<p>Note that you have an <strong>identification problem</strong> here because price is an endogenous variable. A way to deal with this problem would be to find an instrument (e.g. prices  of the same good in other markets as in <a href="https://www.nber.org/chapters/c6068.pdf" rel="nofollow noreferrer">Hausman (1996)</a>).</p>
<p>Regarding your questions.</p>
<ol>
<li>Yes (although fixed effects are probably not the right wording here).</li>
<li>Yes.</li>
<li>If you want to capture a cross elasticity effect you need to introduce the <code>own price</code> as well as <code>price of substitutes</code> into the equation. You may face a dimensionality problem due to the large number of parameters to be estimated. The effect <code>substitutable units</code> would be interpreted as the effect of the availability of substitutes on demand.</li>
<li>I would think about the status of these types. Is the same product with different attributes? Are these types substitutes? Is it a kind of aggregation? Regarding interpretation: you interpret one category with respect to another (or to a benchmark category in case of more than one category).</li>
</ol>

CC BY-SA 4.0
2020-08-21T07:32:28.487Z
1. My data unit of analysis is quarter - year and some of those variables are yearly observations. what's the right wording, for my knowledge. 3. Price in the equation average market price of the unit. The substitutable units is # available, and average price of substitutes.
kms
CC BY-SA 4.0
2020-08-21T07:35:50.537Z
I would call them control variables, given that you are interested in price elasticity
emeryville
CC BY-SA 4.0
2020-09-26T12:21:57.210Z
For #3, the own price of the good is avg. price and available substitutes units is just number of available units vs the price. The idea is that the number of available substitute units has an effect on quantity demanded.
kms
CC BY-SA 4.0
2020-08-21T07:24:54.200Z
2020-08-21T07:45:19.100Z
2020-08-21T07:45:19.100Z
emeryville
<p>I have a time series of units sold, and price. I'd like to calculate elasticity of demand wrt to price and a few other variables, some of them are fixed effects.</p>
<pre><code>Qp = b0 + b1 * log(Price) + b2 * Location + b3 * log(Income) + b4 * log(HouseHolds)
</code></pre>
<p>I am using log-log regression to calculate the elasticities, and the independent variable of interest is Price. Qp is # of units sold.</p>
<p>My questions are</p>
<ol>
<li><p>Can I use Median Income, and Households are fixed effects for the time period in log-log regression model.</p>
</li>
<li><p>Interpretation of Log - Log regression.
1% change in price changes the units sold by b1%(coefficient of price), Ceteris paribus, all else being equal.</p>
</li>
<li><p>Cross Elasticity.
What I add a term for # of available substitutable units? How would I interpret the term?</p>
<p><code>Qp = b0 + b1 * Price + b2 * Location + b3 * Income + b4 * HouseHolds + b5 * substitutable units</code></p>
</li>
<li><p>I also have additional categorical variable, i.e type of unit sold. <code>type 1</code> and <code>type 2</code>. Does it make sense to include that variable in the equation or fit a regression separately for each type? How would you interpret different coefficients of categorical variable?</p>
</li>
<li><p>I'd like to find the point where increasing the Price negatively affects units sold.</p>
</li>
</ol>

<elasticity><regression><fixed-effects>
Log log regression with fixed effects and cross elasticity of demand
kms
# Log log regression with fixed effects and cross elasticity of demand

(Asked by: username_0 on 2020-08-21)

I have a time series of units sold, and price. I'd like to calculate elasticity of demand wrt to price and a few other variables, some of them are fixed effects.
Qp = b0 + b1 * log(Price) + b2 * Location + b3 * log(Income) + b4 * log(HouseHolds)

I am using log-log regression to calculate the elasticities, and the independent variable of interest is Price. Qp is # of units sold.
My questions are

Can I use Median Income, and Households are fixed effects for the time period in log-log regression model.

Interpretation of Log - Log regression.
1% change in price changes the units sold by b1%(coefficient of price), Ceteris paribus, all else being equal.

Cross Elasticity.
What I add a term for # of available substitutable units? How would I interpret the term?
Qp = b0 + b1 * Price + b2 * Location + b3 * Income + b4 * HouseHolds + b5 * substitutable units

I also have additional categorical variable, i.e type of unit sold. type 1 and type 2. Does it make sense to include that variable in the equation or fit a regression separately for each type? How would you interpret different coefficients of categorical variable?

I'd like to find the point where increasing the Price negatively affects units sold.

**Tags:** elasticity, regression, fixed-effects

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## 1 answers

### Answer by username_1 on 2020-08-21. Score: 2

Note that you have an **identification problem** here because price is an endogenous variable. A way to deal with this problem would be to find an instrument (e.g. prices of the same good in other markets as in [Hausman (1996)](https://www.nber.org/chapters/c6068.pdf)).

Regarding your questions.

1. Yes (although fixed effects are probably not the right wording here).
2. Yes.
3. If you want to capture a cross elasticity effect you need to introduce the `own price` as well as `price of substitutes` into the equation. You may face a dimensionality problem due to the large number of parameters to be estimated. The effect `substitutable units` would be interpreted as the effect of the availability of substitutes on demand.
4. I would think about the status of these types. Is the same product with different attributes? Are these types substitutes? Is it a kind of aggregation? Regarding interpretation: you interpret one category with respect to another (or to a benchmark category in case of more than one category).

> **Comments:**
> **username_0**: 1. My data unit of analysis is quarter - year and some of those variables are yearly observations. what's the right wording, for my knowledge. 3. Price in the equation average market price of the unit. The substitutable units is # available, and average price of substitutes.  
> **username_1**: I would call them control variables, given that you are interested in price elasticity  
> **username_0**: For #3, the own price of the good is avg. price and available substitutes units is just number of available units vs the price. The idea is that the number of available substitute units has an effect on quantity demanded.  

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