  Externalities are the costs that a user of a common resource imposes on
others. For example, consider a FCFS M/G/1 queue and a customer with service
demand of $x\geq0$ minutes who arrived into the system when the workload level
was $v\geq0$ minutes. Let $E_v(x)$ be the total waiting time which could be
saved if this customer gave up on his service demand. In this work, we analyse
the \textit{externalities process} $E_v(\cdot)=\left\{E_v(x):x\geq0\right\}$.
It is shown that this process can be represented by an integral of a (shifted
in time by $v$ minutes) compound Poisson process with positive discrete jump
distribution, so that $E_v(\cdot)$ is convex. Furthermore, we compute the LST
of the finite-dimensional distributions of $E_v(\cdot)$ as well as its mean and
auto-covariance functions. We also identify conditions under which, a sequence
of normalized externalities processes admits a weak convergence on
$\mathcal{D}[0,\infty)$ equipped with the uniform metric to an integral of a
(shifted in time by $v$ minutes) standard Wiener process. Finally, we also
consider the extended framework when $v$ is a general nonnegative random
variable which is independent from the arrival process and the service demands.
This leads to a generalization of an existing result from a previous work of
Haviv and Ritov (1998).
