Intro to Mathematical Economics
Instructor |
Teaching Assistant |
---|---|
Professor Alan G. Isaac |
Linh Khuat |
Office: Zoom (via Canvas) |
Office: Kreeger G02 (or Zoom by appt) |
Office Hours: M9-12; by appointment |
Hours: T 2:00-3:00; by appointment |
Email: aisaac@american.edu |
Email: lk3393a@american.edu |
Econ 405/605 Overview
Learning Outcomes
This course introduces core mathematical methods used by economists. These are foundational for any advanced study in economics. Students who master the material will be able to understand and solve problems related to:
sets and methods of proof in economic theory.
functions and equation in economic modeling.
composition of functions.
some very basic statistics.
matrix algebra for linear economic models.
linear comparative statics (predictions of economic models).
differential calculus (marginal analysis at multiple margins).
nonlinear comparative statics (micro and macro applications).
multivariate optimization (profit maximization; optimal constrained choice).
computer applications of mathematical methods to economic analysis.
Course Prerequisites
A college-level calculus course is prerequisite to this course. I assume you remember basic differential calculus from the first semester and a little bit about integration. Ideally you also recall some statistics and matrix algebra, but we will develop these topics when needed.
Course Policies
Communication
This class will use Canvas. Look there for the syllabus, lecture supplements, and assignments. Canvas announcements are sent by email; students must monitor these announcements and Canvas Conversations (Inbox). Students should also subscribe to the Canvas Discussions. In any online discussion, be sure to adhere to basic etiquette: be respectful, and quote appropriately.
Classroom Policies (IRW)
The following policies apply to in-person meetings only.
- Masks:
Be sure to follow the AU mask guidelines. These are updated on a regular basis, in response to local conditions. Use a high-quality mask (e.g., KN95). Surgical masks are not adequate. When wearing a mask, ensure that it fits correctly. The mask must be snug over both the nose and mouth.
- Connected devices:
As a courtesy to other students, do not browse the web or check your email during class. Such activities distract others and reduce your ability to contribute to discussions. In addition, there is evidence that students believe themselves capable of productive multitasking but in fact are not (May and Elder, 2018).
- Cell phones:
Please silence your phone before entering the classroom. (E.g., put it on vibrate, or turn it off.) Place it out of sight in a pocket or bag (and not on your desk). If you need to make or take a call, you may quietly leave the classroom. (Please sit near the door if you anticipate such a need.)
- Computers:
You may use a computer to take notes or do other course-relevant activity. However, be aware that research indicates that using a computer to take notes can hinder learning (Sana, Weston, Cepeda 2013). This appears to be due to the distraction of multitasking.
Software
This course requires the use of Mathematica, both in the classroom and for homework assignments. There is a free Mathematica tutorial, which you should complete on your own during the first week of class. Homework assignments must be typed into a Mathematica notebook and then submitted on Canvas in PDF format. Software crashes or disk crashes are not an excuse for late submission: turn on autosave and additionally use an external backup such as GoogleDrive for Desktop or OneDrive.
Assessment and Grading
Assessment
I assess student mastery of the learning outcomes (see above) by means of graded exams, graded homeworks, and ungraded class participation.
Class Participation
Class participation is ungraded, but it is expected and attendance is graded. Class participation includes both in-class participation and asynchronous participation in online discussion. Both are used for ongoing assessment of student mastery of this course's learning outcomes (listed above). I use your in-class participation to provide immediate feedback, with the goal of enhancing mastery of student learning outcomes. So be sure to ask questions!
Exams
Exams are graded, and no collaboration is allowed on exams. Exams presume a thorough knowledge of the homework problems. During exams, you will not have access to your textbook, the internet, or a computer.
In this course, I offer no makeup exams. (If you miss an exam due to unavoidable contingencies, such as illness or family emergencies, please obtain an excused absence from the Dean of Students. Your grade will then be calculated from the remaining exams.) There is no “extra credit”.
MIDTERM EXAMINATION: see our Canvas Assignments page.
FINAL EXAMINATION: always check the final exam schedule for the date of our final examination. (The official final exam schedule always determines the date and time of the final.)
Homework
Homework assignments must be submitted on time via Canvas. Computer problems are not an excuse for late submission: be sure to use autosave and to back up to the cloud.
