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内容説明
A complete and up-to-date survey of microeconometric methods available in Stata, Microeconometrics Using Stata, Revised Edition is an outstanding introduction to microeconometrics and how to execute microeconometric research using Stata. It covers topics left out of most microeconometrics textbooks and omitted from basic introductions to Stata.
This revised edition has been updated to reflect the new features available in Stata 11 that are useful to microeconomists. Instead of using mfx and the user-written margeff commands, the authors employ the new margins command, emphasizing both marginal effects at the means and average marginal effects. They also replace the xi command with factor variables, which allow you to specify indicator variables and interaction effects. Along with several new examples, this edition presents the new gmm command for generalized method of moments and nonlinear instrumental-variables estimation. In addition, the chapter on maximum likelihood estimation incorporates enhancements made to ml in Stata 11.
Throughout the book, the authors use simulation methods to illustrate features of the estimators and tests described and provide an in-depth Stata example for each topic discussed. They also show how to use Stata’s programming features to implement methods for which Stata does not have a specific command. The unique combination of topics, intuitive introductions to methods, and detailed illustrations of Stata examples make this book an invaluable, hands-on addition to the library of anyone who uses microeconometric methods.
著者について
University of California, California, USA Indiana University, Bloomington, Indiana, USA
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カスタマーレビュー
最も参考になったカスタマーレビュー
5 人中、4人の方が、｢このレビューが参考になった｣と投票しています。
形式:ペーパーバック
stataの基本的な利用方法から、データ整理、クロスセクション分析、パネル分析
時系列分析、シュミレーション等幅広くカバーししています。
ですが、初めてstataを利用する人には少しハードルが高いかもしれないので、
松浦寿幸の「Stataによるデータ分析入門」などを読んでからこちらを読むと、
さらに理解が進むと思います。
各章では、簡単な理論の解説とその理論を使って実際のデータを動かしながら
コマンドの解説を行うので、マスターしやすくなっています。
一つ注意点として理論の解説にはそれほど踏み込んでいないので、GreeneやHayashiなどで
分からないところは参照したほうがいいです。
このように、理論とstataの基本を理解している人がこの本を読むことで、
より深い実証分析ができるのではないかと思います。
星を一つだけ減点させた理由は、少し込み入った話になると説明を省略していたり、
ユーザーコマンドに逃げていたりするので、このような点もしっかり説明が欲しかったからです。
ですが普通に実証分析をする分には、本書に掲載されているコマンドが分かれば十分だと思うので
理論書と一緒にこの本を持っていて損はないと思います。
時系列分析、シュミレーション等幅広くカバーししています。
ですが、初めてstataを利用する人には少しハードルが高いかもしれないので、
松浦寿幸の「Stataによるデータ分析入門」などを読んでからこちらを読むと、
さらに理解が進むと思います。
各章では、簡単な理論の解説とその理論を使って実際のデータを動かしながら
コマンドの解説を行うので、マスターしやすくなっています。
一つ注意点として理論の解説にはそれほど踏み込んでいないので、GreeneやHayashiなどで
分からないところは参照したほうがいいです。
このように、理論とstataの基本を理解している人がこの本を読むことで、
より深い実証分析ができるのではないかと思います。
星を一つだけ減点させた理由は、少し込み入った話になると説明を省略していたり、
ユーザーコマンドに逃げていたりするので、このような点もしっかり説明が欲しかったからです。
ですが普通に実証分析をする分には、本書に掲載されているコマンドが分かれば十分だと思うので
理論書と一緒にこの本を持っていて損はないと思います。
Amazon.com で最も参考になったカスタマーレビュー (beta)
Amazon.com:
5つ星のうち 4.9
11件のカスタマーレビュー
11 人中、11人の方が、｢このレビューが参考になった｣と投票しています。
5つ星のうち 5.0
Best book for modeling in STATA
2010/12/16
By S. Frazelle
- (Amazon.com)
形式:ペーパーバック|Amazon.co.jpで購入済み
This is an excellent econometrics book for people who want to USE econometrics and still understand, theoretically, the difference between the models. There are brief descriptions of the theory (including equations) about each model before a very detailed explanation about how to code the model into STATA. I've taken several Econometrics courses and, for me, the challenge has typically been, "yes, but how do I transform my data to do that in real life". Answers are here as long as you are comfortable with using the typical STATA manual instructions. I'd say the advantage of this book over the help manual is how nicely all the models are packaged together. I found myself simply reading through the book and trying models and robustness checks I might not have previously thought of. It covers everything from cross-sectional to panel, including bootstrapping and simulations. It also includes some handy graphing techniques.
