Social networks and labour match quality: a search approach

个人往往依靠他们非正式的个人联系——社会网络——来找工作或改善他们的劳动力市场前景。理论文献的总体方向预测了网络对工人和企业之间匹配质量的积极影响，从而对工资和营业额产生积极影响，因为它们减少了信息和搜索摩擦。然而，经验文献给出了混合和异质的结果。我的目标是探索从网络到匹配质量的替代传输渠道。我将研究网络在工资谈判中的作用，作为工人外部选择的决定因素，以及作为对抗失业发生率的社会风险分担机制，以解释网络对工资和流失率影响的差异。为了解决这些问题，我将采用一种结构性的方法来识别和量化这种关系背后的经济机制。在理论部分，我将制定三个模型，将网络整合到一个有向搜索框架中，包括工资重新谈判和对匹配质量的学习。使用来自英国和德国的个人水平数据，我将使用先进的定量方法对这些模型的预测进行实证检验。该项目将有助于搜索模型中社交网络的理论文献，以及使用大型个人层面数据集评估它们的实证文献。从政策的角度来看，这个项目将有助于为职业介绍所设计方案，以填补那些难以获得工作推荐的人的信息缺口。

Individuals often rely on their informal personal contacts - social networks - to findemployment or improve their labour market prospects. The general direction of thetheoretical literature predicts a positive effect of networks on the quality of the matchbetween workers and firms, and thus wages and turnover, because they reduce informationand search frictions. However, the empirical literature gives mixed and heterogenous results.My objective is to explore alternative channels of transmission from networks to matchquality. I will study the role of networks in wage bargaining as a determinant of the worker'soutside option, and as a social risk sharing mechanism against the incidence ofunemployment, to explain the differentials of the effect of networks on wages and turnoverby skill level. To address these issues, I will follow a structural approach to identify andquantify the economic mechanisms behind the relationship. For the theoretical part, I willformulate three models incorporating networks into a directed search framework, thatincludes wage renegotiation and learning about match quality. Using individual level datafrom the UK and Germany, I will empirically test the predictions of these models usingadvanced quantitative methods. This project will contribute to the strand of theoreticalliterature on social networks in search models, and the empirical literature that evaluatesthem using large individual level datasets. From a policy point of view, this project will beuseful when designing programs for employment agencies to fill the information gap forthose who have less access to job referrals.