In reply to Ksharp.

No, there are at least two problems with using PCA for this task:
1. The principal components are determined by the data. In particular, the first PC is the direction of maximal variation. For standardized variables. you might get a score such as 0.7*Test1 + 0.7*Test2. This might satisfy the law school, but it will not satisfy those who want to emphasize one test score more than the other.
2. A principal component can use negative coefficients to form the linear combinations, whereas weights are always positive. If Test1 and Test2 are negatively correlated, the PCA will give 0.7*Test1 - 0.7*Test2. The minus sign is not acceptable for a weight vector.