Hello,

I am having some difficulty interpreting the p-value of my results - especially the dummy variables. Are you able to interpret the p-values of dummy variables? If not, how can I properly code my regression to incorporate the dummy variables? If you can interpret the p-value of dummy variables, what happens when some are statistically significant, and others aren't? Am I doing something wrong here?

Thanks in advance,

Quinn

Variable List:

Dependent variable: Public support for income equality
Independent variables: income, skilled labour, ethnicity
Control: education level, employement status, number of children, sex, age range

regress moreequal highincome i.moreskill b3.ethnicity i.highedu b5.employstat morechild i.female i.agerange


Source | SS df MS Number of obs = 2,616
-------------+---------------------------------- F(19, 2596) = 9.98
Model | 1181.16033 19 62.1663333 Prob > F = 0.0000
Residual | 16165.6287 2,596 6.22712968 R-squared = 0.0681
-------------+---------------------------------- Adj R-squared = 0.0613
Total | 17346.789 2,615 6.63357132 Root MSE = 2.4954

--------------------------------------------------------------------------------------
moreequal | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
highincome | -.1642055 .0259355 -6.33 0.000 -.2150619 -.1133492

moreskill |
Semi-skilled | .4099856 .1308398 3.13 0.002 .1534246 .6665466
Skilled | -.485611 .1486537 -3.27 0.001 -.7771029 -.1941191

ethnicity |
Black | -.5094474 .1684931 -3.02 0.003 -.8398417 -.179053
Coloured | .2522887 .2262135 1.12 0.265 -.1912884 .6958658
Other | -.6747567 .3086933 -2.19 0.029 -1.280067 -.0694467

highedu |
Primary | -.3592873 .2671538 -1.34 0.179 -.8831433 .1645687
Secondary | -.5459883 .2726625 -2.00 0.045 -1.080646 -.0113303
Post-Secondary | -.7621883 .3413934 -2.23 0.026 -1.431619 -.0927573

employstat |
Full-time | -.1003902 .1315503 -0.76 0.445 -.3583444 .1575639
Part-time | -.3351507 .1939232 -1.73 0.084 -.7154105 .0451092
Self-employed | -.1412256 .2606941 -0.54 0.588 -.6524151 .3699639
Not in labour force | -.1179686 .1585718 -0.74 0.457 -.4289085 .1929714

morechild | -.1130585 .0492506 -2.30 0.022 -.2096329 -.0164842

female |
Female | .0241241 .1002043 0.24 0.810 -.1723645 .2206126

agerange |
30-39 | .1037347 .1343116 0.77 0.440 -.159634 .3671034
40-49 | .3456979 .1630838 2.12 0.034 .0259104 .6654854
50-69 | .1078065 .1914722 0.56 0.573 -.2676472 .4832601
60 and older | .1870045 .258449 0.72 0.469 -.3197825 .6937915

_cons | 6.716194 .363987 18.45 0.000 6.00246 7.429928