Tail integral formula for moments

For $q>0$ and a random variable $X$ with finite absolute $q$th moment, Tonelli theorem gives

For a nonnegative random variable, $Y={\int }_0^{\infty }{1}_{\{Y>t\}}dt$ pointwise, including when $Y=\infty$. Tonelli's theorem permits taking expectation under the integral and proves the formula in the extended nonnegative reals. This relates finiteness of a Brownian exit time expectation to integrability of its survival probability.

If $\mathbb{P}(|Z|\ge t)\le A{e}^{-b{t}^2}$ for $A\ge 1$ and $b>0$, then $\mathbb{E}{Z}^2\le (1+\log A)/b$. Indeed the tail integral formula for moments gives $\mathbb{E}{Z}^2\le {\int }_0^{\infty }\min (1,A{e}^{-bu})du$; split at $u=(\log A)/b$. Clipping at one improves the constant compared with integrating the exponential bound alone.