  The distribution of impact factors has been modeled in the recent informetric
literature using two-exponent law proposed by Mansilla et al. (2007). This
paper shows that two distributions widely-used in economics, namely the Dagum
and Singh-Maddala models, possess several advantages over the two-exponent
model. Compared to the latter, the former give as good as or slightly better
fit to data on impact factors in eight important scientific fields. In contrast
to the two-exponent model, both proposed distributions have closed-from
probability density functions and cumulative distribution functions, which
facilitates fitting these distributions to data and deriving their statistical
properties.
