2000币求书 Microeconometrics Using Stata, 2nd Edition

论坛上有好几个非高清的第一版。这里求高清的第二版。非常感谢。

【作者(必填)】by A. Colin Cameron (Author), Pravin K. Trivedi (Author)

【文题(必填)】Microeconometrics Using Stata: Revised Edition 2nd Edition

【年份(必填)】2010

【全文链接或数据库名称(选填)】http://www.stata.com/bookstore/microeconometrics-stata/

这是第二版的中文版，供您参考。
链接是：https://bbs.pinggu.org/thread-4467139-1-1.html

这是另外一个第二版中文版的链接：https://bbs.pinggu.org/thread-4675416-1-1.html

xinchuzu 发表于 2016-7-26 22:54
自己看，然后决定是不是需要的。压根就没有看到英文第二版！

好人[em27][em27]

[size=+2]A. Colin Cameron and Pravin K. Trivedi [size=+2]MICROECONOMETRICS USING STATA SECOND EDITION: 2022 Two volumes   1,675 pages   Stata Press [size=+2][size=+2]

[size=+1]
NOW AVAILABLE at https://www.stata-press.com/books/microeconometrics-stata/

Volume 1: Cross-Sectional and Panel Regression Models
Volume 2: Nonlinear Models and Causal Inference Methods

The book includes coverage of Stata 17 (released April 2021).

[size=+1]Detailed Table of Contents for 2022 Second Edition

[size=+1]The second edition covers over ten years of both enhancements to Stata and developments in the methods most commonly-used in empirical microeconometrics analysis. [size=+1][size=+1]Our target user base consists of practitioners of applied microeconometrics, and the focus of the book remains the use of linear and nonlinear regression methods for cross-section and short panel data. [size=+1][size=+1][size=+1]We have attempted to not only update our previous coverage to bring it in line with newer tools in the latest edition (version 17) of Stata but also to bring into the book many topics and methods that are now actively studied and increasingly used in applied microeconometrics.
The new edition is much expanded (1,675 pages) and is split into two volumes. [size=+1][size=+1]To assist the reader we have provided numerous cross-references and a much lengthier subject index.

The first volume (chapters 1-15) focuses on the linear regression model as well as providing a brief introduction to nonlinear regression models. [size=+1][size=+1]This volume is an expanded version of chapters 1-10, and 12-13 and the appendices of the First and Revised Editions. In places there is greater explanation of underlying methods than in earlier editions, and much of the first volume is intended to be suitable for an advanced undergraduate course in addition to serving graduate students and researchers.

The second volume (chapters 16-30) covers the standard nonlinear models (chapters 11 and 14-18 of the earlier editions) as well as more advanced and more recent material. In addition to updated versions of existing chapters, the second volume includes new chapters on duration models, treatment effects in randomized control trials, treatment effects with endogenous treatments, parametric models for endogeneity and heterogeneity, spatial regression, semiparametric regression, machine learning and prediction, and Bayesian methods.

SECOND EDITION: VOLUME  1[size=+1]: Cross-Sectional and Panel Regression Models1.  Stata basics
2.  Data management and graphics
3.  Linear regression basics
4.  Linear regression extensions
5.  Simulation
6.  Linear regression with correlated errors
7.  Linear instrumental variables regression
8.  Linear panel-data models: Basics
9.  Linear panel-data models: Extensions
10. Introduction to nonlinear regression
11. Tests of hypotheses and model selection
12. Bootstrap methods
13. Nonlinear regression methods
14. Flexible regression: finite mixtures and nonparametric
15. Quantile regression
Appx.A: Programming in Stata
Appx.B: Mata
Appx.C: Optimization in Mata       

SECOND EDITION: VOLUME 2: Nonlinear Models and Causal Inference Methods16. Nonlinear optimization methods
17. Binary outcome models
18. Multinomial models
19. Tobit and selection models
20. Count-data models
21. Survival analysis for duration data
22. Nonlinear panel models
23. Parametric models for heterogeneity and endogeneity
24. RCTs and exogenous treatment effects
25. Endogenous treatment effects
26. Spatial regression
27. Semiparametric regression
28. Machine learning for prediction and inference
29. Bayesian methods: Basics
30. Bayesian methods: MCMC algorithms

For the earlier First Edition and Revised Edition see http://cameron.econ.ucdavis.edu/musbook/mus.html

我有哈，需要可以联系

放个图，有需要找我