The question is somewhat ambiguous, but I interpret "collected your nth coupon" to mean that you finally have n different types in your collection, but you may have purchased many more and thrown many away because they were not different from one you had already. (That is the standard interpretation in the so-called coupon collector's problem.)
Your proposed solution does not account properly for the fact that n (different) types have been collected already. For example, in the classical problem we have all p_i = 1/m for i = 1,2, ..., m. If n = 1 the probability that the next purchased coupon is the same as the first one is 1/m, so the probability that it is different is 1-1/m. By the time you have collected n = m-1 different coupons, the probability that the next purchased coupon is different is 1/m. Things to the power of n do not come into it.
However, what is worse is that your solution does not account for the fact that different coupons have different probabilities p_i. I will just look at the second coupon. After collecting 1 coupon, what is the probability that your second purchased coupon is different from it? Look instead at the probability it is the same. If we don't observe exactly what the first collected coupon is (say a friend is collecting coupons for us in another room and we don't see what is happening---all we get is a signal saying "same" or "different"). In that type of scenario, the probability of S (same) given the first is of type i (event Fi) is
[tex]P\{S\} = \sum_{i=1}^m P(S|F_i) P(F_i) = \sum p_i \cdot p_i = \sum p_i^2/[/tex] So, the probability your next purchased coupon is different from the first one is ##1 - \sum p_i^2.## This is the result you want if n = 1.
Similarly, if n = 2 the probability you want is ##1 - (\sum p_i^2 - \sum p_i^3), ## etc. I have not yet extended this to n = 3 or n = 4, etc.; it starts to get complicated.
However, maybe the problem assumes you do know what coupons have already been collected. By relabelling if necessary, assume we already have coupons 1,2, ...,n and want to know the probability of collecting coupon n+1 or n+2 or ..., or coupon m on the next purchase. Can you see how to compute that?
RGV