Hello! I have a regression model that requires two interaction terms. I am however a bit unsure how to correctly interpret the coefficients? My variables are as follow
1) INV_W --> change in investment spending
2) CR_POM (dummy variable) --> measuring if firms are close to a credit rating change or not
3) Tech_Industry ( dummy variable) --> first interaction term to distinguishing between firms in technology industry and the ones not
4) INV_G (dummy variable) --> second interaction term to distinguish between investment grade firms and the ones below
5) Size, Profitability are control variables
My regression and output are as follows:
I am currently unsure if for instance coefficient for CR_POM would indicate the firms that are close to a credit rating change, but excluding firms in tech industry as well as the ones in investment grade? Additionally, I if I would like to arrive at a coefficient to see if the effect on net investments is stronger for firms that are close to a credit rating change within investment grade in contrast to rest of the firms. Also if this effect is more prominent in Tech industries. Overall, I am wondering how adding up the coefficients can be interpreted, for instance adding up CR_POM + Int_CR_POM_Tech or alterantivly CR_POM + Int_CR_POM + Int_Tech_INV_G. Thank you in advance!!
1) INV_W --> change in investment spending
2) CR_POM (dummy variable) --> measuring if firms are close to a credit rating change or not
3) Tech_Industry ( dummy variable) --> first interaction term to distinguishing between firms in technology industry and the ones not
4) INV_G (dummy variable) --> second interaction term to distinguish between investment grade firms and the ones below
5) Size, Profitability are control variables
My regression and output are as follows:
Code:
regress INV_W CR_POM Tech_Industry INV_G Int_CR_POM_Tech Int_CR_POM_INV_G Int_Tech_INV_G Size Profitability, vce(hc3) Linear regression Number of obs = 5715 F( 8, 5706) = 6.80 Prob > F = 0.0000 R-squared = 0.0089 Root MSE = 1.4518 ---------------------------------------------------------------------------------- | Robust HC3 INV_W | Coef. Std. Err. t P>|t| [95% Conf. Interval] -----------------+---------------------------------------------------------------- CR_POM | .0820362 .0840089 0.98 0.329 -.0826532 .2467256 Tech_Industry | -.0754513 .0922812 -0.82 0.414 -.2563574 .1054549 INV_G | .0118881 .0831091 0.14 0.886 -.1510372 .1748135 Int_CR_POM_Tech | .0329208 .0867673 0.38 0.704 -.1371761 .2030178 Int_CR_POM_INV_G | -.0782386 .0891753 -0.88 0.380 -.253056 .0965788 Int_Tech_INV_G | .1185679 .0921215 1.29 0.198 -.0620253 .2991611 Size | -.1483267 .0293412 -5.06 0.000 -.2058467 -.0908068 Profitability | 1.027661 .2402928 4.28 0.000 .5565956 1.498726 _cons | 1.619802 .2798224 5.79 0.000 1.071244 2.16836 ----------------------------------------------------------------------------------
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