Syllabus

Introduction to Numerical Analysis Software (2016 Summer)

Contents

Course Information

Lecturer: Yuan Chai

Email: chaix026@umn.edu

Office: 248E Ruttan Hall

Class schedule: Monday, August 22 through Friday, August 26, 1:00-4:00pm

Location: 220 Learning and Environmental Sciences (LES)

Objectives

This short course is designed to prepare first-year MS and PhD students in applied economics with basic numerical analysis skills using MATLAB programming language. MATLAB is a powerful software package that can accomplish a diverse range of tasks, from mathematical operations, numerical optimizations to three-dimensional imaging.

This course consists both lecture notes and hands-on practice examples. Lecture notes explain programming concepts and demonstrate the use of basic functions applicable to econometric analysis. Hands-on practice problems are designed to help students familiarize themselves with programming in MATLAB, master good programming practices and perform numerical analysis on their own. Topics covered in this course include basic operations on matrics and arrays, data input/output and visualization, user-defined functions, and implementation of economics analysis methods such as linear regression, non-linear systems, and maximum likelihood estimations.

This course mainly serves as a preparation course for APEC 8211 Econometric Analysis. The objective of this course is to help students understand the basics of MATLAB and equip students with the necessary skills for their programming needs in APEC 8211 and further graduate studies.

Participation and grades

    • There is no University credit associated with this course.

    • Exercises and assignments Students are encouraged to replicate teaching materials and practice in-class assignments on their computer in the lab. There will be one or more comprehensive exercise problems accompanying each lecture. Students are encouraged to replicate these comprehensive exercises. There will be no after-class homework. Exercises and assignments are not graded and answers will be provided.

Course outline

Mon, Aug 22 -- Lecture 01: Basics of MATLAB programming language

    • MATLAB environment: Command Window vs m-files

    • Matrices and arrays

    • Good coding practices

    • Example: m-file for a linear regression simulation

Tue, Aug 23 -- Lecture 02: Data visualization

    • Data import and export

    • 2-D plot: scatter, line and histogram

    • 3-D plot: scatter, line, mesh, surface and contour

    • Formatted output: an OLS report

Wed, Aug 24 -- Lecture 03: Decision and loop structures

    • if/else/elseif statements

    • switch statements

    • for statements

    • while statements

    • User-defined function

    • Example: user-defined OLS function

Thu, Aug 25 -- Lecture 04: Numerical methods

    • Linear algebra

    • Polynomials

    • Non-linear system of equations

    • Newton-Raphson method / Optimization

    • Optimization

Fri, Aug 26 -- Lecture 05: Applications

    • Maximum likelihood estimation (MLE)

    • Simulation: Sample size and OLS estimates

    • Extra: symbolic math toolbox

Readings

Lecture notes

MATLAB® Primer, for Version 8.6 (R2015b), MathWorks, Inc.

Frain, J.C., 2014. MATLAB for Economics and Econometrics, A Beginners Guide. TEP Working Paper No. 0414. Trinity College Dublin, Department of Economics.

Additional Readings

Attaway, S., 2012. MATLAB®-- A Practical Introduction to Programming and Problem Solving, 2nd ed. Elsevier Inc.

Brandimarte, P., 2013. Numerical methods in finance and economics: a MATLAB-based introduction. John Wiley & Sons.

Published with MATLAB® R2015b