A random variable taking positive values has density $f(t)$.
If I truncate the variable in $(0,x]$, the density should be $f_T(t,x)=f(t)/F(x)$.
If the truncation value $x$ is itself random with density $g(x)$ in $(0,b]$, the resulting density for $t$ should be
$$f_T(t) = \int_0^b \frac{ f(t) g(x) }{ F(x) } dx = f(t) \int_0^b \frac{ g(x) }{ F(x) } dx$$
However, the integral can be singular because $F(0)=0$.
General questions: Is if this derivation of $f_T(t)$ (the distribution of $t$ with random truncation parameter) correct? Can $f_T(t)$ really be undefined because of the singular integrand?
Specific question: if $f(t)=ae^{-at}$, and $g(x)=1/b$, the integral diverges "only" logarithmically. I am thinking of just introducing a cutoff so that $x$ is in $[a,b]$ with some $a>0$, but maybe there are better ways to deal with the divergence?
Writing $f_T(t,x) = \frac{f(t)}{F(x)}$ is an incomplete story. We should have $f_T(t,x) = 0$ when $t > x$. We could write this as $f_T(t,x) = \frac{f(t)}{F(x)}[t \le x]$, where $[t\le x]$ is an Iverson bracket equal to $1$ if the condition is met and $0$ otherwise.
Then $$ f_T(t) = \int_0^b \frac{f(t)g(x)}{F(x)}[t \le x] \,dx = f(t) \int_0^b \frac{g(x)}{F(x)}[t\le x]\,dx = f(t) \int_t^b \frac{g(x)}{F(x)}\,dx. $$ Now for values of $t$ where $F(t) > 0$ there is no problem with the integral, and for values of $t$ where $F(t) = 0$, we should also have $f_T(t) = f(t) = 0$.