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الرئيسية > Statistical Analysis of Intern...>الوصف

Statistical Analysis of Internal Migration in Egypt Using Markov Chains

المصدر: مجلة التجارة والتمويل
الناشر: جامعة طنطا - كلية التجارة
المؤلف الرئيسي: Antar, Asmaa (Author)
مؤلفين آخرين: Elgohary, Mervat M. (Co-Author) , Abd Elghany, Amira (Co-Author)
المجلد/العدد: ع1
محكمة: نعم
الدولة: مصر
التاريخ الميلادي: 2024
الشهر: مارس
الصفحات: 360 - 379
ISSN: 1110-4716
رقم MD: 1479684
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: EcoLink
مواضيع:
التحليلات الإحصائية | الهجرة الداخلية | سلاسل ماركوف | مصر
كلمات المؤلف المفتاحية:
Markov Chain | Steady State | Internal Migration | Transition Probability Matrix | The Equilibrium Matrix | Initial Probability | Stationary Probability
رابط المحتوى:
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المستخلص: This paper aims to analyze internal migration in Egypt using Markov Chain method to predict the numbers of migrants for each region of Egypt for the coming periods. This study aims to find the matrix of transition probabilities that shows the probabilities of migrants moving between the regions, and to find the mean first passage time and the mean recurrence time. The states of the Markov chain model are Cairo region, Alexandria region, Delta region, Canal region, North Upper Egypt region, Central Upper Egypt region, and Southern Upper Egypt region these states are communicated to each other and irreducible. The results of the analysis; show that the Cairo region is the only region that attracts migrants, whether male or female, while the rest of the regions are regions that expel people, and the rate of expulsion varies in each of them. Moreover, it is found that the North Upper Egypt region is the most region that expells the migrants, especially to Cairo region, and it is also the least region that retains migrants, whether male or female. We conclude from the forecasting process that the percentage of migrants, whether male or female, for the Cairo region will increase, and the percentage of migrants for the rest of the regions of the Republic will decrease.
ISSN: 1110-4716

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