SOCIAL COMPARISON AND EFFORT PROVISION: EVIDENCE FROM A FIELD EXPERIMENT

Social comparison has potentially far reaching consequences in many economic domains. We conducted a field experiment to examine how social comparison affects workers' effort provision if their own wage or that of a co‐worker is cut. Workers were assigned to groups of two, performed identical individual tasks, and received the same performance‐independent hourly wage. Cutting both group members' wages caused a decrease in performance. But when only one group member's wage was cut, the affected workers decreased their performance more than twice as much as when both workers' wages were cut. This finding indicates that social comparison among workers affects effort provision because the only difference between the two wage‐cut treatments is the other group member's wage level. In contrast, workers whose wage was not cut but who witnessed their group member's pay being cut displayed no change in performance relative to the baseline treatment in which both workers' wages remained unchanged. This indicates that social comparison exerts asymmetric effects on effort.     

How Do Policies Affect the Exit Rate out of Unemployment? Disentangling Job Creation from Labour Market Frictions

This paper assesses the effects of labour market policies on the unemployment outflow rate while disentangling two channels, namely labour market tightness and employer–employee matching efficiency. Using a sample of 11 OECD countries over the period 1985–2007, we treat the endogeneity of market tightness with business cycle shocks and the tax wedge as instruments. We find that the replacement rate of unemployment benefits, Active Labour Market Policies as well as the tax wedge in countries with poorly representative unions, have a significant, robust, and large impact on market tightness. Employment protection has a negative but small impact on matching efficiency. Overall, policy effects appear to be mostly channeled through market tightness and job creation.     

Asymptotic approximation of the likelihood of stationary determinantal point processes

Continuous determinantal point processes (DPPs) are a class of repulsive point processes on ${ℝ}^d$ with many statistical applications. Although an explicit expression of their density is known, it is too complicated to be used directly for maximum likelihood estimation. In the stationary case, an approximation using Fourier series has been suggested, but it is limited to rectangular observation windows and no theoretical results support it. In this contribution, we investigate a different way to approximate the likelihood by looking at its asymptotic behavior when the observation window grows toward ${ℝ}^d$. This new approximation is not limited to rectangular windows, is faster to compute than the previous one, does not require any tuning parameter, and some theoretical justifications are provided. It moreover provides an explicit formula for estimating the asymptotic variance of the associated estimator. The performances are assessed in a simulation study on standard parametric models on ${ℝ}^d$ and compare favorably to common alternative estimation methods for continuous DPPs.     

Testing for the Price- and Wage-Setting Model in Belgium Using Multivariate Cointegration Tests

Using multivariate cointegration tests based on Johansen's approach, this paper tests for the existence of long-run relationships between real wages and other explaining variables in Belgium. We retain two cointegrating vectors which can refer to wage and price setting behaviours.     

Coordinated Contract Decisions in a Make‐to‐Order Manufacturing Supply Chain: A Stochastic Programming Approach

One of the important objectives of supply chain S&OP (Sales and Operations Planning) is the profitable alignment of customer demand with supply chain capabilities through the coordinated planning of sales, production, distribution, and procurement. In the make‐to‐order manufacturing context considered in this paper, sales plans cover both contract and spot sales, and procurement plans require the selection of supplier contracts. S&OP decisions also involve the allocation of capacity to support sales plans. This article studies the coordinated contract selection and capacity allocation problem, in a three‐tier manufacturing supply chain, with the objective to maximize the manufacturer's profitability. Using a modeling approach based on stochastic programming with recourse, we show how these S&OP decisions can be made taking into account economic, market, supply, and system uncertainties. The research is based on a real business case in the Oriented Strand Board (OSB) industry. The computational results show that the proposed approach provides realistic and robust solutions. For the case considered, the planning method elaborated yields significant performance improvements over the solutions obtained from the mixed integer programming model previously suggested for S&OP.