For a random sample of size n from an absolutely continuous bivariate population (X, Y), let X-i:n be the i th X-order statistic and be its concomitant. We study the joint distribution of (V-s:m, Wt:n-m,), where V-s:m is the s th order statistic of the upper subset (Y-[i:n] i= n-m+ 1 n), and Wt:n-m, is the t th order statistic of the lower subset {Y-[j:n], j=1,...,n-m) of concomitants. When m = [np(0)], s = [mp(1)], and t = [(n-m)p(2)], 0 < p(i) < 1, i = 0,1,2, and n -> infinity, we show that the joint distribution is asymptotically bivariate normal and establish the rate of convergence. We propose second order approximations to the joint and marginal distributions with significantly better performance for the bivariate normal and Farlie-Gumbel bivariate exponential parents, even for moderate sample sizes. We discuss implications of our findings to datasnooping and selection problems. 2010 Elsevier B.V. All rights reserved.