Costly Multidimensional Screening

TL;DR

This paper investigates when a principal should use costly multidimensional screening instruments, finding that under positive correlation in preferences, simple one-dimensional screening is optimal, with applications to pricing and labor markets.

Contribution

It establishes conditions under which simple one-dimensional screening is optimal, even with multidimensional costly instruments, extending the theory of screening mechanisms.

Findings

Simple screening of the productive component is optimal under positive correlation.

The results hold for general type and allocation spaces, including nonlinear and interdependent valuations.

Applications include monopoly pricing, bundling, and labor market screening.

Abstract

A screening instrument is costly if it is socially wasteful and productive otherwise. A principal screens an agent with multidimensional private information and quasilinear preferences that are additively separable across two components: a one-dimensional productive component and a multidimensional costly component. Can the principal improve upon simple one-dimensional mechanisms by also using the costly instruments? We show that if the agent has preferences between the two components that are positively correlated in a suitably defined sense, then simply screening the productive component is optimal. The result holds for general type and allocation spaces, and allows for nonlinear and interdependent valuations. We discuss applications to monopoly pricing, bundling, and labor market screening.