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. 
Jean-Fran\c{c}ois Chamayou
math.PR