The effect of variable pay schemes on workplace absenteeism

We estimate the effect of variable pay schemes on workplace absenteeism using two cross sections of British establishments. Private sector establishments that explicitly link pay with individual performance are found to have significantly lower absence rates. This effect is stronger for establishments that offer variable pay schemes to a greater share of their non-managerial workforce. Matched employer-employee data suggest that the effect is robust to a number of sensitivity tests. We also find that firms that tie a greater proportion of employees' earnings to variable pay schemes are also found to experience lower absence rates. Further, quintile regression results suggest that variable pay schemes have a stronger effect on establishments with an absence rate that is higher than an average or sustainable level. Finally, panel data suggest that a feedback mechanism is present, whereby high absenteeism in the past is related to a greater future incidence of individual variable pay schemes, which, in turn, is correlated with lower absence rates

Federated Learning Under Restricted User Availability

Federated Learning (FL) is a decentralized machine learning framework that enables collaborative model training while respecting data privacy. In various applications, non-uniform availability or participation of users is unavoidable due to an adverse or stochastic environment, the latter often being uncontrollable during learning. Here, we posit a generic user selection mechanism implementing a possibly randomized, stationary selection policy, suggestively termed as a Random Access Model (RAM). We propose a new formulation of the FL problem which effectively captures and mitigates limited participation of data originating from infrequent, or restricted users, at the presence of a RAM. By employing the Conditional Value-at-Risk (CVaR) over the (unknown) RAM distribution, we extend the expected loss FL objective to a risk-aware objective, enabling the design of an efficient training algorithm that is completely oblivious to the RAM, and with essentially identical complexity as FedAvg. Our experiments on synthetic and benchmark datasets show that the proposed approach achieves significantly improved performance as compared with standard FL, under a variety of setups.Comment: 5 pages, 4 figure

Performance Pay as an Incentive for Lower Absence Rates in Britain

Using two cross-sections of a representative dataset of British establishments, the effect of various forms of incentive pay (e.g. performance-related pay (PRP), profit-sharing, share ownership, cash bonuses) on the absence rates of firms is investigated. Incentives that are tightly linked to individual or group merit are found to be significantly related to lower absenteeism. Important disparities in the effect of PRP on absenteeism are detected, which depend on the extent of monitoring, private-public status, teamwork, and other organizational changes. The findings are robust to the potential endogenous relation between monitoring, PRP and absenteeism, and have important implications for the design of optimal compensation policies by firms

Performance Pay as an Incentive for Lower Absence Rates in Britain

Using two cross-sections of a representative dataset of British establishments, the effect of various forms of incentive pay (e.g. performance-related pay (PRP), profit-sharing, share ownership, cash bonuses) on the absence rates of firms is investigated. Incentives that are tightly linked to individual or group merit are found to be significantly related to lower absenteeism. Important disparities in the effect of PRP on absenteeism are detected, which depend on the extent of monitoring, private-public status, teamwork, and other organizational changes. The findings are robust to the potential endogenous relation between monitoring, PRP and absenteeism, and have important implications for the design of optimal compensation policies by firms

Variety of Performance Pay and Firm Performance: Effect of Financial Incentives on Worker Absence and Productivity

Using two cross-sections of a representative dataset of British establishments, the effect of various forms of performance-related pay (objective/subjective, individual/group/collective) on the absence rates and productivity of firms is investigated. Incentives that are tied to the subjective evaluation of individual merit are found to be significantly related to lower absenteeism, but have no effect on labour productivity. In contrast, PRP that is objectively conditioned on outputs has a beneficial effect on workers’ productivity, albeit with no effect on absence rates. The findings therefore suggest that firms are likely to use objective and subjective PRP schemes in tandem in order to counteract any possible dysfunctional responses on behalf of their workforce (e.g. intertemporal allocation of effort). It is also found that public sector firms and those which have interdependent production should be wary of using PRP as an absence control tool

Variety of Performance Pay and Firm Performance: Effect of Financial Incentives on Worker Absence and Productivity

Using two cross-sections of a representative dataset of British establishments, the effect of various forms of performance-related pay (objective/subjective, individual/group/collective) on the absence rates and productivity of firms is investigated. Incentives that are tied to the subjective evaluation of individual merit are found to be significantly related to lower absenteeism, but have no effect on labour productivity. In contrast, PRP that is objectively conditioned on outputs has a beneficial effect on workers’ productivity, albeit with no effect on absence rates. The findings therefore suggest that firms are likely to use objective and subjective PRP schemes in tandem in order to counteract any possible dysfunctional responses on behalf of their workforce (e.g. intertemporal allocation of effort). It is also found that public sector firms and those which have interdependent production should be wary of using PRP as an absence control tool

Optimal measurement locations for parameter estimation of distributed parameter systems

Identifying the parameters with the largest influence on the predicted outputs of a model revealswhich parameters need to be known more precisely to reduce the overall uncertainty on themodel output. A large improvement of such models would result when uncertainties in the keymodel parameters are reduced. To achieve this, new experiments could be very helpful,especially if the measurements are taken at the spatio-temporal locations that allow estimate the parameters in an optimal way. After evaluating the methodologies available for optimal sensor location, a few observations were drawn. The method based on the Gram determinant evolution can report results not according to what should be expected. This method is strongly dependent of the sensitivity coefficients behaviour. The approach based on the maximum angle between subspaces, in some cases, produced more that one optimal solution. It was observed that this method depends on the magnitude of outputs values and report the measurement positions where the outputs reached their extrema values. The D-optimal design method produces number and locations of the optimal measurements and it depends strongly of the sensitivity coefficients, but mostly of their behaviours. In general it was observed that the measurements should be taken at the locations where the extrema values (sensitivity coefficients, POD modes and/or outputs values) are reached. Further improvements can be obtained when a reduced model of the system is employed. This is computationally less expensive and the best estimation of the parameter is obtained, even with experimental data contaminated with noise. A new approach to calculate the time coefficients belonging to an empirical approximator based on the POD-modes derived from experimental data is introduced. Additionally, an artificial neural network can be used to calculate the derivatives but only for systems without complex nonlinear behaviour. The latter two approximations are very valuable and useful especially if the model of the system is unknown.EThOS - Electronic Theses Online ServiceUniversidad del Zulia, Maracaibo, VenezuelaGBUnited Kingdo