University of Wisconsin Fall Semester 2016 Department of Economics Economics 709 Economic Statistics and Econometrics I Professor Jack Porter Social Sciences Building #6448 [email protected] Office Hours: Wednesday 9:30{11:00 and by appointment TA Yoshi Rai Social Sciences Building #7231 [email protected] Office Hours: Tuesday 2:00-4:00, and by appointment Course Description This course is an introduction to probability theory and statistical inference designed for first year economics Ph.D. students. Lectures and Sections Each week there will be two lectures of 1 1/4 hours. In addition there will be a section meeting once a week in which problems sets and other issues from lecture will be discussed. Books The textbook for the course is: Casella, G., and R. L. Berger, (2002), Statistical Inference, 2nd edition, Brooks/Cole Press. Other helpful references are: Goldberger, A., A Course in Econometrics Hogg, R., and A. Craig, Introduction to Mathematical Statistics DeGroot, M., Probability and Statistics Mood, A., F. Graybill and D. Boes, Introduction to the Theory of Statistics Lehmann, E.L., and Romano, J., Testing Statistical Hypotheses Problems Sets and Exams Problem sets will be assigned approximately weekly and will be discussed in the section meetings. Grades will be based on a midterm exam (30%), a final exam in December (50%), and the problem sets (20%). 1 Course Outline (Parenthetical chapters/sections refer to Casella and Berger) 1. Probability Theory (a) Elementary Probability Theory (1.1{1.2) (b) Conditional Probability, Independence (1.3) (c) Random Variables, Distribution Functions, Functions of Random Variables (1.4{ 1.6, 2.1) (d) Transformations and Expectations (2.1{2.3) (e) Joint and Conditional Distributions (4.1{4.7) (f) Special Distributions (3) (g) Convergence, Laws of Large Numbers, Central Limit Theorems (5.1{5.2, 5.5) 2. Statistical Inference (a) Decision Theory (CB 7.3.4, 8.3.5, 9.3.4) (b) Minimum Variance Unbiased Estimation (7.3) (c) Maximum Likelihood Estimation (7.2.2) (d) Hypothesis Testing (8) (e) Interval Estimation (9) (f) Bayesian Inference (7.2.3, 8.2.2) **Recording of the class is prohibited. **Students with Disabilities: please see me as soon as possible if you will need accommoda- tion. **Exam Regrade Policy: we will discuss this procedure following the midterm. 2 Academic Misconduct Academic integrity is critical to maintaining fair and knowledge based learning at UW Madison. Academic dishonesty is a serious violation: it undermines the bonds of trust and honesty between members of our academic community, degrades the value of your degree and defrauds those who may eventually depend upon your knowledge and integrity. Examples of academic misconduct include, but are not limited to: cheating on an ex- amination (copying from another student's paper, referring to materials on the exam other than those explicitly permitted, continuing to work on an exam after the time has expired, turning in an exam for regrading after making changes to the exam), copying the homework of someone else, submitting for credit work done by someone else, stealing examinations or course materials, tampering with the grade records or with another student's work, or know- ingly and intentionally assisting another student in any of the above. Students are reminded that online sources, including anonymous or unattributed ones like Wikipedia, still need to be cited like any other source; and copying from any source without attribution is considered plagiarism. The Dept. of Economics will deal with these offenses harshly following UWS14 proce- dures: http://students.wisc.edu/doso/docs/UWS14.pdf 1. The penalty for misconduct in most cases will be removal from the course and a failing grade. 2. The department will inform the Dean of Students as required and additional sanctions may be applied. 3. The department will keep an internal record of misconduct incidents. This information will be made available to teaching faculty writing recommendation letters. If you think you see incidents of misconduct, you should tell your instructor about them, in which case they will take appropriate action and protect your identity. You could also choose to contact our administrator Tammy Herbst-Koel [email protected]) and your iden- tity will be kept confidential. 3.