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论坛 计量经济学与统计论坛 五区 计量经济学与统计软件
11031 22
2009-08-27
Edited by
HELMUT LU¨ TKEPOHL
European University Institute, Florence
MARKUS KRA¨ TZIG
Humboldt University, Berlin

Themes in Modern Econometrics
Managing Editor
PETER C.B. PHILLIPS, Yale University
Series Editors
ERIC GHYSELS, University of North Carolina, Chapel Hill
RICHARD J. SMITH, University of Warwick
Themes in Modern Econometrics is designed to service the large and growing
need for explicit teaching tools in econometrics. It will provide an organized
sequence of textbooks in econometrics aimed squarely at the student population
and will be the first series in the discipline to have this as its express aim.
Written at a level accessible to students with an introductory course in econometrics
behind them, each book will address topics or themes that students and
researchers encounter daily. Although each book will be designed to stand alone
as an authoritative survey in its own right, the distinct emphasis throughout will
be on pedagogic excellence.
Titles in the Series
Statistics and Econometric Models: Volumes 1 and 2
CHRISTIAN GOURIEROUX and ALAIN MONFORT
Translated by QUANG VOUNG
Time Series and Dynamic Models
CHRISTIAN GOURIEROUX and ALAIN MONFORT
Translated and edited by GIAMPIERO GALLO
Unit Roots, Cointegration, and Structural Change
G.S. MADDALA and IN-MOO KIM
Generalized Method of Moments Estimation
Edited by L´ASZLO´ MA´ TYA´ S
Nonparametric Econometrics
ADRIAN PAGAN and AMAN ULLAH
Econometrics of Qualitative Dependent Variables
CHRISTIAN GOURIEROUX
Translated by PAUL B. KLASSEN
The Econometric Analysis of Seasonal Time Series
ERIC GHYSELS and DENISE R. OSBORN
Semiparametric Regression for the Applied Econometrician
ADONIS YATCHEW
Preface page xv
Notation and Abbreviations xix
List of Contributors xxv
1 Initial Tasks and Overview 1
Helmut L¨utkepohl
1.1 Introduction 1
1.2 Setting Up an Econometric Project 2
1.3 Getting Data 3
1.4 Data Handling 5
1.5 Outline of Chapters 5
2 Univariate Time Series Analysis 8
Helmut L¨utkepohl
2.1 Characteristics of Time Series 8
2.2 Stationary and Integrated Stochastic Processes 11
2.2.1 Stationarity 11
2.2.2 Sample Autocorrelations, Partial Autocorrelations,
and Spectral Densities 12
2.2.3 Data Transformations and Filters 17
2.3 Some Popular Time Series Models 22
2.3.1 Autoregressive Processes 22
2.3.2 Finite-Order Moving Average Processes 25
2.3.3 ARIMA Processes 27
2.3.4 Autoregressive Conditional Heteroskedasticity 28
2.3.5 Deterministic Terms 30
2.4 Parameter Estimation 30
2.4.1 Estimation of AR Models 30
2.4.2 Estimation of ARMA Models 32
2.5 Model Specification 33

xii Contents
5.3.1 Alternative Model Specifications 214
5.3.2 Estimation of Multivariate GARCH Models 217
5.3.3 Extensions 218
5.3.4 Continuing the Empirical Illustration 220
6 Smooth Transition Regression Modeling 222
Timo Ter¨asvirta
6.1 Introduction 222
6.2 The Model 222
6.3 The Modeling Cycle 225
6.3.1 Specification 225
6.3.2 Estimation of Parameters 228
6.3.3 Evaluation 229
6.4 Two Empirical Examples 234
6.4.1 Chemical Data 234
6.4.2 Demand for Money (M1) in Germany 238
6.5 Final Remarks 242
7 Nonparametric Time Series Modeling 243
Rolf Tschernig
7.1 Introduction 243
7.2 Local Linear Estimation 245
7.2.1 The Estimators 245
7.2.2 Asymptotic Properties 248
7.2.3 Confidence Intervals 250
7.2.4 Plotting the Estimated Function 251
7.2.5 Forecasting 254
7.3 Bandwidth and Lag Selection 254
7.3.1 Bandwidth Estimation 256
7.3.2 Lag Selection 258
7.3.3 Illustration 261
7.4 Diagnostics 262
7.5 Modeling the Conditional Volatility 263
7.5.1 Estimation 264
7.5.2 Bandwidth Choice 265
7.5.3 Lag Selection 266
7.5.4 ARCH Errors 267
7.6 Local Linear Seasonal Modeling 268
7.6.1 The Seasonal Nonlinear Autoregressive Model 269
7.6.2 The Seasonal Dummy Nonlinear Autoregressive
Model 270
7.6.3 Seasonal Shift Nonlinear Autoregressive Model 271
Contents xiii
7.7 Example I: Average Weekly Working Hours in the United
States 272
7.8 Example II: XETRA Dax Index 280
8 The Software JMulTi 289
Markus Kr¨atzig
8.1 Introduction to JMulTi 289
8.1.1 Software Concept 289
8.1.2 Operating JMulTi 290
8.2 Numbers, Dates, and Variables in JMulTi 290
8.2.1 Numbers 290
8.2.2 Numbers in Tables 291
8.2.3 Dates 291
8.2.4 Variable Names 292
8.3 Handling Data Sets 292
8.3.1 Importing Data 292
8.3.2 Excel Format 292
8.3.3 ASCII Format 293
8.3.4 JMulTi .dat Format 293
8.4 Selecting, Transforming, and Creating Time Series 293
8.4.1 Time Series Selector 293
8.4.2 Time Series Calculator 295
8.5 Managing Variables in JMulTi 296
8.6 Notes for Econometric Software Developers 296
8.6.1 General Remark 296
8.6.2 The JStatCom Framework 297
8.6.3 Component Structure 297
8.7 Conclusion 299
References 301
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Applied Time Series Econometrics.pdf

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2009-9-15 13:18:29
该书的数据文件见:http://www.jmulti.de/data_atse.html
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2009-12-17 16:30:13
2# brwei2007
书很超值~~赞楼主!
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2010-1-7 12:23:24
书特好,清晰版的,好而不贵,超赞!还有数据!
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2010-4-6 17:16:33
NICE MAN!!!
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2010-8-18 17:49:16
THANK YOU SO MUCH..
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