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This paper examines the importance of differences in reservation wages for the gender wage gap. Based on two waves of rich survey data for a sample of newly unemployed individuals in Germany, we perform a decomposition analysis including measures for reservation wages, detailed information on education, socio-demographics, labor market history, as well as personality traits. In order to address the potential endogeneity of reservation wages we exploit a generated instrumental variable strategy that relies on heteroscedasticity of the error terms. Our findings indicate that the gender wage gap becomes small and statistically insignificant once we control for reservation wages. Moreover, we perform a subgroup analysis that provides valuable insights about the importance of potentially unobserved characteristics that affect reservation wages and realized wages simultaneously. Reasons for differences in reservation wages could arise from productivity differences, the fact that women anticipate discrimination and different unobserved traits or preferences. [ABSTRACT FROM AUTHOR]

Purpose -- This paper aims to analyze the role of social networks on the job search choices of the unemployed. If social networks convey useful information in the job search process, individuals with larger networks should experience a higher productivity of informal search channels. This in turn affects the choice of formal search intensity and the reservation wage. The paper seeks to test these search-theoretic implications of productive social networks empirically. Design/methodology/approach -- The authors use the IZA Evaluation Dataset containing detailed information on job search behavior of recently unemployed individuals. Observing a rich array of personality traits and direct measures of the social network, the authors choose an identification approach based on observable characteristics using least squares and binary probit regression analysis. Findings -- The findings confirm theoretical expectations. Individuals with larger networks use informal search channels more often and shift from formal to informal search. In addition to that, evidence is found for a positive relationship between network size and reservation wages. Research limitations/implications - The extent to which networks are used during job search most likely also depends on the quality of the network, which cannot be observed in the data. However, as the network significantly changes the observable formal job search effort of individuals, public job search monitoring policies should take these effects into account. Originality/value -- The paper complements the previous body of literature on the role of social networks in the labor market that predominantly focuses on labor market outcomes. By highlighting the interaction between networks and job search choices the paper improves the understanding of realized labor market outcomes in the presence of networks. [ABSTRACT FROM AUTHOR]

Purpose -- This paper aims to present the IZA Evaluation Dataset, a newly created data source allowing for the evaluation of active labor market policies in Germany. Design/methodology/approach -- The paper's approach is a description of the sampling and contents of the IZA Evaluation Dataset and an outline of its research potential. Findings -- The evaluation of active labor market policies is often confronted with a lack of adequate empirical data. The IZA Evaluation Dataset may serve as a role model for the provision of such data. Research limitations/implications -- The scope of active labor market policy instruments that can be analyzed with the IZA Evaluation Dataset is mainly restricted to measures for unemployed individuals. Originality/value -- In recent years, many countries have opened their administrative databases for evaluation studies. However, information that might be relevant for economic modeling is often absent. The IZA Evaluation Dataset aims to overcome such limitations for Germany by complementing administrative data from the Federal Employment Agency with innovative survey data. [ABSTRACT FROM AUTHOR]