This authoritative collection brings together the most important papers in time series econometrics published since 1990. These articles cover a range of central aspects of the field, concentrating in the main on theoretical and methodological developments. Taken together, they provide an overview of the current status of research in time series econometrics, emphasising those areas that appear to have attracted most recent interest in the profession.Volume I includes sections on unit root and stationarity tests; cointegration; structural breaks; nonlinearity; and long memory. Volume II covers conditional heteroskedasticity; stochastic volatility; unobserved components; trend function analysis; prediction; seasonality; and causality. These volumes will be essential reading for all who have an interest in this rapidly advancing subject.

Table of Contents:
Contents: Volume I Acknowledgements Introduction Paul Newbold and Stephen J. Leybourne PART I UNIT ROOT AND STATIONARITY TESTS 1. Serena Ng and Pierre Perron (1995), ‘Unit Root Tests in ARMA Models With Data-Dependent Methods for the Selection of the Truncation Lag’ 2. Sastry G. Pantula, Graciela Gonzalez-Farias and Wayne A. Fuller (1994), ‘A Comparison of Unit-Root Test Criteria’ 3. Graham Elliott, Thomas J. Rothenberg and James H. Stock (1996), ‘Efficient Tests for an Autoregressive Unit Root’ 4. Denis Kwiatkowski, Peter C.B. Phillips, Peter Schmidt and Yongcheol Shin (1992), ‘Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We that Economic Time Series Have a Unit Root?’ 5. S.J. Leybourne and B.P.M. McCabe (1999), ‘Modified Stationarity Tests With Data-Dependent Model-Selection Rules’ 6. Ignacio N. Lobato and Peter M. Robinson (1998), ‘A Nonparametric Test for I(0)’ PART II COINTEGRATION 7. Cheng Hsiao (1997), ‘Cointegration and Dynamic Simultaneous Equations Model’ 8. Cheng Hsiao (2001), ‘Identification and Dichotomization of Long- and Short-run Relations of Cointegrated Vector Autoregressive Models’ 9. Alfred A. Haug (1996), ‘Tests for Cointegration: A Monte Carlo Comparison’ 10. Michael T.K. Horvath and Mark W. Watson (1995), ‘Testing for Cointegration When Some of the Cointegrating Vectors Are Prespecified’ 11. Pentti Saikkonen and Helmut Lütkepohl (2000), ‘Testing for the Cointegrating Rank of a VAR Process With an Intercept’ 12. Søren Johansen (1997), ‘Likelihood Analysis of the J(2) Model’ 13. Yongcheol Shin (1994), ‘A Residual-based Test of the Null of Cointegration Against the Alternative of No Cointegration’ PART III STRUCTURAL BREAKS 14. Stephen J. Leybourne, Terence C. Mills and Paul Newbold (1998), ‘Spurious Rejections by Dickey-Fuller Tests in the Presence of a Break Under the Null’ 15. Jushan Bai (1994), ‘Least Squares Estimation of a Shift in Linear Processes’ 16. Jushan Bai and Pierre Perron (1998), ‘Estimating and Testing Linear Models with Multiple Structural Changes’ 17. Eric Zivot and Donald W.K. Andrews (1992), ‘Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis’ 18. Timothy J. Vogelsang and Pierre Perron (1998), ‘Additional Tests for a Unit Root Allowing for a Break in the Trend Function at an Unknown Time’ PART IV NONLINEARITY 19. Ruey S. Tsay (1998), ‘Testing and Modeling Multivariate Threshold Models’ 20. Timo Teräsvirta (1994), ‘Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models’ 21. Øyvind Eitrheim and Timo Teräsvirta (1996), ‘Testing the Adequacy of Smooth Transition Autoregressive Models’ 22. Walter Enders and