# Interpreting OLS regression with continuous interaction?

I'm a beginner when it comes to statistics and I have a question about how to interpret the results of this OLS model and specifically the interaction of two continuous variables.

The following regression is from an exercise I'm working on. The dependent variable is (log)wage with a plethora of explanatory variables.

Thanks to the links provided by @mkt and @EdM, most of my questions got cleared up! I'm still a little bit uncertain about the interpretation of the continuous interaction of Experience_Education.

From the link provided by @EdM, I understand that the effect of a one-unit increase in X1 when X2 is held constant is β1+β3X2. The effect when X2 is increased by one unit while holding X1 constant is β2+β3X1.

So if we simplify the model to

Wage = B0 + B1Education + B2Experience + B3Experience_Education.

Then the effect on Education, when holding Experience constant, should be B1 + B3Experience?

However, wouldn't Experience in this case, since it is held constant, be 0. So the effect on Education is simply B1?

0.0672779 + 0.0004121*(0) -> since Experience is 0?

But if Experience would be 5 for example then the effect on Education would be:

0.0672779 + 0.0004121*(5)?

• This might help: stats.stackexchange.com/q/388651/121522
– mkt
Jan 28, 2019 at 17:44
• Also, look at this page. Please consider revising this question to focus on issues that are still unresolved after you try to apply the information from the answers to these related questions.
– EdM
Jan 28, 2019 at 18:16
• @mkt thank you! that cleared up most of my question of how to interpret an interaction with dummy and continuous variable. I'm still a bit unsure about the interaction of two continuous variables. Jan 28, 2019 at 19:24
• @EdM thank you as well! That helped me understand an interaction of two continuous variables better. I'm still a bit uncertain about the interpretation though so I have revised the question. Jan 28, 2019 at 19:25