As a result of the modernization and development of societies from past to present, the place of women in society and business life is increasing day by day. Now, women take a more active role in society and are employed, take a place more in academia, work more in the fields of senior and mid-level management by breaking down the understanding that managers should be men before in business life. However, it has been wondered whether women's senior and mid-level management leads to more innovative thinking or innovation, or increases the entrepreneurship. The reason for this is that women have a different thinking system than men. In addition, scientific studies reveal that the male and female brain structures and neural connections in the brain are different. The aim of this study is to investigate whether there is a relationship between the number of women in senior and mid-level management and innovation and entrepreneurship activities due to these differences between women and men. In this study, panel causality relationships between variables in the OECD countries with data were investigated by taking into consideration the female employment rate and entrepreneurship and innovation index in senior and mid-level management of 2000-2017. In the study, Kónya (2006) causality analysis which is a bootstrap causality analysis, was used as panel causality analysis. According to the results of the study, in some countries, the presence of women in senior and mid-level management has a relationship with innovation and entrepreneurship, but not in some countries. Starting from this point of view, in order to ensure that a different perspective exists in the business world, increasing female employment and increasing the number of senior and mid-level female managers in addition to increasing the policies and campaigns encouraging this can be presented as a policy proposal to be drawn from this study.
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Author Name: Yagmur Akarsu, Serdar Kurt, Nur Dilbaz Alacahan
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Keywords: women's employment, entrepreneurship, innovation, panel causality analysis