Peer effects on worker output in the laboratory generalize to the field

Peer effects on worker output in the laboratory generalize to the field
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实验室中工人产出的同伴效应可推广到现场

DOI:
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发表时间:
2015
期刊:
影响因子:
56.9
通讯作者:
Alexandre Mas
Alexandre Mas
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Daniel Z. Herbst;Alexandre Mas

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瑞士高中生和东欧季节性劳工有什么共同点?当前者的任务是在课堂上将问卷塞进信封,而后者则受雇在英国采摘水果时,两人在同龄人面前都会更加努力地工作。Herbst和Mas重新分析了35项此类研究的结果,这些研究要么是在受控条件下进行的实验,要么是基于实地收集的数据的实证研究(参见Charness和Fehr的观点)。令人鼓舞的是,他们发现溢出效应的大小--当其他工人在一起时,一个工人工作得有多努力--是一样的。实验室实验和现实世界的观察一致认为,当人们一起工作时,他们工作得更努力。[Also我们比较了实验室实验和自然环境中的实地研究中同伴对工人产出的影响。一个工人的工作效率随同事工作效率的提高而变化的平均研究水平估计值(γ)为γ^ = 0.12(SE = 0.03,n研究= 34),研究间标准差τ = 0.16。实验室和田间研究的平均γ^-估计值接近(γ^lab−γ^field = 0.04,P = 0.55,nlab = 11,nfield = 23),研究间方差τ2的估计值也接近(τ ^lab 2 −τ ^field 2 =-0.003,P = 0.89)。即使在控制了激励计划和工作复杂性等样本特征之后,实验室和现场估计值之间的微小平均差异仍然存在(γ^lab-γ^field = 0.03,P = 0.62,nsamples = 46)。实验室实验定量地概括了生产率溢出的均值和方差,提供了准确的描述。
Comparing lab and field estimates What do Swiss high-school students and Eastern European seasonal laborers have in common? When the former are tasked with stuffing questionnaires into envelopes in a classroom setting and the latter are employed to pick fruit in the United Kingdom, both work harder in the presence of their peers. Herbst and Mas reanalyzed the results of 35 such studies, either experiments carried out under controlled conditions or empirical studies based on data collected in the field (see the Perspective by Charness and Fehr). Encouragingly, they found that the magnitude of the spillover effect—how much harder a worker works when other workers are alongside—was the same. Science, this issue p. 545; see also p. 512 Lab experiments and real-world observations are in agreement that people work harder when they work together. [Also see Perspective by Charness and Fehr] We compare estimates of peer effects on worker output in laboratory experiments and field studies from naturally occurring environments. The mean study-level estimate of a change in a worker’s productivity in response to an increase in a co-worker’s productivity (γ) is γ^ = 0.12 (SE = 0.03, nstudies = 34), with a between-study standard deviation τ = 0.16. The mean estimated γ^-values are close between laboratory and field studies (γ^lab−γ^field = 0.04, P = 0.55, nlab = 11, nfield = 23), as are estimates of between-study variance τ2 (τ^lab2−τ^field2=−0.003, P = 0.89). The small mean difference between laboratory and field estimates holds even after controlling for sample characteristics such as incentive schemes and work complexity (γ^lab−γ^field = 0.03, P = 0.62, nsamples = 46). Laboratory experiments generalize quantitatively in that they provide an accurate description of the mean and variance of productivity spillovers.