文件名称：Analysis of Integrated and Cointegrated Time Series with R
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更新时间：2016-05-24 02:58:45
R语言 协整
用纯粹R语言做协整的书，感觉不错。 Part I Theoretical Concepts 1 Univariate Analysis of Stationary Time Series............. 3 1.1 CharacteristicsofTime Series............................. 3 1.2 AR(p ) Time SeriesProcess ............................... 6 1.3 MA(q ) Time Series Process ............................... 10 1.4 ARMA( p , q ) Time SeriesProcess.......................... 14 Summary ................................................... 20 Exercises ................................................... 21 2 Multivariate Analysis of Stationary Time Series........... 23 2.1 Overview............................................... 23 2.2 Vector AutoregressiveModels ............................. 23 2.2.1 Specification, Assumptions, and Estimation . . . . . . . . . . . 23 2.2.2 DiagnosticTests .................................. 28 2.2.3 CausalityAnalysis................................. 34 2.2.4 Forecasting....................................... 36 2.2.5 Impulse ResponseFunctions ....................... 37 2.2.6 ForecastErrorVarianceDecomposition .............. 41 2.3 StructuralVector AutoregressiveModels ................... 43 2.3.1 SpecificationandAssumptions ...................... 43 2.3.2 Estimation ....................................... 44 2.3.3 Impulse ResponseFunctions ........................ 47 2.3.4 ForecastErrorVarianceDecomposition .............. 48 Summary ................................................... 49 Exercises ................................................... 50 3 Non-stationary Time Series ................................ 53 3.1 Trend- versus Difference-Stationary Series . . . . . . . . . . . . . . . . . . 53 3.2 Unit RootProcesses ..................................... 55 3.3 Long-MemoryProcesses.................................. 62 Summary ................................................... 70 Exercises ................................................... 71 4 Cointegration .............................................. 73 4.1 Spurious Regression ..................................... 73 4.2 Concept of Cointegration and Error-Correction Models . . . . . . . 75 4.3 Systems ofCointegratedVariables ......................... 78 Summary ................................................... 86 Exercises ................................................... 86 Part II Unit Root Tests 5 Testing for the Order of Integration....................... 91 5.1 Dickey-FullerTest ....................................... 91 5.2 Phillips-Perron Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 5.3 Elliott-Rothenberg-Stock Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 5.4 Schmidt-Phillips Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 5.5 Kwiatkowski-Phillips-Schmidt-Shin Test . . . . . . . . . . . . . . . . . . . . 103 Summary ...................................................104 Exercises ...................................................105 6 Further Considerations ....................................107 6.1 Stable Autoregressive Processes with Structural Breaks . . . . . . 107 6.2 SeasonalUnit Roots .....................................112 Summary ...................................................118 Exercises ...................................................118 Part III Cointegration 7 Single-Equation Methods ..................................121 7.1 Engle-GrangerTwo-StepProcedure........................121 7.2 Phillips-Ouliaris Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Summary ...................................................126 Exercises ...................................................127 8 Multiple-Equation Methods ...............................129 8.1 TheVector Error-CorrectionModel .......................129 8.1.1 SpecificationandAssumptions ......................129 8.1.2 Determining the CointegrationRank.................130 8.1.3 Testing for Weak Exogenity ........................134 8.1.4 Testing Restrictions onβ ...........................136 8.2 VECMand StructuralShift...............................143 8.3 The Structural Vector Error-Correction Model . . . . . . . . . . . . . . 145 Summary ...................................................158 Exercises ...................................................158 9 Appendix ..................................................161 9.1 TimeSeries Data........................................161 9.2 Technicalities ...........................................162 9.3 CRAN PackagesUsed ...................................163