When a model gets to be this fragile, the very general possibilities are
you are trying to include more predictors and/or use a model that the
data won't bear. Either way, retreat to something much simpler and then
build up to see where the problems enter.
Nick
[email protected]
Sue
I'm seeing some huge test statistics that I can't seem to explain. I
run -logit- on a set of regressors (some of them dummies, most of them
not; some country level, some firm level variables), and I also
interact all the regressors with another dummy and include those as
well. I then test for the significance of all the interaction terms.
The test statistics under this baseline model are in a reasonable
range; however, when I add just one more country level variable (which
is continuous), the test statistic on the interaction term goes crazy
and hits a number between 4-7 figures. Does anyone have an idea why
this might be happening? I'm showing part of the output below to give
you an idea:
africa (d) -177.1579***
(2.6441)
small (d) -0.6886***
(0.0987)
_IafrXsmall_1 (d) -0.3126
(0.2492)
medium (d) -0.1960***
(0.0574)
_IafrXmediu_1 (d) -0.1700
(0.1455)
foreign (d) -0.2349***
(0.0789)
_IafrXforei_1 (d) 0.2128
(0.2149)
exporter (d) 0.2909***
(0.0487)
_IafrXexpor_1 (d) -0.4631***
(0.1264)
manufacturing (d) 0.5076***
(0.1562)
_IafrXmanuf_1 (d) -0.9735***
(0.2952)
services (d) -0.2403
(0.1511)
_IafrXservi_1 (d) -0.9857*
(0.5771)
gdp_gr 6.8111
(5.1657)
_IafrXgdp_g_1 4.0075
(6.2356)
inf -1.6883
(1.5576)
_IafrXinf_1 49.0775***
(1.6506)
kkm 0.8556**
(0.3435)
_IafrXkkm_1 -13.0895***
(0.3669)
ca_gdp 1.2100
(2.7650)
_IafrXca_gd_1 128.8948***
(3.3821)
bc -1.3390
(0.8460)
_IafrXbc_1 75.3131***
(1.8706)
fos -2.1180***
(0.7812)
_IafrXfos_1 96.0801***
(1.3381)
gdp_pc -0.0085
(0.2651)
_IafrXgdp_p_1 -6.8328***
(0.2706)
ln_pd 0.2728*
(0.1458)
_IafrXln_pd_1 7.3811***
(0.2421)
natres -0.2812
(0.3640)
_IafrXnatre_1 133.4017***
(7.8873)
ln_population -0.0640
(0.1086)
_IafrXln_po_1 24.6676***
(0.2401)
ofc (d) -0.9053
(0.9095)
pop_gdp -0.0151
(0.2987)
_IafrXpop_g_1 -705.4406
(0.0000)
sec2prim_enrol 0.4339
(0.5475)
_IafrXsec2p_1 133.0970***
(1.3934)
new_geobrpen -0.1639 --> The variable that was added
to the baseline regression
(0.1455)
_IafrXnew_g_1 35.1637***
(1.0889)
N 32367
Chi_ln_pd 1580.0943
p_ln_pd 0.0000
Chi_ln_pop 12780.4619
p_ln_pop 0.0000
Chi_gdp_gr 9.5544
p_gdp_gr 0.0020
Chi_inf 8281.7145
p_inf 0.0000
Chi_kkm 9608.6463
p_kkm 0.0000
Chi_ca_gdp 4513.9768
p_ca_gdp 0.0000
Chi_new_geobrpen 1051.8437
p_new_geobrpen 0.0000
Chi_new_geobrpen 1051.8437
p_new_geobrpen 0.0000
Any idea would be appreciated.
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