C.W.J. Granger (1998), ‘Unit-Root Tests and Asymmetric Adjustment With an Example Using the Term Structure of Interest Rates’ PART V LONG MEMORY 23. Richard T. Baillie (1996), ‘Long Memory Processes and Fractional Integration in Econometrics’ 24. P.M. Robinson (1994), ‘Efficient Tests of Nonstationary Hypotheses’ 25. P.M. Robinson (1995), ‘Gaussian Semiparametric Estimation of Long Range Dependence’ 26. Carlos Velasco and Peter M. Robinson (2000), ‘Whittle Pseudo-Maximum Likelihood Estimation for Nonstationary Time Series’ 27. I.N. Lobato and N.E. Savin (1998), ‘Real and Spurious Long-Memory Properties of Stock-Market Data’ Name Index Volume II Acknowledgements An introduction by the editors to both volumes appears in Volume I PART I CONDITIONAL HETEROSKEDASTICITY 1. Tim Bollerslev, Ray Y. Chou and Kenneth F. Kroner (1992), ‘ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence’ 2. Robert F. Engle and Kenneth F. Kroner (1995), ‘Multivariate Simultaneous Generalized ARCH’ 3. Richard T. Baillie, Tim Bollerslev and Hans Ole Mikkelsen (1996), ‘Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity’ PART II STOCHASTIC VOLATILITY 4. Esther Ruiz (1994), ‘Quasi-maximum Likelihood Estimation of Stochastic Volatility Models’ 5. Andrew Harvey, Esther Ruiz and Neil Shephard (1994), ‘Multivariate Stochastic Variance Models’ 6. Bruce E. Hansen (1995), ‘Regression with Nonstationary Volatility’ 7. Andrew Harvey and Mariane Streibel (1998), ‘Testing for a Slowly Changing Level with Special Reference to Stochastic Volatility’ 8. Sangjoon Kim, Neil Shephard and Siddhartha Chib (1998), ‘Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models’ 9. F. Jay Breidt, Nuno Crato and Pedro de Lima (1998), ‘The Detection and Estimation of Long Memory in Stochastic Volatility’ PART III UNOBSERVED COMPONENTS 10. Agustín Maravall and Christophe Planas (1999), ‘Estimation Error and the Specification of Unobserved Component Models’ 11. Andrew Harvey and Siem Jan Koopman (2000), ‘Signal Extraction and the Formulation of Unobserved Components Models’ PART IV TREND FUNCTION ANALYSIS 12. Eugene Canjels and Mark W. Watson (1997), ‘Estimating Deterministic Trends in the Presence of Serially Correlated Errors’ 13. Timothy J. Vogelsang (1998), ‘Trend Function Hypothesis Testing in the Presence of Serial Correlation’ PART V PREDICTION 14. Kenneth D. West (1996), ‘Asymptotic Inference about Predictive Ability’ 15. Todd E. Clark and Michael W. McCracken (2001), ‘Tests of Equal Forecast Accuracy and Encompassing for Nested Models’ PART VI SEASONALITY 16. Eric Ghysels, Clive W.J. Granger and Pierre L. Siklos (1996), ‘Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?’ 17. Denise R. Osborn (1991), ‘The Implications of Periodically Varying Coefficients for Seasonal Time-Series Processes’ 18. S. Hylleberg, R.F. Engle, C.W.J. Granger and B.S. Yoo (1990), ‘Seasonal Integration and Cointegration’ 19. Richard J. Smith and A.M. Robert Taylor (1999), ‘Likelihood Ratio Tests for Seasonal Unit Roots’ 20. H. Peter Boswijk and Philip Hans Franses (1996), ‘Unit Roots in Periodic Autoregressions’ PART VII CAUSALITY 21. Hafida Boudjellaba, Jean-Marie Dufour and Roch Roy (1992), ‘Testing Causality Between Two Vectors in Multivariate Autoregressive Moving Average Models’ 22. Helmut Lütkepohl and D.S. Poskitt (1996), ‘Testing for Causation Using Infinite Order Vector Autoregressive Processes’ 23. Clive W.J. Granger and Jin-Lung Lin (1995), ‘Causality in the Long Run’ Name Index