000			03726nam a22004695i 4500
001			978-1-4614-8060-0
003			DE-He213
005			20200420211746.0
007			cr nn 008mamaa
008			130923s2014 xxu| s |||| 0|eng d
020			_a9781461480600 _9978-1-4614-8060-0
024	7		_a10.1007/978-1-4614-8060-0 _2doi
050		4	_aHB139-141
072		7	_aKCH _2bicssc
072		7	_aBUS021000 _2bisacsh
082	0	4	_a330.015195 _223
245	1	0	_aRecent Advances in Estimating Nonlinear Models _h[electronic resource] : _bWith Applications in Economics and Finance / _cedited by Jun Ma, Mark Wohar.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2014.
300			_aXVI, 299 p. 39 illus., 24 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aChapter 1 Stock Return and Inflation: An Analysis Based on the State-Space Framework -- Chapter 2 Diffusion Index Model Specification and Estimation: Using Mixed Frequency Datasets -- Chapter 3 Testing for Neglected Nonlinearity Using Regularized Artificial Neural Networks -- Chapter 4 On the Use of the Flexible Fourier Form in Unit Roots Tests, Endogenous Breaks, and Parameter Instability -- Chapter 5 Testing for a Markov-Switching Mean in Serially-Correlated Data -- Chapter 6 Nonlinear Time Series Models and Model Selection -- Chapter 7 Nonstationarities and Markov Switching Models -- Chapter 8 Has Wealth Effect Changed Over Time? Evidence from Four Industrial Countries -- Chapter 9 A Simple Specification Procedure for the Transition Function in Persistent Nonlinear Times Series Models -- Chapter 10 Small Area Estimation with Correctly Specified Linking Models -- Chapter 11 Forecasting Stock Returns: Does Switching between Models Help? -- Chapter 12 The Global Joint Distribution of Income and Health.
520			_aThis edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. The focus is on such topics as state-space model and the identification issue, use of Markov Switching Models and Smooth Transition Models to analyze economic series, and how best to distinguish between competing nonlinear models. Most economic theory suggests that the economic relationships among economic variables in the real world are fairly complex and nonlinear. Nonlinear models are necessary to capture these important channels through which economic variables can influence each other and various policies can affect economic activities. This volume features cutting-edge research from leading academics in economics, finance, and business management. The principles and techniques used here will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.
650		0	_aStatistics.
650		0	_aEconometrics.
650		0	_aMacroeconomics.
650	1	4	_aEconomics.
650	2	4	_aEconometrics.
650	2	4	_aStatistics for Business/Economics/Mathematical Finance/Insurance.
650	2	4	_aMacroeconomics/Monetary Economics//Financial Economics.
700	1		_aMa, Jun. _eeditor.
700	1		_aWohar, Mark. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461480594
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-8060-0
912			_aZDB-2-SBE
942			_cEBK
999			_c50991 _d50991