نموذج إحصائى لقياس العوامل المؤثرة فى هجرة الکفاءات العلمية المصرية على التنمية الإقتصادية | ||||
| مجلة الدراسات المالية والتجارية | ||||
| Article 4, Volume 29, Issue 2, August 2019, Page 160-194 PDF (728.94 K) | ||||
| Document Type: المقالة الأصلية | ||||
| DOI: 10.21608/mosj.2019.122432 | ||||
 View on SCiNiTO | ||||
| Abstract | ||||
| The research aims to measure the factors affecting on the migration of scientific competencies abroad on The Egyptian economic growth from 1990 to 2019.Then, forecasting GDP as an indicator of economic development as a result of the impact of these factors from 2020 to 2030. The Research used ordinary least squares (OLS) model, robust regression (RR), Partial Least Squares (PLS) model and the hybrid model between robust regression and partial least squares . After that it was compared between them in terms of explanatory and predictive ability. The results found that the best model for forecasting of gross domestic product (GDP it) is robust partial least squares (RPLS) model, where its explanatory and predictive ability is higher than other models. It was found that the most important factors affecting of gross domestic product (GDP it) is the Migration of Scientific Competence Index (MSC it) and it is measured by the total number of immigrants from higher university and university education to the total number of graduates, the unemployment rate (UNEMP it),The size of the employees (EMP it), the Human Capital Index (HC it), the rate of expenditure on Research and Development (ERD it), the number of researchers working in research and development (RRD it), the proportion of public spending on education as a proportion of national income (ES it). | ||||
| Keywords | ||||
| Migration of scientific competencies; Economic development; Multicollinearity; Outliers; Ordinary least squares model; Robust regression model; Partial least squares model; Robust partial least squares model; Time series | ||||
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