<p><span class="math-container">$Performance_i = \beta_0 +\beta_1 Attend_i +\varepsilon_i$</span></p>
<p>It may be that healthier snacks do not affect attendance, but I would be very concerned making an assumption of the form <span class="math-container">$Cov(Attend_i, \varepsilon_i)=0$</span>. Students who are more likely to perform well are also probably more likely to attend. i.e., there could be an omitted variable, <span class="math-container">$Motivation_i$</span> such that <span class="math-container">$\varepsilon_i =\beta_2 Motivation_i +\eta_i$</span>.</p>
<p>Then <span class="math-container">$Motivation_i$</span> is probably correlated with both attendance and performance.</p>
<p>This is tricky. How are you measuring performance? Test scores? Or something else?</p>

CC BY-SA 4.0
2022-04-25T09:34:23.007Z
2022-04-25T09:34:23.007Z
Michael Gmeiner
<br/>
I'm looking for the effect of nutritional coffee breaks on MBA performance, and I found that the change to a healthier catering increased the performance of MBA students. Additionally, I want to see if **more exposure to nutritional meals** affects more or less these students' test scores. To do that, I want to use **attendance to measure the intensity of the treatment** (if you attended more, you were more exposed to the treatment). Still, given that the healthier snacks might affect attendance, I first obtain the effect of healthier on attendance, estimating a precise zero. Consequently, can I use attendance as a measure of intensity? or even if I find that healthier coffee breaks do not affect attendance, I should assume that it is endogenous. If the aforementioned answer is correct, can you explain to me why? <br/>
Thank you very much.

<microeconomics><econometrics><applied-econometrics><education-economics><endogeneity>
When can I assume that a variable is exogenous?
Alexis
# When can I assume that a variable is exogenous?

(Asked by: username_0 on 2022-04-22)

I'm looking for the effect of nutritional coffee breaks on MBA performance, and I found that the change to a healthier catering increased the performance of MBA students. Additionally, I want to see if \*\*more exposure to nutritional meals\*\* affects more or less these students' test scores. To do that, I want to use \*\*attendance to measure the intensity of the treatment\*\* (if you attended more, you were more exposed to the treatment). Still, given that the healthier snacks might affect attendance, I first obtain the effect of healthier on attendance, estimating a precise zero. Consequently, can I use attendance as a measure of intensity? or even if I find that healthier coffee breaks do not affect attendance, I should assume that it is endogenous. If the aforementioned answer is correct, can you explain to me why?   
Thank you very much.

**Tags:** microeconomics, econometrics, applied-econometrics, education-economics, endogeneity

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## 1 answers

### Answer by username_1 on 2022-04-25. Score: 1

$Performance\_i = \beta\_0 +\beta\_1 Attend\_i +\varepsilon\_i$

It may be that healthier snacks do not affect attendance, but I would be very concerned making an assumption of the form $Cov(Attend\_i, \varepsilon\_i)=0$. Students who are more likely to perform well are also probably more likely to attend. i.e., there could be an omitted variable, $Motivation\_i$ such that $\varepsilon\_i =\beta\_2 Motivation\_i +\eta\_i$.

Then $Motivation\_i$ is probably correlated with both attendance and performance.

This is tricky. How are you measuring performance? Test scores? Or something else?


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