Cookies?
Library Header Image
LSE Research Online LSE Library Services

Managing intrinsic motivation in a long-run relationship

Eliaz, Kfir and Spiegler, Ran (2014) Managing intrinsic motivation in a long-run relationship. CFM discussion paper series (CFM-DP2014-14). Centre For Macroeconomics, London, UK.

[img]
Preview
PDF - Published Version
Download (265kB) | Preview

Abstract

We study a simple model of a long-run relationship between an employer and a worker. Due to contractual incompleteness, the employer is effectively restricted to offering a "spot" wage contract at every period (rather than a more elaborate performance-based payment scheme). If the worker rejects an offer, the two parties are permanently separated. The worker's productivity relies on his "intrinsic motivation". Motivated by ideas in the behavioural-economics literature, we assume that intrinsic motivation is "reference-dependent". Specifically, at any period during the relationship, the worker's productivity plummets if his wage falls below a "reference wage", which we define to be his lagged-expected wage in that period. We assume that the worker's outside option follows a Markov process with i.i.d shocks. We characterize the equilibrium path of the worker's wage, and show how it gives rise to patterns of wage rigidity and efficiency wages. We also show that the worker's rent (i.e. excess payoff relative to the outside option) is equal to the highest shock value. The modeling ideas in this brief paper may be applied to macro-labour models and illuminate wage-rigidity phenomena.

Item Type: Monograph (Discussion Paper)
Official URL: http://www.centreformacroeconomics.ac.uk/Home.aspx
Additional Information: © 2014 The Authors
Divisions: Centre for Macroeconomics
Subjects: H Social Sciences > H Social Sciences (General)
Date Deposited: 18 Jul 2014 14:24
Last Modified: 15 Sep 2023 23:32
Funders: Sapir Centre and ERC grant no. 230251
URI: http://eprints.lse.ac.uk/id/eprint/58020

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics