<p>Unfortunately for your case all GMM estimators suffer from finite sample bias. In the presence of an endogenous explanatory variable the GMM estimator is only consistent.</p>

<p>There's not much you can do to remedy this issue, except collect more data. Check for consistency of sign and magnitude of estimates between OLS and GMM, as well as sensitivity to instrument choice (if your model is over-identified).</p>

CC BY-SA 3.0
2015-09-15T13:56:06.323Z
Did you have any specific tests in mind?
Quirik
CC BY-SA 3.0
2015-09-16T05:58:01.783Z
Btw, what would be appropriate sample size in order to use GMM? Is there any rule of thumb?
Quirik
CC BY-SA 3.0
2015-09-15T08:18:05.387Z
2015-09-15T08:18:05.387Z
Alan
<p>Price elasticity of demand is computed as follows:</p>

<pre><code>Percent Change in Quantity Demanded (Qd) / Percent Change in Price (P)
</code></pre>

<p>Say you have price and demand quantity data from two years (t=1,2).  To calculate change in Q demanded you would do the following:</p>

<pre><code>[(Qd in t=2)-(Qd in t=1)] / (Qd in t=1)
</code></pre>

<p>The process is the same for price (substitute P for Qd above).</p>

<p>Elasticity may be calculated for other variables as well; not just price and demand.  For example, if you wanted to see how a 1% change in IQ affects the relative change in a student's GRE score you could.  This is done by messing with logs and regression functions.</p>

<p>Hopefully this helps you out a bit.</p>

CC BY-SA 3.0
2015-09-14T20:08:37.827Z
Yes, I am aware of this. Thanks for your effort. Anyway, I was pointing on the possibility to obtain reliable results because of the small sample size which is not recommended when using GMM (or so I read).
Quirik
CC BY-SA 3.0
2015-11-14T10:10:26.447Z
this does not seem to answer the question. also, it is unnecessarily vague (messing with logs)
HRSE
CC BY-SA 3.0
2015-09-14T19:57:13.030Z
2015-09-14T19:57:13.030Z
milk
<p>I have 25 quarterly observations and I want to estimate price elasticity of demand. I intented to use GMM-IV estimator. However, I read that it is not good for small samples. What can you suggest me? Please keep in mind that I am not econometrician by profession.</p>

<elasticity><regression>
Estimating price elasticity of demand
Quirik
# Estimating price elasticity of demand

(Asked by: username_0 on 2015-09-14)

I have 25 quarterly observations and I want to estimate price elasticity of demand. I intented to use GMM-IV estimator. However, I read that it is not good for small samples. What can you suggest me? Please keep in mind that I am not econometrician by profession.

**Tags:** elasticity, regression

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## 2 answers

### Answer by username_1 on 2015-09-15. Score: 1

Unfortunately for your case all GMM estimators suffer from finite sample bias. In the presence of an endogenous explanatory variable the GMM estimator is only consistent.

There's not much you can do to remedy this issue, except collect more data. Check for consistency of sign and magnitude of estimates between OLS and GMM, as well as sensitivity to instrument choice (if your model is over-identified).

> **Comments:**
> **username_0**: Did you have any specific tests in mind?  
> **username_0**: Btw, what would be appropriate sample size in order to use GMM? Is there any rule of thumb?  

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### Answer by username_2 on 2015-09-14. Score: -1

Price elasticity of demand is computed as follows:
Percent Change in Quantity Demanded (Qd) / Percent Change in Price (P)

Say you have price and demand quantity data from two years (t=1,2).  To calculate change in Q demanded you would do the following:
[(Qd in t=2)-(Qd in t=1)] / (Qd in t=1)

The process is the same for price (substitute P for Qd above).
Elasticity may be calculated for other variables as well; not just price and demand.  For example, if you wanted to see how a 1% change in IQ affects the relative change in a student's GRE score you could.  This is done by messing with logs and regression functions.
Hopefully this helps you out a bit.

> **Comments:**
> **username_0**: Yes, I am aware of this. Thanks for your effort. Anyway, I was pointing on the possibility to obtain reliable results because of the small sample size which is not recommended when using GMM (or so I read).  
> **username_3**: this does not seem to answer the question. also, it is unnecessarily vague (messing with logs)  

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