1. Introduction; 2. Statistical distributions and asymptotic theory; 3. Location; 4. Scale; 5. Location/scale models for non-negative variables; 6. Dynamic kernel density estimation and time-varying quantiles; 7. Multivariate models, correlation and association; 8. Conclusions and further directions.
The book presents a statistical theory for a class of nonlinear time-series models. It will be of interest to econometricians and statisticians.
Andrew Harvey is Professor of Econometrics at the University of Cambridge and a Fellow of Corpus Christi College. He is a Fellow of the Econometric Society and of the British Academy. He has published more than one hundred articles in journals and edited volumes and is the author of three books, The Econometric Analysis of Time Series, Time Series Models, and Forecasting and Structural Time Series Models and the Kalman Filter (Cambridge University Press, 1989). He is one of the developers of the STAMP computer package.
'It offers a comprehensive view of DCS models and is self-contained
in that it includes the necessary statistical theory for
understanding and applying them. Empirical examples help the reader
appreciate the potential of these models.' Journal of Economic
Literature
'Besides being invaluable to researchers in time series, the book
will be of immense help to practitioners, particularly in the
fields of econometrics and finance.' Sugata Sen Roy, Mathematical
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