000			02164cam a2200313 i 4500
003			RNL
005			20260330055448.0
008			220107s2021 fr a b 001 0 fre
020			_a9783031729096
040			_aRCL
082			_a330.0151 B69D
100	1		_aBismans, Francis J. _930953
245	1	0	_aDynamic Econometrics : _bModels and Applications _c/ Francis J. Bismans , Olivier Damette
260			_aCham: _bPalgrave Macmillan Cham, _c2025.
300			_axix, 349p ; 23cm. _billustrations ;
490	0		_aBibliothèque de l'économiste,
504			_aIncludes bibliographical references (pages 301-328) and index.
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.
546			_aEnglish
650		0	_aEconometrics,
650		0	_a Economic Theory _930954
650		0	_aQuantitative Economics _930955
650		0	_aMathematical Methods _930956
650		0	_aApplications of Mathematics _930957
650		0	_aStatistical Theory and Methods _930939
700	1		_aDamette, Olivier _930958
856			_uhttps://link.springer.com/book/10.1007/978-3-031-72910-2
942			_cBK
999			_c48034 _d48034