一本高级计量经济学教材----Free now!

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

I already obtained enough money for my purchase, so i free this book.

“Econometric Theory and Methods” 英文版 PDF

By Davidson and Mackinnon 4.5M

这是我在美国读博士二年级时的教材。 一年级用的是格林的书。

个人感觉在理论的解释上比格林的书要清楚。 尤其在面板数据（PANEL　DATA）, IV estimation 和SUR 上.(这本书的Hausman-Dubin-Wu test 解释的很清楚，通过这个TEST 你可以知道是否要用IV ESTIMATOR，fiexed effect model or random effect model, which one is better. And some more general uses.)

从下面LINK, 可以下载每章后的练习题的数据集

92579.rar (4.5 MB)

2007-2-23 06:29:00 上传

一本高级计量经济学教材

(I have a brief introduction of this book at the seventh floor.)

Some guys pointed out that the version of this e-book is older than the hardcopy of this book. I did not compare them carefully, however when i took the econometric class, i used this ebook instead of the hardcopy of 2004 version. So i think the difference between this e-book and hardcopy is subtle. 

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏32 回帖

关键词：高级计量经济学教材 计量经济学教材 高级计量经济学 经济学教材 计量经济学 obtained purchase general already seventh

Table of Contents

Chapter 1 Regression Models 1

• 1.1 Introduction 1
• 1.2 Distributions, Densities, and Moments 3
• 1.3 The Specification of Regression Models 15
• 1.4 Matrix Algebra 22
• 1.5 Method-of-Moments Estimation 30
• 1.6 Notes on the Exercises 37
• 1.7 Exercises 38

Chapter 2 The Geometry of Linear Regression 42

• 2.1 Introduction 42
• 2.2 The Geometry of Vector Spaces 43
• 2.3 The Geometry of OLS Estimation 54
• 2.4 The Frisch-Waugh-Lovell Theorem 62
• 2.5 Applications of the FWL Theorem 69
• 2.6 Influential Observations and Leverage 76
• 2.7 Final Remarks 81
• 2.8 Exercises 82

Chapter 3 The Statistical Properties of Ordinary Least Squares 86

• 3.1 Introduction 86
• 3.2 Are OLS Parameter Estimators Unbiased? 88
• 3.3 Are OLS Parameter Estimators Consistent? 92
• 3.4 The Covariance Matrix of the OLS Parameter Estimates 97
• 3.5 Efficiency of the OLS Estimator 104
• 3.6 Residuals and Error Terms 107
• 3.7 Misspecification of Linear Regression Models 111
• 3.8 Measures of Goodness of Fit 115
• 3.9 Final Remarks 118
• 3.10 Exercises 118

Chapter 4 Hypothesis Testing in Linear Regression Models 122

• 4.1 Introduction 122
• 4.2 Basic Ideas 122
• 4.3 Some Common Distributions 129
• 4.4 Exact Tests in the Classical Normal Linear Model 138
• 4.5 Large-Sample Tests in Linear Regression Models 146
• 4.6 Simulation-Based Tests 155
• 4.7 The Power of Hypothesis Tests 166
• 4.8 Final Remarks 172
• 4.9 Exercises 172

Chapter 5 Confidence Intervals 177

• 5.1 Introduction 177
• 5.2 Exact and Asymptotic Confidence Intervals 178
• 5.3 Bootstrap Confidence Intervals 185
• 5.4 Confidence Regions 189
• 5.5 Heteroskedasticity-Consistent Covariance Matrices 196
• 5.6 The Delta Method 202
• 5.7 Final Remarks 209
• 5.8 Exercises 209

Chapter 6 Nonlinear Regression 213

• 6.1 Introduction 213
• 6.2 Method-of-Moments Estimators for Nonlinear Models 215
• 6.3 Nonlinear Least Squares 224
• 6.4 Computing NLS Estimates 228
• 6.5 The Gauss-Newton Regression 235
• 6.6 One-Step Estimation 240
• 6.7 Hypothesis Testing 243
• 6.8 Heteroskedasticity-Robust Tests 250
• 6.9 Final Remarks 253
• 6.10 Exercises 253

Chapter 7 Generalized Least Squares and Related Topics 257

• 7.1 Introduction 257
• 7.2 The GLS Estimator 258
• 7.3 Computing GLS Estimates 260
• 7.4 Feasible Generalized Least Squares 264
• 7.5 Heteroskedasticity 266
• 7.6 Autoregressive and Moving-Average Processes 270
• 7.7 Testing for Serial Correlation 275
• 7.8 Estimating Models with Autoregressive Errors 285
• 7.9 Specification Testing and Serial Correlation 292
• 7.10 Models for Panel Data 298
• 7.11 Final Remarks 305
• 7.12 Exercises 306

Chapter 8 Instrumental Variables Estimation 311

• 8.1 Introduction 311
• 8.2 Correlation Between Error Terms and Regressors 312
• 8.3 Instrumental Variables Estimation 315
• 8.4 Finite-Sample Properties of IV Estimators 324
• 8.5 Hypothesis Testing 330
• 8.6 Testing Overidentifying Restrictions 336
• 8.7 Durbin-Wu-Hausman Tests 338
• 8.8 Bootstrap Tests 342
• 8.9 IV Estimation of Nonlinear Models 345
• 8.10 Final Remarks 347
• 8.11 Exercises 347

