Template-Type: ReDIF-Paper 1.0
Title: Partnership Dissolution in a Search Market With On-The-Match Learning
Author-Name: Finn Schmieter 
Author-Email: finn.schmieter@uni-bonn.de 


Classification-JEL: C78, D83, J64
Keywords: Search frictions, matching, on-the-job search, learning

Abstract: We construct a frictional search-and-matching model with on-the-match learning
and rematching. Agents are ex-ante homogeneous, have idiosyncratic preferences,
and receive news about the profitability of their current match following a
Poisson process. We provide an infinite number of pointwise balance conditions
and a finite number of aggregate balance conditions and prove their equivalence.
We show that agents follow cutoff strategies in the unique steady-state equilibrium.
If the profitability types inside a match have a strong positive (negative)
correlation, then a faster learning rate is ex-ante welfare-increasing (decreasing)
for the agents.

Note: 
Length: 30
Creation-Date: 2022-01
Revision-Date: 
File-URL: https://www.crctr224.de/research/discussion-papers/archive/dp327
File-Format: application/pdf
Handle: RePEc:bon:boncrc:CRCTR224_2022_327