I am writing my BA-Thesis in Economics and hope somebody can help me out.
First let me explain the variables:
- tprofits = profit of participants
- class = 1 if participant was in the class treatment (not of interest here, control variable)
- prior_exp = 1 if participant had prior business experience
- mentorL_ba = 1 if mentor is in the lowest 25% of mentor experience
- mentorM_ba = 1 if mentor is in the 25% - 75% of mentor experience
- mentorH_ba = 1 if mentor is in the 75% - 100% of mentor experience
- i.wave, tprofits_b, $controls = control variabels
Code:
reg tprofits class i.prior_exp i.mentorL_ba#i.prior_exp i.mentorM_ba#i.prior_exp i.mentorH_ba#i.prior_exp i.wave tprofits_b $controls2, cluster(id)
Linear regression Number of obs = 2,276
F(21, 367) = .
Prob > F = .
R-squared = 0.1283
Root MSE = 1706.2
(Std. Err. adjusted for 368 clusters in id)
--------------------------------------------------------------------------------------
| Robust
tprofits | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
class | 93.1618 141.8026 0.66 0.512 -185.6859 372.0094
1.prior_exp | 410.4867 124.8495 3.29 0.001 164.9765 655.9969
|
mentorL_ba#prior_exp |
1 0 | 389.6264 263.7742 1.48 0.141 -129.0721 908.3249
1 1 | 594.4702 224.8253 2.64 0.009 152.3627 1036.578
|
mentorM_ba#prior_exp |
1 0 | 468.3452 257.7104 1.82 0.070 -38.42922 975.1196
1 1 | 438.0457 202.1707 2.17 0.031 40.48736 835.604
|
mentorH_ba#prior_exp |
1 0 | 1151.504 516.897 2.23 0.027 135.0521 2167.955
1 1 | 206.6049 254.6565 0.81 0.418 -294.1641 707.3739I want to know which mentor-mentee experience-combination has the largest impact on the profit. I’m not sure what regression to use here as I'm still very new to STATA.
Alternatively I have created a single variable for mentor experience (mentor_exp=1 if low experience, mentor_exp=2 if medium experience, mentor_exp=3 if high experience) and run another regression.
Code:
reg tprofits class i.mentor_exp i.mentor_exp#i.prior_exp i.wave tprofits_b $controls2, cluster(id)
Linear regression Number of obs = 618
F(16, 123) = .
Prob > F = .
R-squared = 0.1205
Root MSE = 2036.6
(Std. Err. adjusted for 124 clusters in id)
--------------------------------------------------------------------------------------
| Robust
tprofits | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
class | 0 (omitted)
|
mentor_exp |
2 | 16.18308 347.0116 0.05 0.963 -670.7051 703.0713
3 | 358.0511 484.6994 0.74 0.461 -601.3816 1317.484
|
mentor_exp#prior_exp |
1 1 | 572.767 332.1417 1.72 0.087 -84.68714 1230.221
2 1 | 392.4994 294.4023 1.33 0.185 -190.2519 975.2508
3 1 | -173.9383 454.761 -0.38 0.703 -1074.11 726.2332And another were I changed the base category to see the effect of no prior experience.
Code:
reg tprofits class i.mentor_exp i.mentor_exp#b1.prior_exp i.wave tprofits_b $controls2, cluster(id)
Linear regression Number of obs = 618
F(16, 123) = .
Prob > F = .
R-squared = 0.1205
Root MSE = 2036.6
(Std. Err. adjusted for 124 clusters in id)
--------------------------------------------------------------------------------------
| Robust
tprofits | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
class | 0 (omitted)
|
mentor_exp |
2 | -164.0845 258.1515 -0.64 0.526 -675.0797 346.9106
3 | -388.6542 285.2731 -1.36 0.176 -953.3348 176.0263
|
mentor_exp#prior_exp |
1 0 | -572.767 332.1417 -1.72 0.087 -1230.221 84.68714
2 0 | -392.4994 294.4023 -1.33 0.185 -975.2508 190.2519
3 0 | 173.9383 454.761 0.38 0.703 -726.2332 1074.11I hope somebody can help me find the regression of interest here.
Thank you in advance for your help.
0 Response to Regression with Interaction Terms
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