ., Dep. of Economics, Zurich

    Linear regression models form the cornerstone of applied research in economics and other scientific disciplines. When conditional heteroskedasticity is present, or at least suspected, the practice of reweighting the data has long been abandoned in... more

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 191 (172)
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    Linear regression models form the cornerstone of applied research in economics and other scientific disciplines. When conditional heteroskedasticity is present, or at least suspected, the practice of reweighting the data has long been abandoned in favor of estimating model parameters by ordinary least squares (OLS), in conjunction with using heteroskedasticity consistent (HC) standard errors. However, we argue for reintroducing the practice of reweighting the data, since doing so can lead to large efficiency gains of the resulting weighted least squares (WLS) estimator over OLS even when the model for reweighting the data is misspecified. Efficiency gains manifest in a first-order asymptotic sense and thus should be considered in current empirical practice. Crucially, we also derive how asymptotically valid inference based on the WLS estimator can be obtained even when the model for reweighting the data is misspecified. The idea is that, just like the OLS estimator, the WLS estimator can also be accompanied by HC standard errors without knowledge of the functional form of conditional heteroskedasticity. A Monte Carly study demonstrates attractive finite-sample properties of our proposals compared to the status quo, both in terms of estimation and making inference.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/111232
    Series: Working paper series / University of Zurich, Department of Economics ; 172
    Subjects: Conditional heteroskedasticity; HC standard errors; weighted least squares
    Scope: Online-Ressource (41 S.), graph. Darst.
  5. The micro dynamics of macro announcements
    Author: Mittnik, Stefan; Robinzonov, Nikolay; Wohlrabe, Klaus
    Published: 2013
    Publisher:  CESifo, München

    We examine how regularly scheduled macroeconomic announcements for the U.S., Germany and the euro area affect the German stock market, using high-frequency, minute-by-minute DAX data. Our study extends the literature on high-frequency announcement... more

    Location:
    Staats- und Universitätsbibliothek Bremen
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    Location:
    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 63 (4421)
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    We examine how regularly scheduled macroeconomic announcements for the U.S., Germany and the euro area affect the German stock market, using high-frequency, minute-by-minute DAX data. Our study extends the literature on high-frequency announcement effects in several ways. First, we account for endogenous return dynamics by assessing announcement impacts via response analysis. Second, we examine the announcements effects on market volatility in a more detailed fashion by distinguishing effects of positive and negative surprises. Finally, we adapt the standard weighted-least-squares approach to more adequately analyze both conditional mean and volatility effects.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/84162
    RVK Categories: QB 910
    Series: Array ; 4421
    Subjects: announcement effects; market efficiency; information spillover; impulse response analysis; volatility; weighted least squares
    Scope: Online-Ressource (26 S.), graph. Darst.
  6. Optimal designs for testing the functional form of a regression via nonparametric estimation techniques
    Author: Biedermann, Stefanie; Dette, Holger
    Published: 2000
    Publisher:  SFB 475, Universität Dortmund, Dortmund

    For the problem of checking linearity in a heteroscedastic nonparametric regression model under a fixed design assumption we study maximin designs which maximize the minimum power of a nonparametric test over a broad class of alternatives from the... more

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 35 (2000,41)
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    For the problem of checking linearity in a heteroscedastic nonparametric regression model under a fixed design assumption we study maximin designs which maximize the minimum power of a nonparametric test over a broad class of alternatives from the assumed linear regression model. It is demonstrated that the optimal design depends sensitively on the used estimation technique (i.e. weighted or ordinary least squares) and on an inner product used in the definiton of the class of alternatives. Our results extend and put recent finndings of Wiens (1991) in a new light, who established the maximin optimality of the uniform design for lack-of-fit tests in homoscedastic multiple linear regression models.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/77227
    Series: [Technical Report, SFB 475: Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund ; 2000,41]
    Subjects: goodness-of-fit test; weighted least squares; optimal design; maximin optimality; D1-optimality
    Scope: Online-Ressource (10 S.)
  7. Economic volatility and sovereign yields' determinants
    a time-varying approach
    Author: Afonso, António; Jalles, João Tovar
    Published: December 2015
    Publisher:  ISEG - School of Economics and Management, Department of Economics, University of Lisbon, Lisbon

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10400.5/10713
    Series: Working papers / ISEG, School of Economics and Management, Department of Economics ; WP 2016, 04 DE/UECE
    Subjects: volatility; fiscal policy; bond spreads; weighted least squares; time-varying coefficients
    Scope: 1 Online-Ressource (circa 24 Seiten), Illustrationen