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Essays in Nonlinear Time Series Econometrics

Editor

Listed:
  • Haldrup, Niels
    (Aarhus University)

  • Meitz, Mika
    (University of Helsinki)

  • Saikkonen, Pentti
    (University of Helsinki)

Abstract

This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Terasvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Terasvirta has had and will continue to have, on the profession. Contributors to this volume - Marco Aiolfi, Quantitative Management LLC Cristina Amado, Aarhus University and CREATES, University of Minho and NIPE Heather M. Anderson, Monash University Laurent A. F. Callot, Free University Amsterdam and CREATES Jennifer L. Castle, Oxford University, Institute for New Economic Thinking, Oxford Martin School Jin Seo Cho, Yonsei University James Davidson, University of Exeter Business School Robert Engle, New York University, Stern School of Business Niels Haldrup, Aarhus University Andreea G. Halunga, University of Exeter Business School David F. Hendry, Oxford University, Institute for New Economic Thinking, Oxford Martin School Eric Hillebrand, Aarhus University and CREATES Isao Ishida, Osaka University and CSFI Katarina Juselius, University of Copenhagen Mikael Juselius, Bank for International Settlements Anders Bredahl Kock, Aarhus University and CREATES Robinson Kruse, Leibniz University Hannover and CREATES Helina Laakkonen, Bank of Finland Tae-Hwy Lee, University of California at Riverside Helmut Lutkepohl, Freie Universitat Berlin and DIW Marcelo C. Medeiros, Pontifical Catholic University of Rio de Janeiro Mika Meitz, University of Helsinki Eduardo F. Mendes, University of New South Wales Marius Rodriguez, Federal Reserve Bank of San Francisco Pentti Saikkonen, University of Helsinki Rickard Sandberg, Stockholm School of Economics Bard Stove, University of Bergen Allan Timmermann, University of California, San Diego, Rady School of Management and CREATES Dag Tjostheim, University of Bergen Farshid Vahid, Monash University Halbert White, University of California at San Diego

Suggested Citation

  • Haldrup, Niels & Meitz, Mika & Saikkonen, Pentti (ed.), 2014. "Essays in Nonlinear Time Series Econometrics," OUP Catalogue, Oxford University Press, number 9780199679959.
  • Handle: RePEc:oxp:obooks:9780199679959
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    Citations

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    Cited by:

    1. Hillebrand, Eric & Lukas, Manuel & Wei, Wei, 2021. "Bagging weak predictors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 237-254.
    2. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    3. Ellahie, Atif & Ricco, Giovanni, 2017. "Government purchases reloaded: Informational insufficiency and heterogeneity in fiscal VARs," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 13-27.
    4. Nelimarkka, Jaakko, 2017. "Evidence on News Shocks under Information Deficiency," MPRA Paper 80850, University Library of Munich, Germany.
    5. Jurgen A. Doornik & David F. Hendry & Steve Cook, 2015. "Statistical model selection with “Big Data”," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1045216-104, December.
    6. repec:hal:spmain:info:hdl:2441/27od5pb99881folvtfs8s3k16l is not listed on IDEAS
    7. James A. Duffy & David F. Hendry, 2017. "The impact of integrated measurement errors on modeling long-run macroeconomic time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 568-587, October.
    8. Audrino, Francesco & Camponovo, Lorenzo & Roth, Constantin, 2015. "Testing the lag structure of assets’ realized volatility dynamics," Economics Working Paper Series 1501, University of St. Gallen, School of Economics and Political Science.
    9. David F. Hendry, 2020. "A Short History of Macro-econometric Modelling," Economics Papers 2020-W01, Economics Group, Nuffield College, University of Oxford.
    10. Nelimarkka, Jaakko, 2017. "The effects of government spending under anticipation: the noncausal VAR approach," MPRA Paper 81303, University Library of Munich, Germany.

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