<p>In panel regressions you have multiple dimensions and that is why also you have 3 different <span class="math-container">$R^2$</span>. The within <span class="math-container">$R^2$</span> tells you how much variation within your panel variables is on average explained by your model. The between <span class="math-container">$R^2$</span>, tells you how much variation between your panel variables is explained by the model, and overall <span class="math-container">$R^2$</span> gives you the combination of both and tells you how much variation in the whole panel data your model explains.</p>

<p>According to the stata manual you should get adjusted <span class="math-container">$R^2$</span> for fixed effects by <code>ereturn list</code> it will be the r2_a scalar. However, there are no simple adjustments for within and between <span class="math-container">$R^2$</span>, those are most often reported unadjusted.</p>

CC BY-SA 4.0
2020-02-28T07:33:16.207Z
2020-02-28T07:33:16.207Z
1muflon1
<p>The ANOVA results indicate 53.11% of dependent  variable is explained - which you should check whether it is significant (or insignificant). Moreover, you may ascertain the chi-square with the help of between and within sum of squares. This could help you to test the significance level at which the effect on dependent variable is significant. </p>

CC BY-SA 4.0
2020-02-28T17:54:53.387Z
2020-02-28T17:54:53.387Z
Subhash C. Davar
<p>I runned a fixed effect regression in Stata (xtreg, fe) for panel data. I obtained below R-sq. results. How should I interpret them? Which one is my main interest(within,below or overall)? How can I derive the exact Adjusted R-sq. by using these 3 values?</p>

<p>R-sq:<br>
     within  = 0.8226<br>
     between = 0.4727<br>
     overall = 0.5311  </p>

<p>Thanks a lot!</p>

CC BY-SA 4.0
2020-02-28T08:19:37.873Z
In general, you should care most about the within R^2.
E. Sommer
<macroeconomics><econometrics><paneldata><stata>
How to interpret fixed effect regression R-sq. results for panel data?
Ozlem Akekmekci
# How to interpret fixed effect regression R-sq. results for panel data?

(Asked by: username_0 on 2020-02-27)

I runned a fixed effect regression in Stata (xtreg, fe) for panel data. I obtained below R-sq. results. How should I interpret them? Which one is my main interest(within,below or overall)? How can I derive the exact Adjusted R-sq. by using these 3 values?

R-sq:  
within = 0.8226  
between = 0.4727  
overall = 0.5311

Thanks a lot!

**Tags:** macroeconomics, econometrics, paneldata, stata

> **Comments:**
> **username_1**: In general, you should care most about the within R^2.  

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## 2 answers

### Answer by username_2 on 2020-02-28. Score: 2

In panel regressions you have multiple dimensions and that is why also you have 3 different $R^2$. The within $R^2$ tells you how much variation within your panel variables is on average explained by your model. The between $R^2$, tells you how much variation between your panel variables is explained by the model, and overall $R^2$ gives you the combination of both and tells you how much variation in the whole panel data your model explains.

According to the stata manual you should get adjusted $R^2$ for fixed effects by `ereturn list` it will be the r2\_a scalar. However, there are no simple adjustments for within and between $R^2$, those are most often reported unadjusted.


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### Answer by username_3 on 2020-02-28. Score: 0

The ANOVA results indicate 53.11% of dependent variable is explained - which you should check whether it is significant (or insignificant). Moreover, you may ascertain the chi-square with the help of between and within sum of squares. This could help you to test the significance level at which the effect on dependent variable is significant.


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