Estimating the rate of return to a university degree has always been difficult due to the problem of omitted variable biases. Benefiting from a special feature of the University Admission system in China, which has clear cutoffs for university entry, combined with a unique data set with information on individual National College Entrance Examination (NCEE) scores, we estimate the Local Average Treatment Effects (LATE) of university education based on a Regression Discontinuity design. To the best of our knowledge, this is the first study to use RD design to estimate the causal effect of a university education on earnings. Our results show that the rates of return to 4-year university education relative to 3-year college education are 40 and 60 per cent for the compliers in the male and female samples, respectively, which are much larger than the simple OLS estimations revealed in previous literature. Since in our sample a large proportion of individuals are compliers (45 per cent for males and 48 per cent for females), the LATEs estimated in this paper have a relatively general implication. In addition, we find that the LATEs are likely to be larger than ATEs, suggesting that the inference drawn from average treatment effects might understate the true effects of the university expansion program introduced in China in 1999 and thereafter.