Monitoring for worker quality: a theory of task assignment, job ladders, wages and mobility in internal labor markets

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The broad goal of the proposed research is to understand how the nature of information and the technology for acquiring it affect wages, promotion paths and task-assignment within firms (the internal labor market). The narrower goal is to explain some of the regularities and variation in the structure of internal labor markets for non-managerial workers. In contrast with much of the literature, the PIs do not focus on policies intended to incentivize hard work or discourage moral hazard, which may be an intuitively unappealing starting point and might lead to conclusions that are inconsistent with the data. Instead, this project focuses on monitoring in order to assess workers.The baseline model is one with two types of workers, good and bad, and two types of task, high and low. In this model most work is routine (at least for suitably trained workers), but workers face occasional "crises" which good workers can resolve but bad workers cannot. Failures are readily observed, but successes are only observed if the firm monitors the worker. Routine work is more productive in the "high" task but failures are more costly. Since monitoring is costly, a firm can choose one of three strategies. First, it can place a worker in the high task and hope for the best. Second, the firm can assign the worker to the low task and monitor the worker. When a crisis arrives, it will observe success as well as failure and know whether the worker is good or bad. Workers who resolve the crisis will be moved to the high task. Finally, it can assign the worker to the low task, not monitor and wait for a failure. As time passes without a failure, it becomes increasingly likely that the worker has successfully resolved a crisis. When sufficient time has passed, the firm will assign the worker to the high task.The first task of this project is the completion of an optimal assignment model with extensions such as partial monitoring, false positive and false negatives as well as the consideration of multiple tasks of increasing complexity. The second task is to embed the model in a broader model of the labor market and wage determination.This type of analysis is expected to enable the PIs to explain important features of non-managerial labor markets.