Dynamic screening

TL;DR

This paper investigates dynamic screening processes with noisy evaluations, revealing that the process quality is non-monotonic in the number of stages and that more stages can improve outcomes significantly.

Contribution

It provides a theoretical analysis showing the non-monotonic relationship between stages and screening quality, and demonstrates conditions under which increasing stages leads to optimal results.

Findings

Adding a single stage can worsen outcomes due to noise.

Increasing stages substantially can achieve first-best results.

The quality of screening is not always improved by more stages.

Abstract

We study dynamic screening problems where elements are subjected to noisy evaluations and, in every stage, some of the elements are rejected while the remaining ones are independently re-evaluated in subsequent stages. We prove that, ceteris paribus, the quality of a dynamic screening process is not monotonic in the number of stages. Specifically, we examine the accepted elements' values and show that adding a single stage to a screening process may produce inferior results, in terms of stochastic dominance, whereas increasing the number of stages substantially leads to a first-best outcome.