1 ECONOMICS 505 MATHEMATICAL ECONOMICS Spring 2015 Professor: Office: Phone: Office Hours: Jan Ondrich 426 Eggers Hall x-9052 TTh 11-12 a.m. 3:30-4 pm and by appointment. Email: [email protected] Texts: Required Carl P. Simon and Lawrence Blume. Mathematics for Economists. Norton. Reference Walter Bossert, Introduction to Mathematical Economics. Alpha Chiang and Kevin Wainwright. Fundamental Methods of Mathematical Economics. McGraw-Hill. Course Description: Economics 505 is a one-semester course in mathematical economics and is a required course for the B, S. Degree in Economics. The prerequisite for the course is ECN 301 or 311 and the knowledge of differential calculus through unconstrained optimization of functions of one variable. Students who have questions about course sequencing should meet with an economics advisor. The goal of this course is to develop the theory of optimization first with equality constraints and then with inequality constraints and to apply this theory to micro- and macroeconomics. Grading: This course is on the Syracuse University Blackboard System. Students can access the Blackboard System by typing in the following URL— http://blackboard.syr.edu and then logging in with their NetID and password. Students are responsible for checking for announcements every Thursday evening, although frequently there will be no announcements. Student grades will be determined by performance on three non-cumulative tests (25 percent for the first two and 35 percent for each test) and their class participation (15 percent). Class participation is measured by attendance and participation in classroom discussion. Attendance will be taken by roll call and roll call will be continued until this system breaks down. The alternative imposes expense on the students so it is to be hoped that the roll-call system does not break down. Students who enter the class after the start of roll call will be marked absent. 2 Students should recognize that the work as presented is not crammable. This means that there is not a book somewhere in the library that mimics the classroom presentation. Rather the classroom lectures complement the text by moving from the simple to the complex in a way that is meant to enlighten the student who attends class consistently. Students who attend class consistently (catching up on missed days by getting the class notes from a friend) and do the assignments should expect a high grade; students who attend sporadically or have incomplete notes should not expect to pass the course. Some students may need academic accommodations due to a disability. These students should discuss their needs with me at the beginning of the semester. They should be registered with the Office of Disability Services (443-4498) and have an updated accommodation letter for me. Accommodations and related support services such as exam administration must be requested 2 weeks in advance of each test. SU’s religious observances policy recognizes the diversity of faiths represented among the campus community and protects the rights of students, faculty, and staff to observe religious holy days according to their tradition. I will provide students an opportunity to make up any examination, study, or work requirements that may be missed due to a religious observance recognized by the University, provided they notify me beforehand. Content (readings from Simon and Blume presented in class notes): 1. Introduction Class Notes #1: Logic, Sets and Functions. Terry Tao: Notes on Sets. Class Notes #2: Foundations of Optimization. 2. Optimization of functions on R Pages 190-192 from Sydsaeter and Hammond, “Essential Mathematics for Economic Analysis, 4th Edition.” Class Notes #3: Limits and Derivatives. Class Notes #4: Economic Applications. 3. Optimization of functions on R n Class Notes #5: Optimization of Functions of Many Variables. Class Notes #6: Matrices and Determinants. Class Notes #7: Many Variables: Economic Applications. 3 4. Equality and inequality constraints in optimization Class Notes #8: The Lagrange Approach. Class Notes #9: Inequality Constraints.