On the Role of Learning, Human Capital, and Performance Incentives for Wages
Braz Camargo (),
Fabian Lange and
Elena Pastorino
No 30191, NBER Working Papers from National Bureau of Economic Research, Inc
Abstract:
Performance pay, through which firms provide workers with incentives for performance, is known to be an important source of the variation in wages across workers. Little is known, though, about the impact of performance pay on wages over the life cycle or about the sources of its variability with workers’ labor market experience. In this paper, we fill this gap by accounting for the possibility that incentives for performance also arise implicitly, as often argued, from workers’ desire to prove themselves whenever their productivity is uncertain and to accumulate human capital when employed. We propose a framework that integrates and extends well-known models of dynamic moral hazard and of information and human capital acquisition in the labor market. This framework allows us to analytically decompose performance pay into distinct terms that capture the basic forces we nest, and is identified under intuitive conditions. We parameterize the model using data from foundational papers in personnel economics and find that the most important determinants of performance pay are workers’ desire to insure against the wage risk due to the uncertainty about their productivity, which explains the relatively low level of performance pay, and their incentive to acquire human capital through learning-by-doing. The contemporaneous risk-incentive trade-off that much of the literature on performance incentives has emphasized is instead less important. Our estimates imply that performance pay is central to the dynamics of wages over the life cycle because of its direct impact on the variability of wages and its indirect impact on the process of human capital acquisition with experience.
JEL-codes: D8 D86 J24 J3 J31 J33 J41 J44 (search for similar items in EconPapers)
Date: 2022-06
New Economics Papers: this item is included in nep-dge, nep-hrm and nep-lma
Note: EFG LS
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