03846nam 22006135 450 991098331040332120250216115531.09783031729102303172910210.1007/978-3-031-72910-2(CKB)37627812800041(MiAaPQ)EBC31921680(Au-PeEL)EBL31921680(DE-He213)978-3-031-72910-2(OCoLC)1503843199(EXLCZ)993762781280004120250216d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierDynamic Econometrics Models and Applications /by Francis J. Bismans, Olivier Damette1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Palgrave Macmillan,2025.1 online resource (560 pages)9783031729096 3031729099 1. General Introduction -- 2. Dynamics in Econometrics -- 3. Estimating the Model -- 4. Testing the Model -- 5. Non-Stationarity and Cointegration -- 6. Specifying the ARDL Model -- 7. Vector Autoregressions -- 8. Panel Data Models -- 9. Non-Stationary Panels -- 10. The Binary Qualitative Model.“This book is a bold and confident advance in dynamic econometric theory and practice.” I. Litvine, Professor in Statistics, Nelson Mandela University, Port Elizabeth, South Africa “This book is an outstanding contribution to econometrics, coming at a crucial time to fill a significant gap in the field.” Maria do Rosário Grossinho, Professor of Analysis and Mathematical Finance ISEG - University of Lisbon Portugal 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. Francis Bismans is Professor in Economics and Statistics, University of Lorraine, France. Olivier Damette is Professor in Economics, University of Lorraine, France.EconometricsSocial sciencesMathematicsRegression analysisEconometricsQuantitative EconomicsMathematics in Business, Economics and FinanceLinear Models and RegressionEconometrics.Social sciencesMathematics.Regression analysis.Econometrics.Quantitative Economics.Mathematics in Business, Economics and Finance.Linear Models and Regression.330.015195Bismans Francis J1784670Damette Olivier1784671MiAaPQMiAaPQMiAaPQBOOK9910983310403321Dynamic Econometrics4316273UNINA