Welcome to the homepage for ECON384, Math for Economists. Below you will find links to all class lectures, as well as some relevant links I have or pulled together from the internet. If you have anything you think would be worth adding, please let me know. You can find me in my office on: Monday 11:45am-2:15pm and Wednesday 11:45-2:15pm. Office hours are occasionally rescheduled due to conflicts. Please try to make an appointment before coming by.

Note on textbook: This semester we are using Pemberton & Rau’s “Mathematics for Economists.” You can get a discount for this book, by first registering for the CORE Team Econ textbook which we will also use. The CORE book is free, but you have to register to get the deal. After registering, you can get the discounted copy of P&R at for $35. Links to relevant sections are provided throughout. While it might be confusing, I am doing this in an effort to minimize costs to you. The CORE book will be used to reintroduce you to the intro concepts that are a prerequisite for this course (and often forgotten).

Syllabus

Mathematica Download and Help

Exercise & Problem Solutions for Pemberton & Rau

Pemberton & Rau 3rd Edition Exercise Solutions, and 4th Edition Exercise Solutions Pemberton & Rau 3rd Edition Problem Solutions, and 4th Edition Problem Solutions

Sections

Section 1: Linear equations: slope/intercept, solving systems of equations, inequalities

Reading:

  • Pemberton & Rau: Chapter 1 & 2
  • CORE Unit 8. With the CORE readings, you might have to go backwards to read more and understand a model.

Lecture:

Leibniz - CORE supplements showing economics & math working together


Section 2: Sets and functions, quadratics and logs, series.

Reading:

  • Pemberton & Rau: Chapter 3, 4, & 5
  • CORE 3.6
  • CORE 11.8

Lecture:

Leibniz


Section 3: Differentiation: first, second, product, quotient rules.

Reading:

Lecture:

Leibniz


Section 4: Optimization, exponential and log functions.

Reading:

Lecture:

Leibniz


Section 5: Matrix algebra

Reading:

  • Pemberton & Rau: Chapters 11, 12, & 13

Lecture:

Supplements: OLS in Matrix form


Section 6: Functions of several variables, differentiation, chain rule, partial derivatives, Hessians, constrained optimization

Reading:

  • Pemberton & Rau: Chapters 14, 15, 16 & 17
  • CORE 3.7
  • CORE 4.4
  • CORE 8.6

Lecture:

Leibniz


Section 7: Basic integration and applications to statistics

Reading:

  • Pemberton & Rau: Chapters 19 & 20
  • CORE 8.5

Lecture:

Leibniz


Software Downloads

Mathematica

Mathematica is software that is used for a wide variety of mathematical and economic purposes including running simulations, solving linear algebra problems, performing regression analysis, building models, to name only a few. Mathematica is incredibly powerful, and will help you to check through taking derivations, solving integrals, examining non-linear problems, and graphically displaying your work. We will only begin to touch on what Mathematica can do.

You can download Mathematica for free at http://www.jmu.edu/computing/download/.

Required Readings

Mathematica Solutions to Economics Site

Hands on Start to Mathematica

R (just “R”)

R is free software used for statistical computing and graphics. While SAS is very powerful software for running prepackaged econometric estimations, R can perform many advanced features that you cannot easily do in SAS. To be fair, SAS is probably able to do almost everything we are going to do with R, but as an experienced user of SAS I can tell you that it can be like trying to hammer a nail with a screwdriver to do the same work in SAS that you can do in R. We are only going to scratch the surface of what you can do with R, but I hope that you are able to apply what you learn here beyond this course. R is open-source software, meaning it is free for you to use for almost any purpose (except redistribution in many cases) and on any platform (Mac, PC, Linux). For those considering graduate work in economics or another mathematically inclined field, you will be able to use R without the restriction of having to pay for it. SAS is very expensive, and is not provided by many employers. The primary benefit of R is the community of open-source programmers who help expand the software. We will use R to experiment with algorithms, matrix manipulation, and Monte Carlo simulation.

Required Readings

An Introduction to R.