التحليل البيزي لنماذج الانحدار الخاصة بالبيانات المزدوجة (panel data) == Bayesian Analysis For Regression Panel Data Models
Author name:
باسم شليبه مسلم عباس القيسي
Supervisor name:
اموري هادي كاظم الحسناوي
General topic:
Administration and Economics
Specific topic:
Statistics
Degree:
Doctorate
University:
University of Baghdad - Faculty Of Administration And Economics - Department Of Statistics
Language:
Arabic
University location:
Baghdad
First pages:
07T3475 - p.pdf
Abstract:
تعد البيانات الاحصائية ضرورية عند دراسة اغلب ظواهر المجتمع ومنها الظواهر الاقتصادية والاجتماعية والنفسية الخ كون تحليل تللك البيانات باستخدام الاساليب الاحصائية توفر للباحث او متخذ القرار حول الظاهرة المدروسة قاعدة من المعلومات الضرورية لتسهيل عملية اتخاذ | The statistic data is important to study most of phenomena as economical , social , psychological phenomena..etc. The analysis of this data via the statistical methods gives the researcher or the decision maker more information about the studied phenomenon to make the suitable decision. The data availability needs to limit a mathematic model which represents them by the researcher and to put in consideration the type of the available data. One of the these data is panel data which can be defined ( that they are repeated measurements to the studied phenomena for N from the cross section and for T from the time series ) which can be represented by one of the model ( fixed effect model or random effect model ).Most of the studies exposed estimation of the chosen model parameters by using the classical methods as GLS and FGLS methods , whereas this research touches on the Bayesian methods to estimate parameters , especial regressive model (panel data) ,depending on the priors distributions ( non informative prior dist. and conjunct prior dist. ) and to compare them with ML method to chose the best ones for estimation and choosing.After doing two practical applications in the research ,we obtained findings. ML method was the most significant for estimating the model parameters for the fixed effect model and pooling model. Bayes method which depends on non informative prior distribution , got the second grade.When using Bayes method depending on prior distribution used in the research to estimate the fixed model parameters when the cross sections number are little to get multivariate - t posterior distribution , and if it is used with random effect model we get multivariate normal after making asymptotic expansion with existing of a loss function of the weighed squired error.
