the association and 0 otherwise. Thus, we use a simple logit
model (again with sampling weights) to estimate the effects of the
independent variables on the probability that a woman will head
the forest user association (For further details, see Long, 1997).
Table 6 reports the effects in a similar manner to Table 5. In the
first column the actual estimated coefficient estimates are
reported, and in the second column the marginal effects for those
variables are reported. (Again, dummy variables represent firstdifferences
in probabilities.) The results indicate that the effect of
having women councilors in the past is not a significant predictor
of having a woman as a leader in the forest association in the
present. Wealth inequality, however, significantly reduces the
probability of a woman leader. From the marginal effects reported
in the second column we can see that holding all other variables at
their means, an association with high wealth inequality has a 0.10
lower probability of having a woman leader than places with low
wealth inequality (significant at the 0.01 level).