[NIki Young]

So is there any economic meaning of the coefficient results?

Can I say that when the income is verified, income group 23 is more likely to default compare to income group 4, while income group 567 is less likely to default than income group 4, compare to the situation when income is not verified?

And I got the margins results, does it take into account the reference group 4? How should I interpretate the result of 0.0965732 from income group 3.



Delta-method
Margin Std. Err. z P>z [95% Conf. Interval]

incomeverified#income2
0 1 .0196078 .0194147 1.01 0.313 -.0184442 .0576599
0 2 .038961 .0110258 3.53 0.000 .0173509 .0605712
0 3 .0316196 .0027186 11.63 0.000 .0262913 .0369479
0 4 .0434022 .0038121 11.39 0.000 .0359306 .0508738
0 5 .0328048 .004165 7.88 0.000 .0246415 .0409681
0 6 .0628898 .0055346 11.36 0.000 .0520423 .0737373
0 7 .0706161 .0055771 12.66 0.000 .0596852 .081547
1 1 . (not estimable)
1 2 .25 .2165064 1.15 0.248 -.1743446 .6743447
1 3 .0965732 .0164863 5.86 0.000 .0642607 .1288857
1 4 .0846561 .0143178 5.91 0.000 .0565938 .1127184
1 5 .0217391 .0107508 2.02 0.043 .000668 .0428102
1 6 .0208333 .0103076 2.02 0.043 .0006308 .0410358
1 7 .0149254 .0074068 2.02 0.044 .0004083 .0294424

[Clyde Schechter]

You would state that the results are adjusted for age and gender. This means that the odds ratios or marginal effects, or any other results you might have calculated, have been modified to reduce or eliminate any differences between groups that results from those groups having different age or sex distributions.