Category Archives: economics

Social behavior VS Individual behavior

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!

A speech on econometrics and R

From next week I'll go to Beijing and Shanghai respectively to give a speech on R. Yesterday I just finished the beamer for presentation in English. Not very long, because I'm afraid of making any serious mistakes.

Here I would like to list the outline.

Topic:

From Economics to R --Using R in Economics and Econometrics

(At first it was "Using R in Economics, Statistics and Econometrics". However, I think it is no good to mention "statistics" since I'm not professional in that area. The same to "economic statistics". Therefore I only mention economics and econometrics instead eventually.)

Outline:

1 Economics and Statistics

  • The Irreplaceable Support
  • Software about econometrics

2 Main Econometric Methods

  • Similar to statistics
  • Realization in R

3 Now Work with R!

  • Transfer the Data
  • Cooperate with LATEX
  • My own experience

Maybe the outline is a little too simple, but in fact I don't have too much to talk, since I'm a beginner of economics and R myself. I really appreciate the opportunity to give a speech on the 2nd Chinese R Conference, and I do hope that there will all right. Anyway, I have no better choice but do my best.

A more detailed post may appear after the lecture.

[2010.02. 20 Updated]

Probability, Information and Economics

These days I was busy reading the biography of John Maynard Keynes, the most famous economist in the past century. One point mentioned in that book attracted my attention -- that is about his ideas on probability.

Every one who has studied macroeconomics must know a word "rational expectations". That is a great issue if talked. Simply, as the wikipedia says,

To assume rational expectations is to assume that agents' expectations are wrong at every one instance, but correct on average over long time periods. In other words, although the future is not fully predictable, agents' expectations are assumed not to be systematically biased and use all relevant information in forming expectations of economic variables.

Here  I do not want to say much about it. I'd like to mention another area, Information Economics. Typically, information economics deals with the situation that there is asymmetric information between principal and agent. Then as we all know, there is moral hazard and adverse selection. With the application of game theory, the common issues can be solved. However, seldom do I read paper discussing about the role of information in economic activities in other approaches. Therefore, followed Keynes' idea, I wonder what will happen if the spread of information is introduced into the economic activities.

Simply, probability reflects the situation that we do not know enough about how the real world functions. Therefore, we use probability to describe the combination every possible result. There is an interesting question: the normal distribution. I'll talk about it later on.

As the aim of science, we are pursuing the ability to predict. I know many people will have different ideas, but it does not matter much. At least, we want to know the mechanisms in every particular field. That is, we are pursuing "certainty" instead of "uncertainty". From uncertainty to probability, then to certainty, in this way we know much better about the real world. It is an old philosophic issue: is there a fixed point?

Then what will happen if the knowledge spreads? I have not got a clear understanding yet. The disappearance of probability is too hard to imagine. We can use "normal distribution" to describe some phenomenons, such as people's height, weight. The result is a description of a group, but not that accurate for a particular person. To predict a person's height, for example, we should get enough information, if applicable, his gene, his nutrition, and what he did in the past... Maybe it is too hard to define what is "enough". Anyway, the probability can be replaced under a special circumstance.

In the first step, I want to talk about how the spread of information influences the social activities. I think we have underestimated the importance of information in economics, or we have no applicable models to explain. I do not know whether more modern mathematical tools are needed in the explanations. As least, I need to read more about the history of probability, including the famous debate between frequency school and Bayesian. And maybe more knowledge about psychology and communication are essential. I want to talk about it later after learning measure theory.

The difference between studying math and economics

These words were written down while I was driven crazy by the theorems and their proofs in functional analysis. Just some jokes for fun. Merry Christmas!

Title: The difference between studying math and economics

  1. Studying economics will make you confident about your IQ, while math will destroy all of you beliefs about your IQ.
    Deduction 1: If you failed in studying economics, please doubt your textbooks and teachers; if you failed in math, please suspect your IQ first.
  2. While you are proving a economic theorem, you can simply persuade yourself that "these conclusion are driven from math" so you can easily prove all of the theorems with the presumption that some conclusions are true; while you are trying to give a proof for a mathematical theorem, the author is doing his best to find the most basic assumptions and there is a long and meticulous proof waiting for you...
    Deduction 2: Creativeness in economics in easy, since you can add an assumption anywhere you need; however, it is really difficult in math, since you cannot make any additional assumptions if unnecessary.
  3. Studying the basic->intermediate->advanced level of economics is like building a house: the introductory level teaches the basic economic principles (build the framework); the intermediate level tells you how to analyze them with graphs (walling); the advanced level force you to use mathematical tools to prove the familiar principles strictly (decoration).
    However, in math, it is like taking down a house: you should drop all decorations first with calculus; then find its frame with real analysis and functional analysis.
  4. While studying economics, you should play with the dirty data in the real world everyday; when studying math, you can ignore anything in the real world and close yourself in your silent room.
  5. Dealing with data in econometrics, an economic student will go shopping -- list all available econometric models and try them one by one; a math student will offer "VIP" custom service -- design a particular model according to the nature of the data.

Anyway, there are only some jokes just for fun! At last,

Merry Christmas!