Dynamic Econometrics

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Dynamic Econometrics

The main problem in econometric modelling of time series is discovering sustainable and interpretable relationships between observed economic variables. The primary aim of this book is to develop an operational econometric approach which allows constructive modelling. Professor Hendry deals with methodological issues (model discovery, data mining, and progressive research strategies); with major tools for modelling (recursive methods, encompassing, super exogeneity, invariance tests); and with practical problems (collinearity, heteroscedasticity, and measurement errors). He also includes an extensive study of US money demand. The book is self-contained, with the technical background covered in appendices. It is thus suitable for first year graduate students, and includes solved examples and exercises to facilitate its use in teaching. About the Series Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.
Dynamic Econometrics

Author: Francis J. Bismans
language: en
Publisher: Springer Nature
Release Date: 2025-02-15
This textbook for advanced econometrics students introduces key concepts of dynamic non-stationary modelling. It discusses all the classic topics in time series analysis and linear models containing multiple equations, as well as covering panel data models, and non-linear models of qualitative variables. The book offers a general introduction to dynamic econometrics and covers topics including non-stationary stochastic processes, unit root tests, Monte Carlo simulations, heteroskedasticity, autocorrelation, cointegration and error correction mechanism, models specification, and vector autoregressions. Going beyond advanced dynamic analysis, the book also meticulously analyses the classical linear regression model (CLRM) and introduces students to estimation and testing methods for the more advanced auto-regressive distributed lag (ARDL) model. The book incorporates worked examples, algebraic explanations and learning exercises throughout. It will be a valuable resource for graduate and postgraduate students in econometrics and quantitative finance as well as academic researchers in this area.
Dynamic Econometrics For Empirical Macroeconomic Modelling

For Masters and PhD students in EconomicsIn this textbook, the duality between the equilibrium concept used in dynamic economic theory and the stationarity of economic variables is explained and used in the presentation of single equations models and system of equations such as VARs, recursive models and simultaneous equations models.The book also contains chapters on: exogeneity, in the context of estimation, policy analysis and forecasting; automatic (computer based) variable selection, and how it can aid in the specification of an empirical macroeconomic model; and finally, on a common framework for model-based economic forecasting.Supplementary materials and notes are available on the publisher's website.