The Distribution of Depth
In the capital as power framework, "depth" refers to the ratio of profit per employee, while "breadth" refers to the number of employees. Depth and breadth represent different methods for pursuing the accumulation of capital. Under a breadth regime, firms attempt to become more profitable by increasing their size (measured in employment), while under a depth regime, firms attempt to become more profitable by increasing profit per employee.
Rather than analyze changes in profitability per employee, in this post I look at the spectrum (or distribution) of depth. In order to make analysis easier, I have redefined depth as capitalization per employee (rather than profit). The reason for this change is that market cap, unlike profit, can never be negative. This makes analyzing the depth spectrum easier, because most skewed distribution functions (such as the lognormal distribution used here) can only take on positive values. Since market cap and profitability are closely related, this change shouldn't be too problematic.
To conduct this analysis, I used data from over 4000 firms in the Compustat USA database in the year 2012. I then constructed a histogram of this data using logarithmic bins, meaning bin size does not remain constant, but rather grows exponentially:
ie. bin 1 = market cap per employee of $1-$10
bin 2 = market cap per employee of $101-$1000
bin 3 = market cap per employee of $1001-$10,000
The result is the histogram below labeled "Empirical Data". The resulting distribution is plotted with the x-axis on a logarithmic scale, giving what appears to be a "normal" distribution. However, the spectrum of depth is not normally distributed at all ... it is lognormally distributed.
The lognormal distribution (http://en.wikipedia.org/wiki/Log-normal_distribution)
is heavily skewed rightward, and belongs to a class of "fat-tail" distributions. As the name implies, the lognormal distribution looks like a normal distribution when plotted on a log scale. Its skewness is easier to see without the log scale.
Enough with mathematics ... what does this mean for political economy? Of particular interest is the right end of the depth spectrum. What kind of firm is capable of generating a market cap per employee of $1 billion? While I haven't conducted a thorough analysis, a quick look suggests that these firms are mostly trust funds and royalty funds.
Topping out the list is Western Asset Mortgage Capital Corporation, which manages residential mortgage-backed securities. Also on the list is Royal Gold, whose principal business activity is the acquisition and management of precious metal royalties. Also at the top is the North European Oil Royalty Trust, which manages oil royalties.
On the left hand of the spectrum, I expected to find mostly startup companies ... I was wrong. Bottoming out the list were large firms such as International Textile Group, Inc and Kelly Services, Inc (the largest temp agency in the US).