Coupled with the help guide already installed in STATA 11, this book is perfect for taking data from a raw form and transferring it into the most up-to-date models. The applications go much further than a grad school textbook.
Coupled with the help guide already installed in STATA 11, this book is perfect for taking data from a raw form and transferring it into the most up-to-date models. The applications go much further than a grad school textbook.
4 人中、4人の方が、｢このレビューが参考になった｣と投票しています。
5つ星のうち 5.0
a godsend
2012/4/17
By Johan
- (Amazon.com)
形式:ペーパーバック|Amazon.co.jpで購入済み
I'm finishing up my undergraduate in econ, and I've been working really hard on doing applied research using Stata, and this book has been an absolute godsend. I'm taking Econometrics right now, and I have an actual textbook for the class, but I decided to buy this book too, and it has explained Stata better than either my professor or textbook has at all. There's a massive amount of information to the book, but thanks to incredibly good organization, and a detailed index, the book works great for either either reference or reading cover to cover
3 人中、3人の方が、｢このレビューが参考になった｣と投票しています。
5つ星のうち 5.0
Should be Required Text for Econometrics Classes
2012/5/28
By M. Whited
- (Amazon.com)
形式:ペーパーバック|Amazon.co.jpで購入済み
This book is terrific. It provides a nice bridge between the Stata manuals and traditional econometrics textbooks (like Wooldridge or Greene). It gives details not only on the Stata commands, but also context for when you might choose different model specifications or tests.
The examples are great. For instance, in section 5.3 "Modeling heteroskedastic data" using GLS, the authors describe two different ways to deal with heteroskedasticity: robust standard errors and FGLS. First they walk you through creating a simulated dataset, performing OLS estimation, then performing OLS with heteroskedastic-robust standard errors (using the "robust" option), and compare the results. Next they show you how to plot the errors to visualize the nature of the heteroskedasticity, as well as how to perform different tests for heteroskedasticity in Stata (and which ones assume normality). Then they walk you through step-by-step how to implement FGLS (the second method), concluding with a discussion of how to augment FGLS with weighted least squares for robustness.
I love that it is concise but thorough, and very well organized. The cross-references help a lot when the authors refer to something that they've explained in more detail elsewhere.
I only wish I had discovered it during my first semester of graduate level econometrics. I highly recommend it, and think it would be great if professors required it (or at least encouraged their students to get it). It's appropriate for upper-level undergraduate or master's level econometrics classes.
The examples are great. For instance, in section 5.3 "Modeling heteroskedastic data" using GLS, the authors describe two different ways to deal with heteroskedasticity: robust standard errors and FGLS. First they walk you through creating a simulated dataset, performing OLS estimation, then performing OLS with heteroskedastic-robust standard errors (using the "robust" option), and compare the results. Next they show you how to plot the errors to visualize the nature of the heteroskedasticity, as well as how to perform different tests for heteroskedasticity in Stata (and which ones assume normality). Then they walk you through step-by-step how to implement FGLS (the second method), concluding with a discussion of how to augment FGLS with weighted least squares for robustness.
I love that it is concise but thorough, and very well organized. The cross-references help a lot when the authors refer to something that they've explained in more detail elsewhere.
I only wish I had discovered it during my first semester of graduate level econometrics. I highly recommend it, and think it would be great if professors required it (or at least encouraged their students to get it). It's appropriate for upper-level undergraduate or master's level econometrics classes.
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5つ星のうち 4.9
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