A Random Difference Equation with Dufresne Variables revisited

The Dufresne laws (laws of product of independent random variables with gamma and beta distributions) occur as stationary distribution of certain Markov chains $X_n$ on $R$ defined by: \begin{equation} X_n = A_n ( X_{n-1} + B_n ) \end{equation} where $X_0 , (A_1,B_1),...,(A_n,B_n)$ are independent and the $(A_i,B_i)'$s are identically distributed. This paper generalizes an explicit example where $A$ is the product of two independent $\beta_{a,1} , \beta_{b,1}$ and $B \sim \gamma_1$ or $\gamma_2$. Keywords: beta, gamma and Dufresne distributions,Markov chains, stationary distributions, hypergeometric differential equations, Poisson process.