- Extent of Foreign sales (also called Foreign Market Penetration) - Ln_GSD (MODEL 1)
- Extent of Foreign production (Foreign Production) - Ln_GSD_Asset (MODEL 2)
- Could you please guide me as to which test I should use? I was thinking of using the likelihood ratio test, however, that works only for nested models.
- Since my 2 models are not nested models, should I use nnest instead (https://stats.oarc.ucla.edu/stata/co...nested-models/) ?
- Another option is to use estat ic but I believe that it works for log likelihood models only.
MODEL 1
Code:
xtreg Ln_EBIT_ROA Ln_Revenue Ln_LTD_to_Sales Ln_Intangible_Assets CoAge wGDPpc wCPI wDCF wExpgr w
> GDPgr wCons Ln_PS_RD c.l1.Ln_GSD##c.l1.Ln_GSD##ib2.crisis if CoAge>=0 & NATION=="UNITED STATES" &
> NATIONCODE==840 & FSTS>=10 & FSTS <=100 & GENERALINDUSTRYCLASSIFICATION ==1 & Year_<2020 & Year_<
> YearInactive & Discr_GS_Rev!=1, fe cluster(n_WSID)
Fixed-effects (within) regression Number of obs = 1,080
Group variable: n_WSID Number of groups = 215
R-sq: Obs per group:
within = 0.1280 min = 1
between = 0.0043 avg = 5.0
overall = 0.0123 max = 19
F(17,214) = .
corr(u_i, Xb) = -0.7239 Prob > F = .
(Std. Err. adjusted for 215 clusters in n_WSID)
--------------------------------------------------------------------------------------------
| Robust
Ln_EBIT_ROA | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
Ln_Revenue | .5231021 .1499161 3.49 0.001 .2276008 .8186035
Ln_LTD_to_Sales | -.125481 .0419333 -2.99 0.003 -.2081362 -.0428258
Ln_Intangible_Assets | -.1103335 .0615829 -1.79 0.075 -.2317202 .0110532
CoAge | -.0029363 .0166989 -0.18 0.861 -.0358517 .0299791
wGDPpc | .0000298 .0000218 1.37 0.172 -.0000131 .0000727
wCPI | .0060675 .0254869 0.24 0.812 -.04417 .056305
wDCF | 1.36e-13 1.27e-13 1.07 0.285 -1.14e-13 3.85e-13
wExpgr | .0126791 .0125128 1.01 0.312 -.0119851 .0373433
wGDPgr | .0115004 .0300052 0.38 0.702 -.0476431 .070644
wCons | -2.27e-14 4.36e-14 -0.52 0.603 -1.09e-13 6.32e-14
Ln_PS_RD | -.04777 .0474308 -1.01 0.315 -.1412614 .0457213
|
Ln_GSD |
L1. | -.49074 .2583853 -1.90 0.059 -1.000046 .0185662
|
cL.Ln_GSD#cL.Ln_GSD | .177507 .1103887 1.61 0.109 -.0400813 .3950953
|
crisis |
1 | .0000289 .1170896 0.00 1.000 -.2307677 .2308255
3 | -.244763 .1386875 -1.76 0.079 -.5181314 .0286055
|
crisis#cL.Ln_GSD |
1 | -.0697625 .1898751 -0.37 0.714 -.4440274 .3045024
3 | -.1822128 .2083067 -0.87 0.383 -.5928084 .2283829
|
crisis#cL.Ln_GSD#cL.Ln_GSD |
1 | -.2631727 .1049846 -2.51 0.013 -.4701091 -.0562364
3 | -.2041293 .0970556 -2.10 0.037 -.3954366 -.0128219
|
_cons | -13.0135 2.823174 -4.61 0.000 -18.57829 -7.448709
---------------------------+----------------------------------------------------------------
sigma_u | 1.1013267
sigma_e | .59130596
rho | .77623771 (fraction of variance due to u_i)
--------------------------------------------------------------------------------------------Code:
. xtreg Ln_EBIT_ROA Ln_Revenue Ln_LTD_to_Sales Ln_Intangible_Assets CoAge wGDPpc wCPI wDCF wExpgr w
> GDPgr wCons Ln_PS_RD c.l1.Ln_GSD_Asset##c.l1.Ln_GSD_Asset##ib2.crisis if CoAge>=0 & NATION=="UNIT
> ED STATES" & NATIONCODE==840 & FSTS>=10 & FSTS <=100 & GENERALINDUSTRYCLASSIFICATION ==1 & Year_<2
> 020 & Year_<YearInactive & Discr_GS_Rev!=1, fe cluster(n_WSID)
Fixed-effects (within) regression Number of obs = 938
Group variable: n_WSID Number of groups = 188
R-sq: Obs per group:
within = 0.1327 min = 1
between = 0.0051 avg = 5.0
overall = 0.0096 max = 18
F(17,187) = .
corr(u_i, Xb) = -0.7147 Prob > F = .
(Std. Err. adjusted for 188 clusters in n_WSID)
-------------------------------------------------------------------------------------------------
| Robust
Ln_EBIT_ROA | Coef. Std. Err. t P>|t| [95% Conf. Interval]
--------------------------------+----------------------------------------------------------------
Ln_Revenue | .6324088 .1731603 3.65 0.000 .2908101 .9740075
Ln_LTD_to_Sales | -.1416329 .0584044 -2.43 0.016 -.2568491 -.0264167
Ln_Intangible_Assets | -.1816245 .0582329 -3.12 0.002 -.2965023 -.0667468
CoAge | -.0027908 .0165359 -0.17 0.866 -.0354117 .0298302
wGDPpc | .0000134 .0000174 0.77 0.443 -.0000209 .0000477
wCPI | -.0212403 .0263041 -0.81 0.420 -.0731312 .0306507
wDCF | 2.58e-13 1.32e-13 1.95 0.052 -2.37e-15 5.19e-13
wExpgr | .0171985 .0136959 1.26 0.211 -.00982 .0442169
wGDPgr | .0045089 .0324868 0.14 0.890 -.0595788 .0685967
wCons | -6.90e-14 4.54e-14 -1.52 0.130 -1.58e-13 2.05e-14
Ln_PS_RD | -.0919234 .0727104 -1.26 0.208 -.2353614 .0515146
|
Ln_GSD_Asset |
L1. | .0831113 .3679609 0.23 0.822 -.6427766 .8089992
|
cL.Ln_GSD_Asset#cL.Ln_GSD_Asset | .2656332 .2406542 1.10 0.271 -.2091129 .7403792
|
crisis |
1 | -.188022 .1496301 -1.26 0.210 -.4832019 .1071579
3 | -.3896768 .1794329 -2.17 0.031 -.7436496 -.035704
|
crisis#cL.Ln_GSD_Asset |
1 | -.5481548 .3419877 -1.60 0.111 -1.222805 .126495
3 | -.523638 .3525392 -1.49 0.139 -1.219103 .171827
|
crisis#cL.Ln_GSD_Asset#|
cL.Ln_GSD_Asset |
1 | -.3290189 .2468779 -1.33 0.184 -.8160426 .1580048
3 | -.3656444 .2437182 -1.50 0.135 -.8464348 .115146
|
_cons | -13.58189 3.460469 -3.92 0.000 -20.40846 -6.755312
--------------------------------+----------------------------------------------------------------
sigma_u | 1.1117421
sigma_e | .59800123
rho | .77559559 (fraction of variance due to u_i)
-------------------------------------------------------------------------------------------------
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