Unobserved Components and Time Series Econometrics

by Siem Jan Koopman, Neil Shephard

Overview

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.

Product Details

ISBN-13:	9780199683666
Publisher:	Oxford University Press
Publication date:	01/19/2016
Pages:	390
Product dimensions:	6.20(w) x 9.30(h) x 1.30(d)

About the Author

Siem Jan Koopman, Professor of Econometrics, VU University Amsterdam,Neil Shephard, Professor of Economics and of Statistics, Harvard University

Siem Jan Koopman is a Professor of Econometrics at the VU University Amsterdam and Research Fellow at the Tinbergen Institute. Furthermore, he is a Visiting Professor at CREATES, University of Aarhus and a Visiting Researcher at the European Central Bank, Financial Research. He has held positions at LSE and Tilburg University, and has been a Research Fellow at the US Bureau of the Census, Washington DC, and a Fernand Braudel Senior Fellow at the European University Institute, Florence.

Neil Shephard is Professor of Economics and of Statistics at Harvard University. He previously was a faculty member at the LSE and Oxford University. He was elected a Fellow of the Econometric Society in 2004 and a Fellow of the British Academy in 2006. He received an honourary doctorate in economics from Aarhus University in 2009. He was award the Richard Stone Prize in Applied Econometrics in 2012. He has been an associate editor of the academic journal Econometrica since 2002. He has previously been on the editorial boards of, for example, Review of Economic Studies, Biometrika and JRSSB.

Table of Contents

1. Introduction, Siem Jan Koopman and Neil Shephard2. The Development of a Time Series Methodology: from Recursive Residuals to Dynamic Conditional Score Models, Andrew Harvey3. A State-Dependent Model for Inflation Forecasting, Andrea Stella and James H. Stock4. Measuring the Tracking Error of Exchange Traded Funds, Giuliano De Rossi5. Measuring the Dynamics of Global Business Cycle Connectedness, Francis X. Diebold and Kamil Yilmaz6. Inferring and Predicting Global Temperature Trends, Craig Ansley and Piet de Jong7. Forecasting the Boat Race, Geert Mesters and Siem Jan Koopman8. Tests for Serial Dependence in Static, Non-Gaussian Factor Models, Gabriele Fiorentini and Enrique Sentana9. Inference for Models with Asymmetric α-Stable Noise Processes, Tatjana Lemke and Simon J. Godsill10. Martingale Unobserved Component Models, Neil Shephard11. More is Not Always Better: Kalman Filtering in Dynamic Factor Models, Pilar Poncela and Esther Ruiz12. On Detecting End-of-Sample Instabilities, Fabio Busetti13. Improved Frequentist Prediction Intervals for Autoregressive Models by Simulation, Jouni Helske and Jukka Nyblom14. The Superiority of the LM Test in a Class of Econometric Models Where the Wald Test Performs Poorly, Jun Ma and Charles R. Nelson15. Generalised Linear Spectral Models, Tommaso Proietti and Alessandra Luati