<p>If you are running an OLS regression, I would recommend to take the more volatile one. Higher volatility in the explanatory variable (interest here) reduces the standard errors of the estimator, making it more efficient and more likely to find a significant effect.</p>

CC BY-SA 3.0
2016-09-29T10:54:23.617Z
2016-09-29T10:54:23.617Z
BB King
<p>We are asked to model the demand for money as a function of interest rates and we are given two periods of data: one with interest rates were relatively stable and the other one were volatile. We can only choose one, but I don't know which one I should choose. What should I be taken into consideration? I am thinking that maybe I should choose the relatively stable one, because the regression line would be more accurate? </p>

<macroeconomics><econometrics>
Model the demand
J.doe
# Model the demand

(Asked by: username_0 on 2016-09-27)

We are asked to model the demand for money as a function of interest rates and we are given two periods of data: one with interest rates were relatively stable and the other one were volatile. We can only choose one, but I don't know which one I should choose. What should I be taken into consideration? I am thinking that maybe I should choose the relatively stable one, because the regression line would be more accurate?

**Tags:** macroeconomics, econometrics


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## 1 answers

### Answer by username_1 on 2016-09-29. Score: 1 | Accepted answer

If you are running an OLS regression, I would recommend to take the more volatile one. Higher volatility in the explanatory variable (interest here) reduces the standard errors of the estimator, making it more efficient and more likely to find a significant effect.


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