2016
DOI: 10.1108/ijm-12-2014-0265
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Performance related pay, productivity and wages in Italy: a quantile regression approach

Abstract: The authors analyzed the role of Performance Related Pay (PRP) in a sample of Italian manufacturing and service firms and presented standard quantile estimates to investigate heterogeneity in pay-performance impacts on labor productivity and wages. In a second stage, the endogeneity of PRP was taken into account by using instrumental variable quantile regression techniques. They find considerable heterogeneity across the distribution of labor productivity and wages, with the highest role of PRP obtained at the… Show more

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Cited by 11 publications
(11 citation statements)
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“…Our findings are similar to Damiani, Pompei, and Ricci () who estimate a positive policy effect across the quantiles of earnings and productivity of Italians firms. While Damiani, Pompei, and Ricci () find a positive U‐shaped curve, we find a (near) U‐shaped distributional policy effect on earnings but a downward distributional effect on workers' productivity. When considering gender differences, we find that the SSPP has a positive and near U‐shaped effect on earnings of females workers but a downward distributional effect on that of males.…”
Section: Introductionsupporting
confidence: 91%
“…Our findings are similar to Damiani, Pompei, and Ricci () who estimate a positive policy effect across the quantiles of earnings and productivity of Italians firms. While Damiani, Pompei, and Ricci () find a positive U‐shaped curve, we find a (near) U‐shaped distributional policy effect on earnings but a downward distributional effect on workers' productivity. When considering gender differences, we find that the SSPP has a positive and near U‐shaped effect on earnings of females workers but a downward distributional effect on that of males.…”
Section: Introductionsupporting
confidence: 91%
“…() — to extensive matched employer–employee data sets that provide direct measures of labour productivity. This allowed to re‐examine the nexus between worker characteristics (such as age, gender, and training), labour productivity, wages, and profits (Cardoso et al ., ; Damiani et al ., ; Devicienti et al ., ; Konings and Vanormelingen, ; Nielen and Schiersch, ; van Ours and Stoeldraijer, , ). Instead of merely assuming that wage differentials between educational groups mirror differences in productivity, which has long been the modus operandi of empirical research within the Mincer framework (Lemieux, ; Pereira and Martins, ), Current literature estimates how the observed productivity differences between educational groups compare with observed differences in labour costs.…”
Section: Literature Reviewmentioning
confidence: 99%
“…This two‐equation approach, pioneered by Hellerstein et al . (), is now standard in the literature on the productivity and wage effects of labour heterogeneity, notably in terms of age, gender, and employment contracts (Cardoso et al ., ; Damiani et al ., ; Garnero et al ., ; Giuliano et al ., ; Hellerstein and Neumark, ; Konings and Vanormelingen, ; Mahlberg et al ., ; Nielen and Schiersch, ). To our knowledge, it has never been used to examine the nexus between educational mismatch, productivity, and wages.…”
Section: Estimation Frameworkmentioning
confidence: 99%
“…The authors use a sample of firms located in an Italian region (Emilia Romagna) and control for endogeneity through a two-stage procedure 7 . Damiani et al (2016) analyze the direct link between PRP and labor productivity by applying a quantile regression (and its IV extension) on survey data 8 from manufacturing firms in the period 2005-2007-2010, finding a positive effect on labor productivity (9.5%) that is substantially uniform and significant across all the quantiles. 9 Lucifora and Origo (2015), working on a sample of 3000 Italian firms operating in the metal engineering sector during the period 1989-1999, find a positive, but rather limited effect (3-5%) of PRP on labor productivity.…”
Section: Literature Review and Backgroundmentioning
confidence: 99%