Chapter 9 The Generalized Method of Moments 352

• 9.1 Introduction 352
• 9.2 GMM Estimators for Linear Regression Models 353
• 9.3 HAC Covariance Matrix Estimation 362
• 9.4 Tests Based on the GMM Criterion Function 365
• 9.5 GMM Estimators for Nonlinear Models 369
• 9.6 The Method of Simulated Moments 383
• 9.7 Final Remarks 393
• 9.8 Exercises 394

Chapter 10 The Method of Maximum Likelihood 399

• 10.1 Introduction 399
• 10.2 Basic Concepts of Maximum Likelihood Estimation 399
• 10.3 Asymptotic Properties of ML Estimators 408
• 10.4 The Covariance Matrix of the ML Estimator 415
• 10.5 Hypothesis Testing 420
• 10.6 The Asymptotic Theory of the Three Classical Tests 429
• 10.7 ML Estimation of Models with Autoregressive Errors 435
• 10.8 Transformations of the Dependent Variable 437
• 10.9 Final Remarks 443
• 10.10 Exercises 444

Chapter 11 Discrete and Limited Dependent Variables 451

• 11.1 Introduction 451
• 11.2 Binary Response Models: Estimation 452
• 11.3 Binary Response Models: Inference 460
• 11.4 Models for More Than Two Discrete Responses 466
• 11.5 Models for Count Data 475
• 11.6 Models for Censored and Truncated Data 481
• 11.7 Sample Selectivity 486
• 11.8 Duration Models 489
• 11.9 Final Remarks 495
• 11.10 Exercises 495

Chapter 12 Multivariate Models 501

• 12.1 Introduction 501
• 12.2 Seemingly Unrelated Linear Regressions 501
• 12.3 Systems of Nonlinear Regressions 518
• 12.4 Linear Simultaneous Equations Models 522
• 12.5 Maximum Likelihood Estimation 532
• 12.6 Nonlinear Simultaneous Equations Models 540
• 12.7 Final Remarks 543
• 12.8 Appendix: Detailed Results on FIML and LIML 544
• 12.9 Exercises 550

Chapter 13 Methods for Stationary Time-Series Data 556

• 13.1 Introduction 556
• 13.2 Autoregressive and Moving-Average Processes 557
• 13.3 Estimating AR, MA, and ARMA Models 565
• 13.4 Single-Equation Dynamic Models 575
• 13.5 Seasonality 579
• 13.6 Autoregressive Conditional Heteroskedasticity 587
• 13.7 Vector Autoregressions 595
• 13.8 Final Remarks 599
• 13.9 Exercises 599

Chapter 14 Unit Roots and Cointegration 605

• 14.1 Introduction 605
• 14.2 Random Walks and Unit Roots 605
• 14.3 Unit Root Tests 613
• 14.4 Serial Correlation and Unit Root Tests 620
• 14.5 Cointegration 624
• 14.6 Testing for Cointegration 636
• 14.7 Final Remarks 644
• 14.8 Exercises 644

Chapter 15 Testing the Specification of Econometric Models 650

• 15.1 Introduction 650
• 15.2 Specification Tests Based on Artificial Regressions 651
• 15.3 Nonnested Hypothesis Tests 665
• 15.4 Model Selection Based on Information Criteria 675
• 15.5 Nonparametric Estimation 677
• 15.6 Final Remarks 692
• 15.7 Appendix: Test Regressors in Artificial Regressions 692
• 15.8 Exercises 695

References 702

好书。

非常感谢楼主能够免费提供。

谢谢了

楼主真是好人，谢谢。

This is the 1999 book, an easy one, at a level similar to Greene's.This ebook is available for a long time.

The estimation and method book is the 1992 one, a much advanced one.

Actually the first version of this book was published in2003.

“Econometric Theory and Methods is a graduate-level econometrics text that was published by Oxford University Press (New York) in October, 2003 with a 2004 copyright. The ISBN is 0-19-512372-7.”

I got this book from my TA, who is a Chinese student also. And he got this book from his major professor who is a Brazilian. When I studied econometrics (2004), I can not find this book in the internet. Maybe you can find this book somewhere now for free, but I only ask for three. It is really cheap.

I need money to buy some materials here, so I post this book. After I got enough money, I will free this book. If some of you need this book now, but do not have enough money for it, please let me know. I will send a copy to you.

I agree this book is in the same level of Greene’s. But it is clearer in explanation of some theories and tests. In my opinion, it is very good for intermediate students. Especially for those who finish Greene’s book but still can not fully understand the concept of panel data and how to carry out tests for the panel data set. (^-^)

If you are an advanced student, no textbook needed. You only need to read the econometric papers published on the Econometica, AER -----. (^-^)

[此贴子已经被作者于2007-2-24 15:01:31编辑过]

非常感谢。

非常感谢！