Dear Statalist,
I have the following issue:
I want to investigate the moderation effect of absorptive capacity in form of research and development expenses on the relationship between innovativeness(number_patents) and CVC actvities(cvc1). To test an inverted U-shape, I also integrated the squared value cvc2.
The results are the following:
How can I interpret the interaction terms? Which value indicates if it is a positive or negative moderation effect? Until now, I used the squared interaction term (c.cvc1#c.cvc1#c.ResearchandDevelopmentExpense) as an indicator. As the regression coefficient is positive, I assumed a positive moderation. Is that the right approach?
Thanks in advance!
Kind regards,
Henrik
I have the following issue:
I want to investigate the moderation effect of absorptive capacity in form of research and development expenses on the relationship between innovativeness(number_patents) and CVC actvities(cvc1). To test an inverted U-shape, I also integrated the squared value cvc2.
The results are the following:
Code:
xtreg number_patents c.cvc1##c.cvc1##c.ResearchandDevelopmentExpense rdi CurrentAssetsTotal log_industry_dynam
> ism StandardIndustryClassification q_tobin i.fyear, re cluster(gvkey)
Random-effects GLS regression Number of obs = 475
Group variable: gvkey Number of groups = 84
R-squared: Obs per group:
Within = 0.2712 min = 1
Between = 0.0562 avg = 5.7
Overall = 0.1817 max = 14
Wald chi2(23) = 181.65
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
(Std. err. adjusted for 84 clusters in gvkey)
---------------------------------------------------------------------------------------------------------------
| Robust
number_patents | Coefficient std. err. z P>|z| [95% conf. interval]
----------------------------------------------+----------------------------------------------------------------
cvc1 | 292.5542 106.482 2.75 0.006 83.85337 501.2551
|
c.cvc1#c.cvc1 | -21.40677 7.323167 -2.92 0.003 -35.75992 -7.053631
|
ResearchandDevelopmentExpense | .0530701 .0231165 2.30 0.022 .0077626 .0983776
|
c.cvc1#c.ResearchandDevelopmentExpense | -.0260776 .0102224 -2.55 0.011 -.046113 -.0060421
|
c.cvc1#c.cvc1#c.ResearchandDevelopmentExpense | .0018291 .0009255 1.98 0.048 .0000152 .003643
|
rdi | -153.8569 299.8545 -0.51 0.608 -741.561 433.8471
CurrentAssetsTotal | -.0025668 .005117 -0.50 0.616 -.0125959 .0074624
log_industry_dynamism | -25.63305 14.76077 -1.74 0.082 -54.56362 3.297527
StandardIndustryClassification | .0711053 .0726104 0.98 0.327 -.0712085 .2134191
q_tobin | 27.10256 28.97523 0.94 0.350 -29.68784 83.89297
|
fyear |
2007 | -21.67683 21.65702 -1.00 0.317 -64.1238 20.77015
2008 | 29.23846 114.2926 0.26 0.798 -194.771 253.2479
2009 | -62.42921 52.84687 -1.18 0.237 -166.0072 41.14876
2010 | -35.8264 52.52186 -0.68 0.495 -138.7674 67.11455
2011 | 61.59043 46.75624 1.32 0.188 -30.05012 153.231
2012 | 121.7003 83.94128 1.45 0.147 -42.82156 286.2222
2013 | 130.6375 87.6358 1.49 0.136 -41.12555 302.4005
2014 | 11.53912 68.65388 0.17 0.867 -123.02 146.0983
2015 | 47.76205 79.24387 0.60 0.547 -107.5531 203.0772
2016 | -57.21649 79.45166 -0.72 0.471 -212.9389 98.50591
2017 | -324.9182 85.68877 -3.79 0.000 -492.8651 -156.9713
2018 | -675.2418 197.5365 -3.42 0.001 -1062.406 -288.0773
2019 | -1053.773 234.9042 -4.49 0.000 -1514.177 -593.3691
|
_cons | 66.27524 319.9227 0.21 0.836 -560.7618 693.3123
----------------------------------------------+----------------------------------------------------------------
sigma_u | 574.47281
sigma_e | 403.78588
rho | .66932552 (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------------------------
Thanks in advance!
Kind regards,
Henrik
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