<p>In your model, the intercept is the average mortality rate for the units (countries?) with CPI=0 and HDI=0, i.e., E(<code>death_rate</code> | <code>CPI</code>=0, <code>HDI</code>=0). So <code>_cons</code> being significant means that the average mortality rate for the units with CPI=0 (most corrupt) and HDI=0 (least developed) is significantly different from zero. This is obvious because people die everywhere, and I would be surprised if it was insignificant unless the sample size is very small.</p>

CC BY-SA 4.0
2022-11-12T10:48:20.977Z
2022-11-12T10:48:20.977Z
chan1142
<p>Your model, in regard to the question whether your regression is lin-lin, log-lin or log-log, is a lin-lin one as you wrote it in its way (without computing the logarithm of any variable). Even if death rates are percentages so numbers divided by 100, coefficients say you that the death rate varies by <span class="math-container">$\beta_{specific-variable}$</span> in average.</p>

CC BY-SA 4.0
2022-11-13T20:48:22.423Z
2022-11-13T20:48:22.423Z
Pepus
<p>I am running a regression the following way on stata: <code>reg death_rate CPI HDI</code></p>
<p>Where death_rate is the mortality rate of COVID-19 in 2021 (measured as a %), HDI is the Human Development Index (0 - 1, 1 is most developed) and CPI is the Corruption Perception Index (0 - 100, 0 most corrupt, 100 least corrupt).</p>
<p><a href="https://i.sstatic.net/XCFIf.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/XCFIf.png" alt="Regression" /></a></p>
<p>I am trying to understand what does it mean that the constant (_cons) is statistically significant in my model but can't fully grasp the concept and what the coefficient means in this case. Moreover, I am not sure if I have a linear or log-lin or log-log model as the mortality rate is a percentage.</p>
<p>If you have any observation, feedback or anything interesting that you might think about this model please let me know so that I can take it into consideration !
Any help / tips / resources are appreciated.</p>

<econometrics><regression><applied-econometrics><stata>
Meaning of a statistically significant constant in a regression and more
Coco Garazzo
# Meaning of a statistically significant constant in a regression and more

(Asked by: username_0 on 2022-11-11)

I am running a regression the following way on stata: `reg death_rate CPI HDI`

Where death\_rate is the mortality rate of COVID-19 in 2021 (measured as a %), HDI is the Human Development Index (0 - 1, 1 is most developed) and CPI is the Corruption Perception Index (0 - 100, 0 most corrupt, 100 least corrupt).

[![Regression](https://i.sstatic.net/XCFIf.png)](https://i.sstatic.net/XCFIf.png)

I am trying to understand what does it mean that the constant (\_cons) is statistically significant in my model but can't fully grasp the concept and what the coefficient means in this case. Moreover, I am not sure if I have a linear or log-lin or log-log model as the mortality rate is a percentage.

If you have any observation, feedback or anything interesting that you might think about this model please let me know so that I can take it into consideration !
Any help / tips / resources are appreciated.

**Tags:** econometrics, regression, applied-econometrics, stata


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## 2 answers

### Answer by username_1 on 2022-11-12. Score: 1

In your model, the intercept is the average mortality rate for the units (countries?) with CPI=0 and HDI=0, i.e., E(`death_rate` | `CPI`=0, `HDI`=0). So `_cons` being significant means that the average mortality rate for the units with CPI=0 (most corrupt) and HDI=0 (least developed) is significantly different from zero. This is obvious because people die everywhere, and I would be surprised if it was insignificant unless the sample size is very small.


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### Answer by username_2 on 2022-11-13. Score: 0

Your model, in regard to the question whether your regression is lin-lin, log-lin or log-log, is a lin-lin one as you wrote it in its way (without computing the logarithm of any variable). Even if death rates are percentages so numbers divided by 100, coefficients say you that the death rate varies by $\beta\_{specific-variable}$ in average.


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