<p>It depends on what you are trying to capture. Assuming the use of linear OLS regression, explaining the dummy using appreciation of leisure time as a regressor will yield a "gross" effect (actually, you'll obtain the correlation between the two in the sample), in the sense that the indirect effects of the explanatory variable on the explained one will not be "netted out". Controlling for "overall happiness" will certainly rise endogeneity issues that you'll have to also address. On the other hand, it hopefully will bring you closer to estimating a causal effect. 
As a side note, I'd suggest considering the use of more traditional demographic/economic variables instead of a computation such as the happiness index at stake. </p>

CC BY-SA 3.0
2016-03-29T04:25:07.607Z
2016-03-29T04:25:07.607Z
rsm
<p>I am using panel data from the <a href="https://www.lissdata.nl/lissdata/" rel="nofollow">LISS</a> to estimate the effect of whether a person practices sport or not on appreciation of leisure time (scale 0-10).</p>

<p>My partner insists on using a variable that indicates overall happiness (scale 0-5). I think this is a mistake because there is a causation problem between overall happiness and leisure time appreciation (do people who make the most out of their leisure time are happier or are happy people making the most out of their leisure time).</p>

<p>Am I crazy to think this is terrible variable to include in our analysis and we should simply overlook this variable all together. </p>

CC BY-SA 3.0
2016-03-28T00:01:07.493Z
What does LISS stand for?
Graeme Walsh
CC BY-SA 3.0
2016-03-28T03:19:56.040Z
https://www.lissdata.nl/lissdata/
Revoltic
CC BY-SA 3.0
2016-03-29T13:28:53.370Z
Please update the title to be more specific.
FooBar
<econometrics>
Including variable with causation problem for estimating from LISS
Revoltic
# Including variable with causation problem for estimating from LISS

(Asked by: username_0 on 2016-03-27)

I am using panel data from the [LISS](https://www.lissdata.nl/lissdata/) to estimate the effect of whether a person practices sport or not on appreciation of leisure time (scale 0-10).

My partner insists on using a variable that indicates overall happiness (scale 0-5). I think this is a mistake because there is a causation problem between overall happiness and leisure time appreciation (do people who make the most out of their leisure time are happier or are happy people making the most out of their leisure time).

Am I crazy to think this is terrible variable to include in our analysis and we should simply overlook this variable all together.

**Tags:** econometrics
> **Comments:**
> **username_1**: What does LISS stand for?  
> **username_0**: https://www.lissdata.nl/lissdata/  
> **username_2**: Please update the title to be more specific.  

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## 1 answers

### Answer by username_3 on 2016-03-29. Score: 0

It depends on what you are trying to capture. Assuming the use of linear OLS regression, explaining the dummy using appreciation of leisure time as a regressor will yield a "gross" effect (actually, you'll obtain the correlation between the two in the sample), in the sense that the indirect effects of the explanatory variable on the explained one will not be "netted out". Controlling for "overall happiness" will certainly rise endogeneity issues that you'll have to also address. On the other hand, it hopefully will bring you closer to estimating a causal effect.
As a side note, I'd suggest considering the use of more traditional demographic/economic variables instead of a computation such as the happiness index at stake.


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