Advanced Statistics

Numbering Code G-ECON31 5A406 LJ43 Year/Term 2022 ・ First semester
Number of Credits 2 Course Type Lecture
Target Year Target Student
Language Japanese Day/Period Tue.2
Instructor name HITOMI KOUTAROU (Part-time Lecturer)
Outline and Purpose of the Course Learn the statistics necessary for studying econometrics at the graduate level.
Course Goals We aim to obtain statistical knowledge necessary for taking advanced econometrics.
Schedule and Contents 1. Measure, probability space, axiom of probability
2. Stochastic variable, distribution function, density function
3. Moment generating function, characteristic function
4. Variable conversion of random variable
5. Distribution of multiple random variables (simultaneous distribution,
marginal distribution, conditional distribution)
6. (Weak) Laws of large number
7. Central limit theorem
8. Some limit theorems
9. Estimation method (Moment method and maximum likelihood method)
10. Consistency, asymptotic normality, effectiveness
11. Test (Statistical Inference)
The concept of statistical test, Naman-Pearson's lemma (most powerful test)
12. Likelihood ratio test, Wald test, score test
13. Basics of linear algebra for econometrics
14. Classical regression model
Small sample theory of OLS under normal error
Large sample characteristics of least squares estimator
15. Answer and explanation of the exam
Evaluation Methods and Policy A weighted average of homework (30%) and final exam (70%) is your score.
Course Requirements It is desirable to have knowledge of undergraduate level statistics and econometrics.
Study outside of Class (preparation and review) I will give homework assignments that I could not cover in class so students should do my homework every time.
References, etc. 現代数理統計学, 竹村彰通, (創文社), ISBN:4-423-89508-0
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