Let's assume that $y=e^x$, where $x\sim N(\mu,\sigma^2)$, that is, $y$ follows a lognormal distribution.
I'm interested in finding how $\mathbb{E}\left[y|y\geq a\right]$ varies with $\mu$ and $\sigma$. From https://en.wikipedia.org/wiki/Log-normal_distribution, it is to see that
$$ \mathbb{E}\left[y|y\geq a\right]=\frac{\int_{a}^{\infty}yf\left(y\right)dy}{\int_{a}^{\infty}f\left(y\right)dy}=\underbrace{e^{\mu+\frac{1}{2}\sigma^{2}}}_{\mathbb{E}\left[y\right]}\frac{\Phi\left(\sigma-\frac{\ln a-\mu}{\sigma}\right)}{1-\Phi\left(\frac{\ln a-\mu}{\sigma}\right)} .$$ So formally, if we define $h(\mu,\sigma) = \mathbb{E}\left[y|y\geq a\right]$, I want to understand $\frac{\partial h}{\partial\mu}$ and $ \frac{\partial h}{\partial\sigma} $, for any value of $a$. I've tried to work out the derivatives, but I always find that both can take any sign. I'm not surprised that $ \frac{\partial h}{\partial\sigma} $ can take any sign, but, shouldn't there be a way to prove that $$ \frac{\partial h}{\partial\mu} >0 ?$$
Is there a counterexample otherwise?