Timeline for How to graph interaction effects for panel data
Current License: CC BY-SA 3.0
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| May 21, 2014 at 17:59 | comment | added | bmciv | If all the covariates are categorical (i.e the value has no meaning), then your estimates would be differences in sample means for each group (removing time and fe), and you could probably just plot these in a bar graph with one bar for each group. From the last line that you wrote, it looks like some of the covariates may be continuous. You could fix x2 (probably at its mean or some other choice that makes since) and make a plot varying x1 for something 2d. You could let both of them vary and make a 3d plot. If you use R, check out the lattice package (and wireframe method) for 3d plots. | |
| May 21, 2014 at 16:54 | comment | added | SJDS | Hi, thanks for your comment. Assuming your D stands for dummy in the formula you are almost right. I understand the need to pick some artificial values for the time- and individual fixed effects which is only going to affect the intercept as you said. However, what is the best way forward when you not only have interactions between a dummy and an explanatory variable but interactions with multiple (discrete) explanatory variables. Something like y = B0 + B1x1 + B2x2 + ... + B10x1^2 + B11x1*x2 + B12x1^2*x2 | |
| May 20, 2014 at 21:30 | history | answered | bmciv | CC BY-SA 3.0 |