Intelligent Machines and Incomplete Information

TL;DR

This paper models a firm's hiring process with incomplete information about employee efficiency, using an intelligent production technology that reveals efficiency levels through output, and characterizes the equilibrium in this setting.

Contribution

It introduces a novel model where output reveals employee efficiency, and characterizes the ex-ante Nash equilibrium under incomplete information.

Findings

Output distribution relates to efficiency levels.

Equilibrium characterized for the incomplete information game.

Model links effort, efficiency, and output in a new way.

Abstract

The distribution of efficient individuals in the economy and the efforts that they will put in if they are hired, there are two important concerns for a technologically advanced firm. wants to open a new branch. The firm does not have information about the exact level of efficiency of an individual when she is hired. We call this situation incomplete information. The standard principal agent models assume that employees know their efficiency levels. Hence these models design incentive-compatible mechanisms. An incentive-compatible mechanism ensures that a participant does not have the incentive to misreport her efficiency level. This paper does not assume that employees know how efficient they are. This paper assumes that the production technology of the firm is intelligent, that is, the output of the machine reveals the efficiency levels of employees. Employees marginal contributions to the total output of the intelligent machine, the probability distribution of the levels of efficiency and employees costs of efforts together define a game of incomplete information. A characterization of ex-ante Nash Equilibrium is established. The results of the characterization formalize the relationship between the distribution of efficiency levels and the distribution of output.