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Graduate Programs

ECO1011H1F Mathematics and Statistics for PhD and MA Doctoral Stream Students

The first half of the course reviews materials that will be useful in econometrics and Ph.D. macroeconomics. The material covered includes: (1) matrix algebra; (2) probability theory; probability measures, integration, expectation and conditional expectation, independence, some commonly encountered distributions; (3) deterministic and stochastic dynamic programming. Estimation, testing and prediction methods are NOT covered in the Math/Stat course, but are covered in detail in ECO 2400H. The second half of the course will concentrate on optimization theory that will be necessary for microeconomic theory and macroeconomic theory. It will start with static optimization theory, and then focus on optimal control theory and dynamic programming. The stochastic counterparts of the latter techniques will only be briefly mentioned. The three basic references for the course are (1) A.K. Dixit, 1990, "Optimization in Economic Theory", second edition, Oxford University Press (in paperback); (2) N.L. Stokey, R.E. Lucas, Jr., with E.C. Prescott, 1989, "Recursive Methods in Economic Dynamics", Harvard University Press (Chapters 3, 4, 5, 6); and (3) T.J. Sargent, 1987, "Macroeconomic Theory", second edition, Academic Press (Chapters 9 and 11).

NOTE: In exceptional circumstances, a regular stream MA student may be permitted to take the Math and Stats course for PhD and MA Doctoral Stream Students, ECO1011H1F. In these particular cases, written permission from the Graduate Director (email the Associate Chair, Martin Osborne at martin.osborne@utoronto.ca to make a request for permission) is required PRIOR to starting the Math Stats course August 16, 2010.

Section L0101, Fall 2009–10

Instructors: Martin Burda, Shouyong Shi
Day/time: MTWRF 10-5
Location: WO 35
TAs: Kinda Hachem, Trevor Tombe