000			02531nam a22002057a 4500
005			20251023111118.0
008			251023b |||||||| |||| 00| 0 eng d
020			_a9783031729096
082			_a330.015195 _bBIS
100			_aBismans, Francis J. _925746
245			_aDynamic econometrics: _bmodels and applications
260			_aSwitzerland _bSpringer _c2025
300			_axxii,349p.
365			_aEUR _b74.99
500			_aFront Matter Pages i-xxii General Introduction Francis J. Bismans, Olivier Damette Pages 1-32 Dynamics in Econometrics Francis J. Bismans, Olivier Damette Pages 33-63 Estimating the Model Francis J. Bismans, Olivier Damette Pages 65-98 Testing the Model Francis J. Bismans, Olivier Damette Pages 99-132 Non-stationarity and Cointegration Francis J. Bismans, Olivier Damette Pages 133-167 Specification of the ARDL Model Francis J. Bismans, Olivier Damette Pages 169-196 On Vector Autoregressions Francis J. Bismans, Olivier Damette Pages 197-227 Panel Data Models Francis J. Bismans, Olivier Damette Pages 229-261 Non-stationary Panels Francis J. Bismans, Olivier Damette Pages 263-293 The Binary Qualitative Model Francis J. Bismans, Olivier Damette Pages 295-324 Back Matter Pages 325-349
520			_aThis 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. (https://link.springer.com/book/10.1007/978-3-031-72910-2)
650			_aEconometrics
700			_aDamette, Olivier _925747
942			_cBK _2ddc
999			_c10372 _d10372