Life can only be understood
going backwards, but it must be lived going forwards. -- S.
Kierkegaard
Description
AGEC
654 is a 2-credit course focusing on dynamic problems in economics. In the area
of theory, students will become familiar with a broad range of economic models
involving time, including those cast in the calculus of variations, optimal
control theory, and dynamic programming. Students will gain familiarity with
applications of differential equations to economic problems, systems of
differential equations, and issues related to the stability of dynamic systems.
Applications will be drawn from a range of problems in microeconomics and
macroeconomics, including current topics in agricultural economics.
Click here to view the course schedule .
Objective
A wide range of dynamic problems appears in the economics literature, and a basic understanding of the techniques of dynamic optimization is necessary for both reading and contributing to this literature. Accordingly, this course has two objectives: (1) to provide students with a basic “pencil and paper” familiarity with dynamic optimization; and (2) to provide students with a basic set of research “tools” (including both approaches and software) with which to solve dynamic problems. Students will gain the necessary background to read journal articles focusing on temporal aspects of resource use and allocation in economics. Students will learn to solve discrete- and continuous-time dynamic problems by translating logical programming steps into iterative solution algorithms. By completing this course students will be able to properly identify dynamic problems, characterize their solution, and formulate practical strategies for undertaking research on dynamic economic problems. As one of the "core" courses for Ph.D. students in Agricultural Economics, an additional goal for this course is to provide students with the necessary skills to recognize the nature of dynamic problems in economics and apply solution strategies across a wide spectrum of conceptual and empirical problems.
Instructor and Office Hours
The course instructor is Prof.
Gerald Shively
656 Krannert (494-4218)
shivelyg@purdue.edu
Feel free to visit anytime. I try to respond quickly to email.
My secretary is Linda Klotz (494-4208; lrzlotz@purdue.edu )
Textbook
Great books on Economic Dynamics and Dynamic Optimization come and go, and not all are easily obtained. I don't require a book for this class. My notes are available for purchase at CopyMat in Purdue Village. These should be sufficient to get you through the course. Nevertheless, several books might be useful. These include Alpha Chiang Elements of Dynamic Optimization and Leonard, D. and Ngo Van Long, Optimal Control Theory and Static Optimization in Economics (Cambridge: Cambridge University Press, 1992). The latter book is available in paperback at a reasonable price.
Several other books may be of interest. One is by Morton Kamien and Nancy Schwartz, Dynamic Optimization (North-Holland Press 1991). This outstanding book is a classic in the field and should be considered an essential item for a professional economist’s library. Unfortunately, Kamien and Schwartz is quite expensive, and will likely appeal only to those who live according to the permanent income hypothesis. Another set of books that I recommend (but do not require) are those by the "king" of dynamic programming, Dimitri Bertsekas. Volumes I and II of Dynamic Programming and Optimal Control (Athena Press 2000) are difficult books but fairly complete and include many examples from economics. This pair of books will especially appeal to students who are planning to use dynamic programming techniques in their dissertation research. Some examples from macroeconomics will be drawn from Stephen J. Turnovsky, Methods of Macroeconomic Dynamics (MIT Press 2000).
These books are widely available new and used through many on-line bookstores including Amazon.com and Reiter's Books . Copies of these books will be made available at the reserve desk in the Krannert Library.
Grading
Grades will be based on five problem sets (30%) a written review of a published journal article (20%) and a final in-class exam (50%). I strongly encourage students to work together on assignments to maximize learning. Problem sets will be announced in class. Supplemental material, such as computer code and additional readings will be made available as the course progresses.
Computing
A number of computer packages (e.g. Maple , GAMS , Gauss , Stella ) can be used to build, solve, and/or simulate dynamic and multi-stage problems. In this course we will rely on several of these.
Special Needs
If you have a disability that requires academic adjustments, please make an appointment with me during the first week of class to discuss your needs. Please note that university policy requires all students with disabilities to be registered with Adaptive Programs in the Office of the Dean of Students before classroom accommodations can be provided.
Campus Emergencies
In the unusual event of a major campus emergency, course requirements, deadlines and grading percentages are subject to changes that may be necessitated by a revised semester calendar or other circumstances. Information about ongoing on-campus emergencies will be posted at http://www.purdue.edu. Local news is available at http://www.wlfi.com and http://www.jconline.com. Cell phone emergency text messages will be sent to those signed up for them. You can register for this university service at http://www.purdue.edu/securepurdue/. For specific information regarding changes in this course, visit this home page, contact me by email at shivelyg@purdue.edu, or call my office (494-4218).
Communication
Please note that my primary out-of-class method of communication will be via email to your Purdue email address. I will not generally attempt to contact you at email addresses other than your Purdue email address. It is your responsibility to check for mail on a regular basis. I recommend checking your Purdue email at least once every 24 hours.
Academic Integrity
University policy on academic dishonesty is clear: academic dishonesty in any form is strictly prohibited. Anyone found to be cheating or helping someone else cheat will be referred directly to the Dean of Students for disciplinary action. Penalties are severe and may include dismissal from the University. The risks associated with cheating far outweigh the perceived benefits. Academic dishonesty includes citing someone else's work as your own, using "cheat sheets" or sharing your answers with someone else. If you are unsure whether your planned action constitutes academic dishonesty, seek clarification from your instructor. Other information regarding your rights and responsibilities as a student are contained in the university's code of conduct .