I have a panel data of 26 countries and 21 years, but I am only concerned with 38 observations. The main variables of interest are a, b and c, which are interaction terms in spline form. The following is what I obtain (all the variables are statistically significant), can you please let me know how to interpret them or how can I estimate this small sample:
Code:
glm vote a b c previousvote coalition right left govtexpr > govtexpl govtexpc gdp gdpgrowth gdppercapita inflat > ion unemployment illiteracy i.country, fa(b) link(logit) vce(robust) note: vote has noninteger values Iteration 0: log pseudolikelihood = -14.9742 Iteration 1: log pseudolikelihood = -14.955528 Iteration 2: log pseudolikelihood = -14.955446 Iteration 3: log pseudolikelihood = -14.955446 Generalized linear models No. of obs = 38 Optimization : ML Residual df = 34 Scale parameter = 1 Deviance = 8.42197e-16 (1/df) Deviance = 2.48e-17 Pearson = 3.74438e-16 (1/df) Pearson = 1.10e-17 Variance function: V(u) = u*(1-u/1) [Binomial] Link function : g(u) = ln(u/(1-u)) [Logit] AIC = .9976551 Log pseudolikelihood = -14.95544633 BIC = -123.6779 ------------------------------------------------------------------------------------ | Robust vote | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------------+---------------------------------------------------------------- a | 74.80361 8.51e-08 8.8e+08 0.000 74.80361 74.80361 b | -26.26746 2.26e-08 -1.2e+09 0.000 -26.26746 -26.26746 c | 73.66431 7.69e-09 9.6e+09 0.000 73.66431 73.66431 previousvote | -1.20297 3.48e-10 -3.5e+09 0.000 -1.20297 -1.20297 coalition | -.0847244 5.00e-10 -1.7e+08 0.000 -.0847244 -.0847244 right | 3.102455 1.08e-09 2.9e+09 0.000 3.102455 3.102455 left | 1.619646 1.66e-09 9.7e+08 0.000 1.619646 1.619646 govtexpr | 5.210685 1.32e-08 4.0e+08 0.000 5.210685 5.210685 govtexpl | 7.271918 1.30e-08 5.6e+08 0.000 7.271918 7.271918 govtexpc | 10.33364 9.53e-09 1.1e+09 0.000 10.33364 10.33364 gdp | 41.34051 4.17e-08 9.9e+08 0.000 41.34051 41.34051 gdpgrowth | 11.10806 1.30e-08 8.5e+08 0.000 11.10806 11.10806 gdppercap~a | -.6511851 1.86e-10 -3.5e+09 0.000 -.6511851 -.6511851 inflation | -14.94398 9.63e-09 -1.6e+09 0.000 -14.94398 -14.94398 unemploym~t | -12.42717 7.46e-09 -1.7e+09 0.000 -12.42717 -12.42717 illiteracy | 7.969718 1.40e-08 5.7e+08 0.000 7.969718 7.969718 | country | 2 | -2.443257 6.08e-08 -4.0e+07 0.000 -2.443257 -2.443257 3 | -.9804617 2.66e-09 -3.7e+08 0.000 -.9804617 -.9804617 5 | -.6115759 1.99e-09 -3.1e+08 0.000 -.6115759 -.6115759 6 | .6141337 2.62e-10 2.3e+09 0.000 .6141337 .6141337 7 | .4435143 3.84e-09 1.2e+08 0.000 .4435143 .4435143 8 | .4853522 1.16e-09 4.2e+08 0.000 .4853522 .4853522 9 | -9.522004 9.61e-09 -9.9e+08 0.000 -9.522004 -9.522004 10 | -11.81219 1.13e-08 -1.0e+09 0.000 -11.81219 -11.81219 11 | -.3736216 4.62e-10 -8.1e+08 0.000 -.3736216 -.3736216 12 | -.4815581 2.90e-09 -1.7e+08 0.000 -.4815581 -.4815581 13 | 2.362357 2.16e-09 1.1e+09 0.000 2.362357 2.362357 17 | 5.388477 1.20e-09 4.5e+09 0.000 5.388477 5.388477 18 | -.0272883 1.19e-09 -2.3e+07 0.000 -.0272883 -.0272883 19 | -2.225435 1.63e-09 -1.4e+09 0.000 -2.225435 -2.225435 20 | -2.206832 1.32e-09 -1.7e+09 0.000 -2.206832 -2.206832 21 | -.6031301 9.51e-10 -6.3e+08 0.000 -.6031301 -.6031301 23 | .8808135 3.75e-09 2.3e+08 0.000 .8808135 .8808135 24 | .5304998 3.41e-09 1.6e+08 0.000 .5304998 .5304998 25 | -3.113585 2.36e-09 -1.3e+09 0.000 -3.113585 -3.113585 26 | -.1508862 7.78e-10 -1.9e+08 0.000 -.1508862 -.1508862 27 | -7.352184 6.55e-09 -1.1e+09 0.000 -7.352184 -7.352184 | _cons | -3.575941 7.12e-09 -5.0e+08 0.000 -3.575941 -3.575941 ------------------------------------------------------------------------------------ . end of do-file
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