Question: How define the order of variables in an interaction term?

[inkrement]

Is it possible to change the order of variables in an interaction term? Using the order argument of the etable command, it is possible to rearrange the variable names per see, but I cannot directly change the ordering within an interaction term. Consequently, I am not sure if this is a question (i.e., functionality already exists) or a feature request.

[lrberge]

Hi, what do you have in mind by "interaction"? It can be several things actually. Could you give an example in code of what you have in mind?

[inkrement]

Hi, thanks for the fast response! With interaction, I mean a formula such as "y ~ x:m". Whereby, xm is an interaction term. It seems like the order of xm (or mx) does not always follow the definition (sometimes I write xm, but the results list m*x; which of course does not affect the result, but the label). The possibility of ordering also the variables within interaction terms would be a nice feature!

[lrberge]

Oh, I see!

Actually my algorithm only reorders when there would ba a consistency problem (i.e. considering two variables with different names as different when they are the same). Here's an example:

base = iris
names(base) = c("y", "x1", "x2", "x3", "species")

a = feols(y ~ x1:x2, base)
b = feols(y ~ x2:x1, base)

# No reordering
etable(a)
#>                                  a
#> Dependent Var.:                  y
#>                                   
#> (Intercept)      4.253*** (0.0694)
#> x1 x x2         0.1425*** (0.0056)
#> _______________ __________________
#> S.E. type                 Standard
#> Observations                   150
#> R2                         0.81221
#> Adj. R2                    0.81094

# No reordering
etable(b)
#>                                  b
#> Dependent Var.:                  y
#>                                   
#> (Intercept)      4.253*** (0.0694)
#> x2 x x1         0.1425*** (0.0056)
#> _______________ __________________
#> S.E. type                 Standard
#> Observations                   150
#> R2                         0.81221
#> Adj. R2                    0.81094

# REORDERING
etable(a, b)
#>                                  a                  b
#> Dependent Var.:                  y                  y
#>                                                      
#> (Intercept)      4.253*** (0.0694)  4.253*** (0.0694)
#> x1 x x2         0.1425*** (0.0056) 0.1425*** (0.0056)
#> _______________ __________________ __________________
#> S.E. type                 Standard           Standard
#> Observations                   150                150
#> R2                         0.81221            0.81221
#> Adj. R2                    0.81094            0.81094

d = feols(y ~ x1:species, base)
e = feols(y ~ species:x1, base)

# No reordering
etable(d)
#>                                         d
#> Dependent Var.:                         y
#>                                          
#> (Intercept)             3.358*** (0.3300)
#> x1 x speciessetosa     0.4833*** (0.0968)
#> x1 x speciesversicolor 0.9299*** (0.1198)
#> x1 x speciesvirginica   1.084*** (0.1117)
#> ______________________ __________________
#> S.E. type                        Standard
#> Observations                          150
#> R2                                0.72257
#> Adj. R2                           0.71687

# No reordering
etable(e)
#>                                         e
#> Dependent Var.:                         y
#>                                          
#> (Intercept)             3.358*** (0.3300)
#> speciessetosa x x1     0.4833*** (0.0968)
#> speciesversicolor x x1 0.9299*** (0.1198)
#> speciesvirginica x x1   1.084*** (0.1117)
#> ______________________ __________________
#> S.E. type                        Standard
#> Observations                          150
#> R2                                0.72257
#> Adj. R2                           0.71687

# REORDERING
etable(d, e)
#>                                         d                  e
#> Dependent Var.:                         y                  y
#>                                                             
#> (Intercept)             3.358*** (0.3300)  3.358*** (0.3300)
#> speciessetosa x x1     0.4833*** (0.0968) 0.4833*** (0.0968)
#> speciesversicolor x x1 0.9299*** (0.1198) 0.9299*** (0.1198)
#> speciesvirginica x x1   1.084*** (0.1117)  1.084*** (0.1117)
#> ______________________ __________________ __________________
#> S.E. type                        Standard           Standard
#> Observations                          150                150
#> R2                                0.72257            0.72257
#> Adj. R2                           0.71687            0.71687

But I think that what you are referring to is due to R's parser which sometimes (and rather inconsistently) reorders the interactions.

In any case, I see your point, I'll see what I can do.

[lrberge]

Hi, I've added the argument interaction.order to deal with this problem:

base = iris
names(base) = c("y", "x1", "x2", "x3", "species")
est = feols(y ~ i(species, x1) + i(species, x2), base)

etable(est, interaction.order = "species")
#>                                          est
#> Dependent Var.:                            y
#>                                             
#> (Intercept)                1.725*** (0.2781)
#> species = setosa x x1     0.7584*** (0.0974)
#> species = versicolor x x1   0.3133* (0.1579)
#> species = virginica x x1     0.1028 (0.1352)
#> species = setosa x x2       0.4627* (0.2212)
#> species = versicolor x x2 0.7838*** (0.1039)
#> species = virginica x x2  0.8222*** (0.0749)
#> _________________________ __________________
#> S.E. type                                IID
#> Observations                             150
#> R2                                   0.86873
#> Adj. R2                              0.86322

etable(est, interaction.order = c("x2", "species"))
#>                                          est
#> Dependent Var.:                            y
#>                                             
#> (Intercept)                1.725*** (0.2781)
#> species = setosa x x1     0.7584*** (0.0974)
#> species = versicolor x x1   0.3133* (0.1579)
#> species = virginica x x1     0.1028 (0.1352)
#> x2 x species = setosa       0.4627* (0.2212)
#> x2 x species = versicolor 0.7838*** (0.1039)
#> x2 x species = virginica  0.8222*** (0.0749)
#> _________________________ __________________
#> S.E. type                                IID
#> Observations                             150
#> R2                                   0.86873
#> Adj. R2                              0.86322