000			01744nam a2200229 4500
005			20250325124616.0
008			250325b |||||||| |||| 00| 0 eng d
020			_a9780192844507
037			_cTextual
040			_aRTL _cRTL
084			_aX:(B2816) N4;R1 _qRTL
100			_aDavidson, James
245			_aStochastic limit theory: an introduction for econometricians
250			_a2nd
260			_aUK _bOxford university press _c2021
300			_axxix, 776p. _bIncludes bibliography and index
520			_aThis book aims to introduce modern asymptotic theory to students and practitioners of econometrics. It falls broadly into two parts. The first half provides a handbook and reference for the underlying mathematics (Part I, Chapters 1‐6), statistical theory (Part II, Chapters 7‐11) and stochastic process theory (Part III, Chapters 12‐17). The second half provides a treatment of the main convergence theorems used in analysing the large sample behaviour of econometric estimators and tests. These are the law of large numbers (Part IV, Chapters 18‐21), the central limit theorem (Part V, Chapters 22‐25) and the functional central limit theorem (Part VI, Chapters 26‐30). The focus in this treatment is on the nonparametric approach to time series properties, covering topics such as nonstationarity, mixing, martingales, and near‐epoch dependence. While the approach is not elementary, care is taken to keep the treatment self‐contained. Proofs are provided for almost all the results.
650			_a Econometric and Statistical Methods and Methodology: General _9747533
650			_aEconometrics
650			_aMathematical Economics
942			_2CC _n0 _cTB _hX:(B2816) N4;R1
999			_c1269243 _d1269243