Asymmetric Information between Employers
Lisa B. Kahn
published in: American Economic Journal: Applied Economics, 2013, 5 (4), 165-205
Employer learning about workers' abilities plays a key role in determining how workers sort into jobs and are compensated. This study explores whether learning is symmetric or asymmetric, i.e., whether potential employers have the same information about worker ability as the incumbent firm. I develop a model of asymmetric learning that nests the symmetric learning case and allows the degree of asymmetry to vary, yielding testable implications for the prevalence of asymmetric learning. I then show how predictions in the model can be tested using compensation data. Using the NLSY, I test the model and find strong support for asymmetric information.
I first exploit the fact that groups of workers differ in their variances in ability – based on economic conditions at time of entry into a firm – to show that incumbent wages track differences in ability distributions more closely than do outside firm wages. Second, I show that learning about ability is more symmetric for occupations that require more communication outside the firm. Finally, I show how to uncover the key parameter of interest in my model representing the degree to which information is asymmetric. My estimates imply that in one period, outside firms reduce the average expectation error over worker ability by roughly a third of the reduction made by incumbent firms. Thus outside firms retain sizeable expectation errors due to asymmetric information.
Text: See Discussion Paper No. 7147