Economic literature highlights the vital role that women can play in enhancing the economic development of nations. However, there is still gender inequality in developing countries, especially in education and labour market participation. Although women represent nearly half of the population in Egypt, their labour force participation rate is still very low compared to men. This paper's primary goal is to investigate the short and long-run associations between female labour force participation and Egypt's GDP growth rate. The study used annual time series data from 1990-2019, where the vector error correction model (VECM) was employed. The study found that female labour force participation and the gross fixed capital formation growth rate can enhance the GDP growth rate in the long run. Nevertheless, there is no statistically significant relationship in the short run. This paper's main recommendations are that the Egyptian government needs to implement policies that encourage women's labour force participation and decrease gender inequality. These policies could be changes in legislation, modernization of social norms, Job flexibility, and increasing access to childcare. Moreover, they need to focus on both the demand and supply sides of the quality of female labour force participation by matching the women’s education with the creation of suitable jobs.

 

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War consistently imposes significant challenges to the functioning and advancement of higher education. To identify the key trends in the development of tertiary education in Ukraine during 2014-2021 amid the war, the synthetic control method (SCM) was employed. The outcome variable for assessing tertiary education development is the gross enrolment ratio of the relevant age group. The broadest set of predictors influencing the dependent variable, for which statistical data is available on the World Bank website, consists of eighteen indicators. Through statistical and expert analysis, sixteen countries were selected for inclusion in the control group. The pre-war period was defined as 2000-2013, with 2014 marking the war’s onset, and 2015-2021 representing the war years. In the first stage, a synthetic model is constructed using the broadest possible dataset. In the second stage, the model’s sensitivity is analyzed, leading to the reduction of predictors to thirteen and the control group to ten countries. Consequently, the adequate synthetic model for the development of tertiary education in Ukraine from 2014 to 2021 was established. A placebo test confirmed that the observed gap between actual and synthetic values for tertiary education in Ukraine is not coincidental. The SCM analysis revealed that, without the war, a decline in demand in tertiary education would have been predicted for the 2014-2021 period. The observed gap underscores the significant impact of the war on Ukraine’s higher education system, providing valuable insights for shaping policy initiatives aimed at advancing tertiary education in the post-war era. Read more