# How important is a statistically significant intercept?

I've created the following model:

log(consumption) = a + b*log(GDP) + c*log(GDP(-1)) + d*log(consumption(-1))


The slope coefficients are all statistically significant, however the intercept has a p-value of 0.1085. How important is this and how will it affect my model?

• The p-value hasn't affected your model at all. Could you clarify the sense in which you intend us to understand "important"?
– whuber
Mar 16, 2019 at 16:20
• Sorry, should have been clearer. I mean to ask, should I reject this model on the grounds that the intercept is not significantly significant? Mar 16, 2019 at 16:29
• I saw some researches were they discard the intercept term if it's not significant Mar 16, 2019 at 16:29
• How you deal with p-values depends on the purpose of your analysis, so it's essential that you include that information in your post. Since the effect of the constant term can be profound--it looks like you have a time series model in terms of logarithms, so at each time step the exponential of the intercept will multiply the consumption estimate, causing it to have an exponentially greater effect over time--so it would be foolish, without much more consideration, to assume that what "some researches" might have done would be appropriate for you.
– whuber
Mar 16, 2019 at 16:34