l*****n
发帖数: 76 | 1 regression 是这样的
R2=a+b*R1+c*V*R1+error
如何show the economic importance of the coefficient c on the interaction
term?
mean of V=0; mean of R1 =0
可以比较the difference in the values of R2 between the case where V is one
standard deviation above its mean and R1 is one standard deviation above its
mean and the benchmark case where V=0 and R1 is one standard deviation
above its mean吗 |
t*****i
发帖数: 68 | 2 No, because in this way the outcome you get includes the direct effect of R1
as well as that of the interaction term. You have to use a diffrence-in-dif
frence approach to show the effect solely from the interaction term.
its
【在 l*****n 的大作中提到】
: regression 是这样的
: R2=a+b*R1+c*V*R1+error
: 如何show the economic importance of the coefficient c on the interaction
: term?
: mean of V=0; mean of R1 =0
: 可以比较the difference in the values of R2 between the case where V is one
: standard deviation above its mean and R1 is one standard deviation above its
: mean and the benchmark case where V=0 and R1 is one standard deviation
: above its mean吗
|
l*****n
发帖数: 76 | 3 why? is the direct effect of R1 removed already by taking the difference
between two cases?
suppose one standard deviation of R1=1
one standard deviation of V=1
case1 R2=a+b*1+c*1*1
benchmark case R2=a+b*1+c*1*0
the difference between case 1 and benchmark case will be Delta_R2=c*1*1
This is the effect of interaction term, right?
R1
dif
【在 t*****i 的大作中提到】
: No, because in this way the outcome you get includes the direct effect of R1
: as well as that of the interaction term. You have to use a diffrence-in-dif
: frence approach to show the effect solely from the interaction term.
:
: its
|
t*****i
发帖数: 68 | 4 My bad. I misunderstood you. Then it's fine to show the effect of the intera
ction this way. However, people ususally also incluce V separately in the re
gression unless there are theoretical reasons for not doing so. you may want
to justify your specification more carefully.
【在 l*****n 的大作中提到】
: why? is the direct effect of R1 removed already by taking the difference
: between two cases?
: suppose one standard deviation of R1=1
: one standard deviation of V=1
: case1 R2=a+b*1+c*1*1
: benchmark case R2=a+b*1+c*1*0
: the difference between case 1 and benchmark case will be Delta_R2=c*1*1
: This is the effect of interaction term, right?
:
: R1
|
j**********n
发帖数: 390 | 5 It is more commonly seen as:
R2 = a + b*R1 + c*V*R1 + d*V + error |
