Statistics and Econometrics Mid-Term – Bank Loan Default I. Introduction The question requires us to understand what factors could lead to people defaulting on their loans. The variables that will be discussed include age, education, employment, address, income etc. An overview of the data will be provided along with assessing inter-relationships among variables as well as providing a good fit model. II. Overview of Data The sample includes 700 observations in the data set based on
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ECONOMETRIC ANALYSIS. INDEX: - Introduction..................................................................................3 -Background....................................................................................8 -Empirical Analysis.........................................................................9 -Conclusion.....................................................................................31 -Bibliography.............................................................
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Question 1: Conceptual Question (a) Model I: The major econometric issue is on the error term ui. The equation ui2=γ1+γ2x1,j indicates that the error term ui is related with the independent variable x1. Under the general assumptions, the error term us designed to capture ‘unexpected’ events, as such the error term should be random and the independent variable x1 is not random which means that its value if known. Therefore, model I breaks out this assumption, the error term ui is related
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上海大学 20 4 ～ 2015 学年 秋季学期研究生课程考试 课程名称： Econometrics 论文题目（Title）: 研究生姓名(Name): Hoang Thi Lan Huong 学号(ID): 14760006 研究生班级： 留学生班 成 绩: 任课教师: 叶明确 评阅日期: 1. Introduction (Background and Purpose) The data use for this paper was constructed in the following way. The data are drawn from the OPE Campus Safety and Security Statistics website database to which crime statistics (as of the 2010 data collection) are submitted annually, via a web-based
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Applied Health Econometrics Lecture 5 Recap • What is the problem with using OLS in the binary model se>ng? • How can Whites corrected standard errors help in this situa@on? • What is the main difference between logit and probit binary models? • How can we choose between logit
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Econ 9720: Econometrics II GSU Department of Economics, Spring 2016 Practice Midterm Questions (No Solution will be Provided) 1. Suppose the data generating process (the true relationship) is y = Xβ + ε, where E[ε|X] = 0, E[εε |X] = σ 2 I n ; and X includes an intercept term. You do not observe the data set Z = [y X]. Instead you observe 150 15 50 Z Z = 15 25 0 50 0 100 2 Compute the least squares estimators β, s2 , R2 and RAdj (the adjusted R2 ). Is there anything to be gained
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The yields of crops in per hectare are low in Bangladesh compare to other countries. The farm prices of produces also low which turn in low income from farm and low purchasing power and low access to food. On the other hand, raising food price is a major concerning issue for the government of Bangladesh. For the stable food price and food, security government has adopted various strategies such as efforts to increase production, intervention in markets, public distribution, direct sales, increase
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¼ ¹Ì ×Ø ÓÖ × Ò ¬ Ò ¼ ¼ ´Ì½ µ ´Ì¾ µ ´ µ ̾ ½´ ½ ½µ ´Ì½ Î Í µ Í Ì ¼ ¾ µ ¿ ½ ¾ ´Ñµ ´ ʬ Ö µ Ñ µ ½ µ Ê Ì Ì ÐÒ Ä Í Ò µ Ò Ö Ö ×× ÓÒ ´Ñ ¼ ÓÒÓÑ ØÖ × Ó ´Ê ¬ Ö µ Ê ´ µ ½Ê ´Ò ´ËË Ê ËË Í µ Ñ ËË Í ´Ò µ ¹Ì ×Ø ÓÖ Ð Ò Ö Ö ×ØÖ Ø ÓÒ× ÓÖÑÙÐ ÖÝ ÓÖ µ Ì ×Ø× ½º ¾º ´ËË Ê ËË Í µ ´ ËË Í ´Ò µ ʾ ´ ½µ ´½ ʾ µ ´Ò µ ½ ¾ ÓÛ¹Ì
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Econ 573: Homework #1 Solution Key Question I The file CEOSAL2.wfl contains data on 177 chief executive officers. The variables are defined as follows: 1. salary – 1990 compensation, $1000s 2. age – in years 3. college – =1 if attended college, 0 otherwise 4. grad – =1 if attended graduate school, 0 otherwise 5. comten – years with company 6. ceoten – years as CEO with company 7. sales – 1990 firm sales, millions 8. profits – 1990 profits, millions 9. mktval – market value, end 1990, mills. 10. lsalary
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Mid-Term – Bank Loan Default I. Introduction The question requires us to understand what factors could lead to people defaulting on their loans. The variables that will be discussed include age, education, employment, address, income etc. An overview of the data will be provided along with assessing inter-relationships among variables as well as providing a good fit model. II. Overview of Data The sample includes 700 observations in the data set based on the summary. Below is the list of
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