Recently I fell in love with social network… Therefore, it is unavoidable to add some social network analysis results into my graduation thesis. Here are some interesting graphs used in my paper, which I would like to share with you online. They are all about “the social network of economists”, i.e. the academic circle of economics.

Full view of the economists’ world, without labels.

The bigger size of nodes denotes the higher level of connections with others (degree/pagerank). (2000-present). An expandable vector diagram can be download here:  all_10_nolabel.pdf

Full view of economists’ world, with grey edges (2000-present)

The structure (reduced) of economists’ social network, with labels of names (2000-present).

An expandable vector diagram can be download here: all_10_main_all_label.pdf
You can find more graphs by continuing reading.
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I’m glad to announce that now the preview version for my brochure Play Economics with R has been released! This time I publish the first two chapters, which were just finished several days ago. At present it is written in Chinese, so there is only an English content for none-Chinese readers.

Content

Chapter 1 Get familiar with R

1.1 Data Import……………………………….. 6
1.2 Summary the data………………………………… 7
1.2.1 Average value………………………………. 7
1.2.2 Linear regression (ordinary least squares, OLS)……………….. 8
1.3 Plot a regreesion figure……………………………….. 9
1.4 Point prediction………………………………….. 10
1.5 Multiple linear regression………………………………. 10
1.6 Save and edit the code……………………………… 11
1.7 Search for help………………………………… 11

Chapter 2 Start from cross-section data

2.1 Parameter test………………………………… 12
2.1.1 t test………………………………. 13
2.1.2 F test………………………………. 13
2.2 Confidence Intervals………………………………… 14
2.3 Dummy variables………………………………… 14
2.3.1 grouped by the nature……………………………. 14
2.3.2 grouped by the value…………………………… 14
2.3.3 interaction items…………………………….. 15
2.3.4 specify the based group……………………………. 17
2.4 Heteroscedasticity test……………………………….. 18
2.4.1 BP test (Breusch-Pagan Test)…………………… 19
2.4.2 White test (White test for heteroskedasticity)……………. 20
2.5 Robust standard deviation……………………………….. 20
2.6 Weighted least squares estimation (WLS)………………………… 21
2.6.1 with disturbance form known …………………………. 21
2.6.2 feasible generalized least squares (Feasible GLS, FGLS)……………. 22
2.7 Generalized Linear Estimation (GLM)…………………………… 24
2.7.1 Maximum Likelihood Estimation (MLE)………. 25
2.7.2 Probit and Logit models………………………… 25
2.7.3 Tobit model…………………………….. 26
2.7.4 Ordered Logit / Probit…………. 27
2.8 Count Model…………………………. 28
2.8.1 Poisson Regression Model………………. 28
2.8.2 test for dispersion………………………… 29
2.8.3 Negative binomial regression model…………. 30
2.8.4 Zero-inflated Poisson model (ZIP)………… 30
2.9 Sample Selection Bias……………………………… 32
2.9.1 Heckit model……………………………. 32
2.10 Simultaneous Equations Model………………………………. 33
2.10.1 two-stage least squares (2SLS) and instrument variable………………. 33
2.10.2 Simultaneous Equations Model Estimation: Seemingly Unrelated Regression (SUR)… 34
2.11 Proxy Variables……. 35

Download

You may download it from GitHub: http://github.com/cloudly/Play-Econometrics-with-R/downloads (I’ll keep updating this page)

Please tolerate the mistakes and typo, as well as some formatting problems I need to come over in the future.

News and Feedback

If you want to keep up with the latest news of this brochure, please send an email to: publication@cos.name or cloudlychen@gmail.com

Your feedback is welcome! Please also send to publication@cos.name or cloudlychen@gmail.com

What‘s Next？

I’m currently working on Chapter 4 Panel Data Analysis (so I skip Chapter 3 Time Series temporarily). Chapter 4 will include several interesting methods, like Fixed / Random Effect, Panel Data tests and GMM estimator, etc. Please tell me what you are looking for in my brochure and I’ll add them if possible.

Well, in fact it is not a piece of news. It is the title of a paper I wrote last winter. After finishing it, I went on doing something else and forgot it. Now it is already a new spring, I do not want to submit it to any journals since I have nothing fresh to add into it. Without anything new, I don’t have the incentive to edit it. Therefore, I share it with you here.

Title

What Do We Pay For Asymmetric Information? The Mechanism Evolution of Reputation, Punishment and Barriers to Entry in Online Markets

Abstract

The appearance of the Internet reduces transaction costs greatly, and brings the boom of online markets. While we are trying to regard it as the most realistic approximation of perfect competition market, the asymmetric information and a series of problems caused by it stop us from dreaming. As the old saying goes, there is no free lunch. This summer witnessed the collapse of the reputation system in Taobao, the biggest online transaction website in China. In fact, during the evolution of mechanisms in online markets, reputation, punishment and barriers to entry have been established in turn. What do we pay for maintaining these mechanisms? In which circumstance will they be effective?