The TA for this course grades the homework. You may request supplementary comments from the TA, but do not request grade changes. The TA is not authorized to make grade changes. If you wish to contest a homework grade, you may submit your homework to me for regrading of the entire assignment. Be aware that I instruct my TA to be quite generous in grading, and regrading may produce a score reduction.
Homework assignments may include problems designated as optional. These are not collected or graded, but they can help you practice for subsequent classes and exams.
At the top of each assignment, include your name, a course identifier, and the assignment number. Ongoing study groups are highly recommended. Study groups are an excellent means of mastering the course material. They are also a core part of the experience of graduate education. Besides, they are fun.
You will produce your homework as Mathematica notebook (.nb) files. However, your homework submission must be a PDF file. To submit, first save the notebook, and then save it again in PDF format. Finally, upload the PDF file on Canvas.
Grading
Homework and exams are graded. Your final grade is based on your total weighted points earned. (See below.) There is no "extra credit". The numerical cut-off points for grades are standard, e.g., 90% for A-range grades and 80% for B-range grades. (Cutoffs are sharp; grades are not rounded upwards.) It follows that in principle everyone can attain an A, if every student makes an exceptional effort.
If numeric scores are unusually low in an otherwise attentive class, I curve the grades. Specifically, if fewer than 15% of the class reaches the 90% cutoff, I will lower all cutoffs proportionally until at least 15% of the grades are A or A-.
Points
Points are earned as follows:
attendance (5 percent of points possible),
homework (25 percent of points possible),
midterm exam (30 percent of points possible),
cumulative final exam (40 percent of points possible).
Topics and Readings
This course draws fairly directly on several chapters of [Hoy.etal-2022-MITPress]. I strongly recommend acquiring this textbook, but the library should also have one copy for Reserve Reading. You will also need to learn a bit of the Wolfram Language for your homework assignments. Accordingly, the following books should prove especially helpful for this course.
- Mathematics for Economists
- An Elementary Introduction to the Wolfram Language
[Wolfram-2024-WolframMedia] (free at https://www.wolfram.com/language/elementary-introduction/3rd-ed/)
In addition, I have requested that some additional texts be put on reserve in the University Library. (Find a list on the syllabus supplement. I occasionally require small amounts of reading from a few of these texts.
The suggested timing of topics and the extent of coverage is tentative and may be revised as the semester progresses. The number of classes designated below for each topic is intended only as a rough guide: class interest and preparation will determine how quickly we progress through the topics. New readings may be added to the readings during the course. Readings listed as recommended are entirely optional.
Logic and Proofs
Week 0 (read independently)
Review this material on your own. It will not be covered in class.
- Informal Logic and Proof Strategies
[Fuchs-2023-CambridgeUP] ch. 3 (on reserve)
Exponents and Logarithms
Week 0 (read independently)
Review this material on your own. It will not be covered in class.
- Functional Forms
[Hoy.etal-2022-MITPress] ch. 2.4.
Review of Functions
Week 1-2
- Sets, Numbers, and Functions
[Hoy.etal-2022-MITPress] ch. 2. (Skip pages 48--50. Emphasize mastering section 2.4.)
There are additional optional readings for this review of functions and this review of sets.
Counting and Probability
Week 3-4
- Elementary Combinatorics
[Fuchs-2023-CambridgeUP] ch. 8 (on reserve)
Strongly Recommended:
- Combinatorics
[Grinstead.Snell-2003-AMS] ch.3 https://open.umn.edu/opentextbooks/textbooks/21
- Basic Probability Theory,
[Hansen-2022a-PrincetonUP] Chapter 1
Sequences
Week 5–7
- Sequences, Series, and Limits
[Hoy.etal-2022-MITPress] ch. 3
Recommended:
- Convergent Sequences
- Fixed Points
Midterm (approximately here)
Week 8
Continuity (Univariate Functions)
Week 9
- Continuity of Functions
[Hoy.etal-2022-MITPress] ch. 4
Recommended:
- Limits and Continuity
[Fuchs-2023-CambridgeUP] ch. 9 (on reserve)
Derivatives and Differentials (Univariate)
Week 9
- Univariate Derivatives, Differentials, Taylor Series
[Hoy.etal-2022-MITPress] ch. 5
Recommended:
- Taylor Series
Optimization (Univariate)
Week 9-10
- Univariate Optimization
[Hoy.etal-2022-MITPress] ch. 6
Elementary Equation Operations
Week 10-11
- Linear Equations and Vector Spaces
[Hoy.etal-2022-MITPress] ch. 7
- Matrices
[Hoy.etal-2022-MITPress] ch. 8
Recommended:
- Preview of Linear Algebra
[Fuchs-2023-CambridgeUP] ch. 11 (on reserve)
- Linear Algebra
[Torrence.Torrence-2019-CambridgeUP] ch. 7.1, 7.3, 7.4, 7.6 illustrates the use of matrices in the Wolfram Language.
