Performance related pay, productivity and wages in Italy: a quantile regression approach
Abstract
Purpose
The purpose of this paper is to analyse the role of performance-related pay (PRP) on productivity and wages of Italian firms.
Design/methodology/approach
A unique data set for the Italian economy, obtained from the ISFOL Employer and Employee Surveys (2005, 2007, 2010), is used to estimate the relationship between PRP, labour productivity and wages, also controlling for an ample set of covariates. The authors performed standard quantile regressions (QRs) to investigate heterogeneity in associations of PRP with labour productivity and wages. In a second stage, the endogeneity of PRP was taken into account by using instrumental variable QR techniques.
Findings
The econometric estimates suggests that PRP are incentive schemes that substantially lead to efficiency enhancements and wage gains. These findings are confirmed for firms under union governance and suggest that well-designed policies, that circumvent the limited implementation of PRP practices, would guarantee productivity improvement and wage premiums for employees.
Research limitations/implications
The main limitation of the findings concerns PRP data, that do not offer statistical information on different types of schemes, at group or individual level.
Originality/value
This paper is the first to investigate, on a national scale for the Italian economy, the role of PRP on both productivity and wages, in order to shed light on the efficiency and distributive implications, whereas most of the studies of related literature are restricted to one of those aspects.
Keywords
Acknowledgements
JEL Classification — D24, J31, J33, J51
The authors are grateful to Vincent Vandenberghe and other participants to the workshop on Firm-Level Analysis of Labour issues, Louvain-la-Neuve (UCL-Belgium), 28 May 2014, for their useful comments. All errors remain the authors’ own.
Citation
Damiani, M., Pompei, F. and Ricci, A. (2016), "Performance related pay, productivity and wages in Italy: a quantile regression approach", International Journal of Manpower, Vol. 37 No. 2, pp. 344-371. https://doi.org/10.1108/IJM-12-2014-0265
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited