  The present paper obtains a complete description of the limit distributions
of sample covariances in N x n panel data when N and n jointly increase,
possibly at different rate. The panel is formed by N independent samples of
length n from random-coefficient AR(1) process with the tail distribution
function of the random coefficient regularly varying at the unit root with
exponent $\beta$ > 0. We show that for $\beta$ $\in$ (0, 2) the sample
covariances may display a variety of stable and non-stable limit behaviors with
stability parameter depending on $\beta$ and the mutual increase rate of N and
n.
