Mean and Variance of Lognormal Distributions

In summary, you are having difficulty converting the growth consumption rate to a lognormal distribution. The problem is #3 in the document below. You can look at this problem from #3 in the Solution Manual I posted to this forum. Thanks.
  • #1
royalstatus
3
0

Homework Statement


Given that the natural log of the growth consumption rate is conditionally normally distributed. I am trying to convert it to a lognormal distribution, but I keep getting a variance that is different from what is in the solution manual. The problem is #3 in the document below
http://www.wiwi.uni-frankfurt.de/profs/faia/welcome_files/ch2ans.pdf

Homework Equations


Log Ct+1/Log Ct ~ N[Et(logCt+1/logCt), Var (logCt+1/logCt)]

The Attempt at a Solution



I re-wrote Log Ct+1/Log Ct as an exponential function since log and e cancel out, and the mean is simply the expected value of function, but the variance I got was -1/2σ(Var Ct+1/Ct) which is different from what the solution manual says.

My problem is I don't understand how they got 1/2σ^2(Var Ct+1/Ct).
If anyone can explain that to me, I would be highly grateful.

For a clearer understanding of the question, you can look at #3 from the Solution Manual I posted above. It is Chapter 2, # 3 from Obstfeld and Rogoff's Foundation of International Economics. Thanks

https://docs.google.com/viewer?a=v&...2MtYmIxZi00OGVmLTkyMWUtYmU1M2E4Y2U0NGE4&hl=en
 
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  • #2
royalstatus said:

Homework Statement


Given that the natural log of the growth consumption rate is conditionally normally distributed. I am trying to convert it to a lognormal distribution, but I keep getting a variance that is different from what is in the solution manual. The problem is #3 in the document below
http://www.wiwi.uni-frankfurt.de/profs/faia/welcome_files/ch2ans.pdf




Homework Equations


Log Ct+1/Log Ct ~ N[Et(logCt+1/logCt), Var (logCt+1/logCt)]


The Attempt at a Solution



I re-wrote Log Ct+1/Log Ct as an exponential function since log and e cancel out, and the mean is simply the expected value of function, but the variance I got was -1/2σ(Var Ct+1/Ct) which is different from what the solution manual says.

My problem is I don't understand how they got 1/2σ^2(Var Ct+1/Ct).
If anyone can explain that to me, I would be highly grateful.

For a clearer understanding of the question, you can look at #3 from the Solution Manual I posted above. It is Chapter 2, # 3 from Obstfeld and Rogoff's Foundation of International Economics. Thanks

https://docs.google.com/viewer?a=v&...2MtYmIxZi00OGVmLTkyMWUtYmU1M2E4Y2U0NGE4&hl=en

What do you get? For now, just forget the attached document and answer the question for X = exp(Y), where Y is normal with mean m and variance s^2.

RGV
 
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  • #3
The variance I got was -1/2σ(Var Ct+1/Ct)

I think the true variance might have something to do with the moment generating function for the lognormal distribution.

My answer is different from what is in the document, so I'm guessing I'm not thinking of this the right way
 
  • #4
royalstatus said:
The variance I got was -1/2σ(Var Ct+1/Ct)

I think the true variance might have something to do with the moment generating function for the lognormal distribution.

My answer is different from what is in the document, so I'm guessing I'm not thinking of this the right way

Your variance formula cannot possibly be right: it is < 0, while variance is always >= 0 if it exists at all. Anyway, I asked you to forget the attachment and just answer a *simple question* for X = exp(Y) with Y~N(m,s^2). Using Ct and 1/Ct, etc., just confuses the issue. Possibly the reason you are having trouble is that you are so focused on the model and notation in the attachment that you are neglecting some basic probability results and methods that apply to any model, not just the one you are researching.

RGV
 
  • #5
RGV,

Will it be Y~N(ln(m),ln(s^2))?

I'm not particularly sure of the question you are asking.
 
  • #6
royalstatus said:
RGV,

Will it be Y~N(ln(m),ln(s^2))?

I'm not particularly sure of the question you are asking.

I am asking you to find EX and Var(X)---that was the question you originally posed to this forum. You claim your formula for Var(X) is wrong, because it disagrees with something in some paper. Well, maybe your formula is wrong, or maybe it is correct and the paper is wrong. Let us see your formula, so we can tell which is which.

RGV
 

1. What is a lognormal distribution?

A lognormal distribution is a probability distribution that describes the values of a variable whose logarithm follows a normal distribution. This means that the data is skewed to the right and typically has a few large values and many small values.

2. How is the mean of a lognormal distribution calculated?

The mean of a lognormal distribution can be calculated by taking the exponent of the mean of the corresponding normal distribution. In other words, if the mean of the normal distribution is μ, then the mean of the lognormal distribution is eμ.

3. What does the variance of a lognormal distribution represent?

The variance of a lognormal distribution represents the amount of spread or variability in the data. It is a measure of how far the data points are from the mean of the distribution. A higher variance indicates a wider spread of data points, while a lower variance indicates a narrower spread.

4. How is the variance of a lognormal distribution calculated?

The variance of a lognormal distribution can be calculated by taking the exponent of the variance of the corresponding normal distribution. In other words, if the variance of the normal distribution is σ2, then the variance of the lognormal distribution is (eσ-1)e2μ+σ2.

5. Can the mean and variance of a lognormal distribution be negative?

No, the mean and variance of a lognormal distribution cannot be negative. This is because the distribution is defined as the logarithm of a normal distribution, and logarithms of negative numbers are undefined. Therefore, the mean and variance of a lognormal distribution are always positive.

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