- Applied Discrete Structures
[Doerr.Levasseur-2021-Lulu] ch. 5 provides a brief elementary introduction to matrices.
The Comparative Statics of Linear Models
Week 11
- Determinants and Inverses
[Hoy.etal-2022-MITPress] ch. 9
Multivariate Calculus and Nonlinear Comparative Statics
Week 12
- Multivariate Calculus
[Hoy.etal-2022-MITPress] ch. 11
- Comparative Statics
[Hoy.etal-2022-MITPress] ch. 14.1, 14.2
We may not have time to discuss chapter 14.
Quadratic Forms and Eigensystems
Week 13
- Topics in Linear Algebra
[Hoy.etal-2022-MITPress] ch. 10
We may not have time for these topics.
Multivariate Optimization
Week 14
- Multivariate Optimization
[Hoy.etal-2022-MITPress] ch. 12
- FONCs for Constrained Multivariate Optimization
[Hoy.etal-2022-MITPress] ch. 13.1
- Second-Order Conditions for Constrained Multivariate Optimization
[Hoy.etal-2022-MITPress] ch. 13.2
Optional: Advanced Reading in Multivariate Optimization
- More Constrained Multivariate Optimization
[Hoy.etal-2022-MITPress] ch. 13
- Envelope Theorem
[Hoy.etal-2022-MITPress] ch. 14.3
- Kuhn-Tucker Conditions
[Hoy.etal-2022-MITPress] ch. 15
References
Binmore, Ken. (1982) Mathematical Analaysis: A Straightforward Approach. : Cambridge University Press.
Doerr, Al, and Ken Levasseur. (2021) Applied Discrete Structures. : Lulu.
Fuchs, Shay. (2023) Introduction to Proofs and Proof Strategies. : Cambridge University Press.
Grinstead, Charles M., and J. Laurie Snell. (2003) Introduction to Probability. : American Mathematical Society. https://open.umn.edu/opentextbooks/textbooks/21
Hammack, Richard. (2018) Book of Proof. Richmond, VA: self published. https://www.people.vcu.edu/~rhammack/BookOfProof/Main.pdf
Hansen, Bruce E. (2022) Probability and Statistics for Economists. Princeton, NJ: Princeton University Press. https://www.ssc.wisc.edu/~bhansen/probability
Hoy, Michael, et al. (2022) Mathematics for Economists. Cambridge, MA: MIT Press.
Lukianoff, Greg, and Jonathan Haidt. (2018) The Coddling of the American Mind: How Good Intentions and Bad Ideas Are Setting Up a Generation for Failure. London, England: Penguin Books.
May, Kaitlyn E., and Anastasia D. Elder. (2018) Efficient, Helpful, or Distracting? A Literature Review of Media Multitasking in Relation to Academic Performance. International Journal of Educational Technology in Higher Education 15, Article 13. https://doi.org/10.1186/s41239-018-0096-z
Torrence, Bruce F., and Eve A. Torrence. (2019) The Student's Introduction to Mathematica(R): A Handbook for Precalculus, Calculus, and Linear Algebra. : Cambridge University Press.
Wolfram, Stephen. (2024) An Elementary Introduction to the Wolfram Language. Champaign, IL: Wolfram Media. https://www.wolfram.com/language/elementary-introduction/2nd-ed/
The syllabus above is Copyright © 2024 by Alan G. Isaac. Some rights are reserved. This work is licensed under the Creative Commons Attribution-ShareAlike License version 2.0 (or any subsequent version).
Required and Recommended Syllabus Sections
The following sections are required or recommended on all syllabi at American University. The language is unaltered from suggestions provided by the administration.
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