Dear all,

I want to verify if I'm interpreting my glm model right. I have a dependent variable, in percentage, (the percentage of the country i population which gave money to charity in 2010, i=1,...,44) and independent variables also measured in percentages (e.g. percentage of the country i population that feels happy).
I used a glm model

You can see my dataset using:


Code:
dataex givingmoney Souci_humankind_much tolerance_at_home_mentioned Justifyied_cheat_tax_never Unemployed_should_take_any_job Do_you_consider_you_religious past_frequence_week_month q11_how_satisfied_with_life_very

Code:
input float(givingmoney Souci_humankind_much tolerance_at_home_mentioned Justifyied_cheat_tax_never Unemployed_should_take_any_job Do_you_consider_you_religious past_frequence_week_month q11_how_satisfied_with_life_very)
Code:

.27 11.83 55.74 48.2 59.5 90.8 9.48 34.97
.69 10.88 68.72 56.71 55.95 63.88 58.7 61.1
.06 17.43 66.87 62.26 33.04 88.71 31.55 28.28
.4 10.31 82.24 40.25 53.95 57.79 67.22 63.86
.29 10.84 58.13 73.55 39.57 94.82 50.03 50.6
.18 12.15 65.21 68.11 55.15 61.15 11.35 30.47
.11 14.08 63.87 27.68 39.02 31.78 11.92 28.56
.26 10.97 70.21 58.16 43.72 83.61 75.09 53.11

I'm using the glm command:
Code:
glm givingmoney Souci_humankind_much tolerance_at_home_mentioned Justifyied_cheat_tax_never Unemployed_should_take_any_job Do_you_consider_you_religious past_frequence_week_month q11_how_satisfied_with_life_very ,  family(binomial) link(logit) robust


I verified my resid :
Code:
ovfplot
and
Code:
rvfplot2, yline(0)
and I want to interpret the effect of my independent variables:
I used
Code:

mfx
.

How do I interpret these figures? As I'm using a link(logit) it should be : one unit increase in my independent variable causes a exp(coefficient value) change (odds ratio) in the dependent variable. However,how a one unit change in a independent variable in % should be interpreted? a 1% increase in the independent variable causes exp(coefficient)% in the dependent variable?

Thank you