Assortative Learning


Authors: Jan Eeckhout and Xi Weng


Because of sorting, more skilled workers are more productive in higher-type firms. They also learn at different rates about their productivity and therefore expect different wage paths across firms. We show that under strict supermodularity, there is always positive assortative matching: differential learning is always dominated by the impact of productivity. Surprisingly, this holds even if learning is faster in the low-type firm. The key assumption driving this result is that this is a pure Bayesian learning model. The model provides realistic predictions about wage variance, turnover and the wage distribution that are in line with recent work that estimates the value of learning from co-workers.