In this paper I try to build a series of models within the principal-agent framework and repeated games to explain why and what we should pay for asymmetric information while enjoying shopping online. Specifically, these mechanisms are considered step by step and their boundary validation conditions are discussed. Finally, as the conclusion indicates, in a larger range that a mechanism is effective, the more opportunity cost should be paid as a rent for information.

Download (English Version)

Copyright Announcement: Please do not change any content without my permission. Please do not use it for commercial purpose. Please do not publish it anywhere else.

• Go to my “Papers and Presentations” page and download it.
• Download final PDF Now (right click on the link and choose “save as”).
• If you need the original Chinese version, please email me: cloudlychen@gmail.com

If you would like to mention or quote it in your article, please link it to this page or copy this link: What Do We Pay For Asymmetric Information? The Mechanism Evolution of Reputation, Punishment and Barriers to Entry in Online Markets

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Well, recently I’m focusing on an interesting model –social network and thinking about an old issue –social behavior. The social network model is really attractive (if it can be regarded as a model, or more exactly, a theory), especially for people like me who are wondering the traditional assumptions in classical economics while trying to borrow something from other subjects, like sociology.

Using complex network as a mathematical tool, the social network model includes so many factors that cannot be described in the past. Well, I should admit here that I haven’t taken any related courses yet, and all I know about sociology are inherited from some unprofessional books. I should also admit that I was really attracted by behavior economics last winter, but until now had I started to “study” it in an academic way. Maybe the reasons are pretty simple: first, I was busying applying for postgraduate study positions last winter; second, there was not a good teacher who was able to teach this course; third, I have no idea about which book (or textbook) should be chosen as an introductory one.

Well, I need some time to make it clear in my mind that how social network works. However,  I’ve got a much easier question yet. That is, in traditional macroeconomic models, like the Lucas’ island model, when we are trying to calculate the sum of all individual’s save, at most time we simply add them together, (i.e. a*N, where N is the number of population).  However, I think at least the individual’s save should be regarded as a stochastic variable (e.g follows a normal distribution, or Brownian movement), so the sum should also follow a normal distribution. Well, in econometrics we do not need to worry about this question. But I wonder whether it would be valuable if we can make this small change.

In the example above, I want to figure out that the micro-foundations for macroeconomics should be dug more deeply in order to persuade readers.  Borrowing some mature conclusions from other fields, this task shall be easier. Alternatively, economists should make an effort (maybe something can be found from data) to know more about the relationships between individual behavior and social behaviors, thereby establishing a proper model to describe them. Personally speaking, the study of social network may be helpful, since different from other social science, at least it has a mathematical model…And the diffusion of information can be easily introduced into macroeconomic models in this way…WoW!

More than  a month without updating… Yes, I was busy doing something else, and that was traveling. I was lucky enough to enjoy a period of free time, and relaxed myself pretty well.

Now it is the time to start something useful, since the spring festival has gone. I need to be responsible for my promise. Therefore, I choose to begin to write the brochure about econometrics and R, the most up-to date statistic software.

Name

Play Econometrics with R

I use “play” to avoid being responsible for any potential academic faults Indeed, I will correct the bugs as soon as I know.

Aim

In this brochure, I’ll introduce typical econometric methods one by one and their realization in R. Of course, a huge volume of examples and data will appear (and that is the most knotty problem for me at the moment). I’ll cover some public examples (i.e. published ones from current books,  e.g Introductory Econometrics: A Modern Approach by Jeffrey M. Wooldridge), and also some meaningful ones (applications in different fields) from scholar articles with data published. I should admit it is a really challenging task, and I need many helps from friends.

Readers

I hope this brochure can be helpful for those groups:

• the statistics students who begin to know and  use econometrics, especially for economic problems.
• the economics students who want to improve their analysis with a more powerful tool — R, instead of Stata or SPSS.

This brochure will help the first group see how econometrics functions in economic analysis, and will bring introductory guide for the second group.

Remarks

More features needed to be announced here:

• This brochure is totally free, and will published regularly on the Internet. If possible, it will be realized with the help through Git of Cos.name, the biggest online statistics community in China.
• I’ll use Latex (Lyx) + Sweave + R as my tools. For more information about this combination, please see here (in Chinese from Yihui’s Blog) .
• At present, this brochure will be written in Chinese (I’m really sorry). But after several revisions, and if anyone calls for needs, I will rewrite another version in English.