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# st: interpretation for negative and positive slope combination of interaction term

 From Nahla Betelmal To statalist@hsphsun2.harvard.edu Subject st: interpretation for negative and positive slope combination of interaction term Date Thu, 9 May 2013 14:20:55 +0100

```Dear Statalist,

As you can see below, I have a interaction term between OC (dummy =1
for overconfidence) and MV (continuous variable for market value). The
interaction term is positive and significant. I want to calculate the
slope against MB for overconfident managers which should be the
coefficient of MV plus the coefficient of OC*MV.
I am confused how to get this figure because MV is negative and OC*MV
is positive. So, Should it be -0.0566241 + 0.0596146= 0.003? if this
is true how can I interpret how many times the effect of MV is larger
for overconfident managers??  0.003/0.0566.

Linear regression                                      Number of obs =      49
F( 10,    38) =    3.23
Prob > F      =  0.0043
R-squared     =  0.4385
Root MSE      =  .08529

------------------------------------------------------------------------------
|               Robust
earnings managment|      Coef.   Std. Err.      t    P>|t|     [95%
Conf. Interval]
-------------+----------------------------------------------------------------
var1 |   .0081153   .0058432     1.39   0.173    -.0037137    .0199443
MV |  -.0566241   .0353602    -1.60   0.118     -.128207    .0149588
var3|   .1992782    .093338     2.14   0.039     .0103252    .3882312
var4 |  -.0040891   .0109331    -0.37   0.710    -.0262219    .0180437
var5 |   .0817256   .1169071     0.70   0.489    -.1549405    .3183917
var6 |   .0291373    .026944     1.08   0.286    -.0254079    .0836825
var7 |  -.0646094   .0320074    -2.02   0.051     -.129405    .0001863
var8 |  -.0867868   .0311875    -2.78   0.008    -.1499227   -.0236509
OC|  -.1040174   .0556577    -1.87   0.069    -.2166906    .0086558
OC*MV |   .0596146   .0324333     1.84   0.074    -.0060433    .1252724
_cons |   .1643745   .0994735     1.65   0.107    -.0369991     .365748

many Thanks

Nahla Betelmal
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```