Tag Archives: Probability

note on beliefs and expectation

Yesterday and today I spend several hours on the conference held by Crei,

Information, Beliefs and Expectations in Macroeconomics

20 & 21 May 2011

Organized by Kristoffer Nimark (CREI & UPF) and Bartosz Maćkowiak (European Central Bank).

To be honest, I have waited for the conference for a while, as I was writing things on beliefs and expectations. However, this conference is a little bit out of my expectation - so again, my expectations deviates from the truth. My poor background in macro is definitely not enough to support me for understanding the presentations, and among all of them, I picked a few to stay and thus make myself confused. They were:

Exogenous Information, Endogenous Information, and Optimal Monetary Policy
Luigi Paciello | Einaudi Institute for Economics and Finance
*Mirko Wiederholt | Northwestern University
Discussant: Jordi Galí | CREI & Universitat Pompeu Fabra

Learning about Consumption Dynamics
Michael Johannes | Columbia U., Columbia Business School
Lars Lochstoer | Columbia U., Columbia Business School
*Yiqun Mou | Columbia U., Columbia Business School
Discussant: Francisco Barillas | Emory U., Goizueta Business S.

Public’s Inflation Expectations and Monetary Policy
Leonardo Melosi | London Business School
Discussant: Francesco Bianchi | Duke University

Just as I had expected, it was too easy for me to get lost in these presentations. In a few minutes I got the feeling that I don't know what's going on so ever. well...Except for the fantastic graphs I have seen, I haven't gained much intuition from them.

A noteworthy point is in Mou's presentation, he empirically showed the convergence to rational expectation. I should admit I don't really understand the techniques he utilized, and so are the debates afterwards. After his presentation, I talked to him with the learning process a little bit, but haven't benefited a lot... there is still a long way to go.

Also, I found another interesting book to read,

1587, a year of no significance : the Ming dynasty in decline / Ray Huang

Very nice book on history. I really treasure this period of time that I have got enough space to read and think across different subjects. As planned before, I also found Keynes' book,

A Treatise on probability

Things are so beautiful!

A few books want to read

Fortunately or accidentally, I only have two classes this term. Meanwhile, they separate them into four days, so I only have two-hours class every day from Monday to Thursday. Compared to my previous schedule, it is too relaxing.

An advantage now is that I have enough time to read and think. Today I found Becker's book by chance, when I was browsing the literature on "social economics", or socio-economics. It is quite exciting, and I have realized how deep the water might be- before I was only using my naive intuition that there is something I can contribute soon.

The book I'm talking about now is

Gary S. Becker and Kevin M. Murphy, 2001, Social Economics: Market Behavior in a Social Environment.

Before I was paying more attention solely to network economics, and it turned out to be that they were quite similar to each other in most sense; however, socio-economics is for sure more broad.

Moreover, I took a few hours finishing reading another book,

Salsburg, D. (2002) The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century

From the name, you can see that this book is about basic statistics. To save time, I read its Chinese translation. Not very long, but very exciting - maybe I have been, and will always be attracted by mathematics and statistics. Especially the later one, perhaps due to the fact that I have so many friends in this area, is one field beyond economics that has influenced me the most, and more on the level of conception and methodology than techniques or actual methods.

@Roma Things remain to be clear

@Roma. Things remain to be clear

While reading this book, it reminds me another book I read before, which is about the famous economist Keynes,

Robert Skidelsky, 2005, John Maynard Keynes: 1883-1946: Economist, Philosopher, Statesman

What impressed me most at that time was not Keynes' contribution to economics - although nobody can neglect that, but his ideas on probability.  Until now, I still have the wish that one day I want to read Keynes' original book on probability somewhere.

I want to read Becker's book only for the reason that I need an idea for my history paper. One question I have been seeking for the answer for a while: why do we need to care about the network structure? Before, I was only arguing that the "summation is a naive way to draw the group's characteristics"; now it seems that I need to really re-think about this argument. In addition to sum or mean, people have developed distribution to help understand the world; furthermore, from central limit theorem, normal distribution can be utilized in most scenarios. Therefore, under what particular case will summation cause a severe problem?

Another thing I'm thinking about now is after reading the "Lady tasting tea", a term still remains to be explained more clearly: frequency school and Bayesian school's debate on the definition of probability. On one side we are lucky today that following Baye's idea will not be regarded as heterodox any more; on the other side, although his idea itself is very simple, how to make a perfect use of it is still a very tricky and should be dealed with carefully.

I'll stop here for now, and see whether I can gain some new senses soon. This year is too short- I need a longer time to make all things clear.

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.