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Unobserved Components and Time Series Econometrics

Editor

Listed:
  • Koopman, Siem Jan
    (Professor of Econometrics, VU University Amsterdam)

  • Shephard, Neil
    (Professor of Economics and of Statistics, Harvard University)

Abstract

This volume presents original and up-to-date studies in unobserved components (UC) time series models from both theoretical and methodological perspectives. It also presents empirical studies where the UC time series methodology is adopted. Drawing on the intellectual influence of Andrew Harvey, the work covers three main topics: the theory and methodology for unobserved components time series models; applications of unobserved components time series models; and time series econometrics and estimation and testing. These types of time series models have seen wide application in economics, statistics, finance, climate change, engineering, biostatistics, and sports statistics. The volume effectively provides a key review into relevant research directions for UC time series econometrics and will be of interest to econometricians, time series statisticians, and practitioners (government, central banks, business) in time series analysis and forecasting, as well to researchers and graduate students in statistics, econometrics, and engineering. Contributors to this volume - Craig Ansley Fabio Busetti, Bank of Italy Piet de Jong, Macquarie University Francis X. Diebold, University of Pennsylvania Giuliano De Rossi, Macquarie Securities Gabriele Fiorentini, University of Florence Simon J. Godsill, University of Cambridge Andrew Harvey, University of Cambridge Jouni Helske, University of Jyvaskyla Siem Jan Koopman, VU University Amsterdam Tatjana Lemke, University of Cambridge Alessandra Luati, University of Bologna Jun Ma, University of Alabama Geert Mesters, Universitat Pompeu Fabra Charles R. Nelson, University of Washington Jukka Nyblom, University of Jyvaskyla Pilar Poncela, Universidad Autonoma de Madrid Tommaso Proietti, University of Tor Vergata Esther Ruiz, Universidad Carlos III de Madrid Enrique Sentana Neil Shephard, Harvard University Andrea Stella, Federal Reserve System James H. Stock, Harvard University Kamil Yilmaz, Koc University

Suggested Citation

  • Koopman, Siem Jan & Shephard, Neil (ed.), 2015. "Unobserved Components and Time Series Econometrics," OUP Catalogue, Oxford University Press, number 9780199683666.
  • Handle: RePEc:oxp:obooks:9780199683666
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    Citations

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    Cited by:

    1. Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
    2. Elmar Mertens & James M. Nason, 2020. "Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility," Quantitative Economics, Econometric Society, vol. 11(4), pages 1485-1520, November.
    3. Mengheng Li & Siem Jan (S.J.) Koopman, 2018. "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers 18-027/III, Tinbergen Institute.
    4. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R, Federal Reserve Bank of Cleveland, revised 15 Aug 2022.
    5. Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
    6. Yunjong Eo & Luis Uzeda & Benjamin Wong, 2023. "Understanding trend inflation through the lens of the goods and services sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 751-766, August.
    7. Łukasz Lenart & Mateusz Pipień, 2017. "Non-Parametric Test for the Existence of the Common Deterministic Cycle: The Case of the Selected European Countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 201-241, September.
    8. Łukasz Lenart, 2018. "Bayesian inference for deterministic cycle with time-varying amplitude: the case of growth cycle in European countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(3), pages 233-262, September.

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