In recent years, a breakthrough in statistical physics has occurred. S
imply put, statistical physicists have determined that physical system
s which consist of a large number of interacting particles obey univer
sal laws that are independent of the microscopic details. This progres
s was mainly due to the development of scaling theory. Since economic
systems also consist of a large number of interacting units, it is pla
usible that scaling theory can be applied to economics. To test this p
ossibility we study the dynamics of firm size. This may help to build
a more complete characterization of the nature and processes behind fi
rm growth. To date, the study of firm dynamics has primarily focused o
n whether small firms on average have higher growth rates than large f
irms. To a lesser extent, attention has been placed on the relationshi
p between firm size and variation in growth rate. Our research goes be
yond these questions by looking at the relationship between numerous f
irm characteristics and the entire distribution of growth rates. Thus,
it may provide a better understanding of the mechanisms behind firm d
ynamics. In contrast to previous studies, this research analyzes data
over many time scales, instead of just a single time interval. From a
scientific standpoint, this work could be useful because it will affec
t the formulation of firm modeling - one of the basic building blocks
of all economic analysis. In addition, this work will have practical a
pplications. For example, there are Federal policies that are designed
to encourage small businesses. While such policies might be justified
on grounds other than their contribution to growth, any systematic di
fference in the growth rates of small and large firms might be relevan
t for evaluating such policies. Also, there has traditionally been a c
oncern that an excessive amount of economic activity might become conc
entrated in a small number of firms. A more detailed understanding of
the firm growth process will provide evidence for whether such concern
s have any scientific foundation.