ECONOMICS 725 01 DATA METHODS IN ECONOMICS UNIVERSITY OF NORTH CAROLINA AT GREENSBORO FALL 2008 Instructor Prof David Ribar Office 459 Bryan Building E mail dcribar uncg edu Phone 336 334 3904 Class meetings Lecture TR 8 00 10 50 211 Bryan Bldg Office hours TR 11 a m 12 p m and by appointment Description Economics 725 is a three credit course that teaches students how to use and analyze large data sets in economics and that introduces the SAS programming language It is intended to precede ECO 726 and to give students the data tools needed to carry out guided research for that class ECO 725 explores how to manipulate data including how to read write subset and combine records how to prepare data for research purposes how to tabulate and display data how to work with descriptive and multivariate statistical output and how to address common data problems such as unit and item non response All of these methods are illustrated using the SAS programming language This course is intended to serve as a building block in applied economic training Student Learning Outcomes On completion of this course students will have learned practical procedures for working with data seen several different ways that data can be organized learned the basics of the SAS programming language and conducted descriptive economic research with a large dataset Texts There is no specific required text for the course Instead articles and write ups will be assigned as needed Procedures Students are required to attend and participate in two hour and 50 minute laboratory sessions that meet twice weekly over an eight week period Starting with the second class students are expected to complete homework and reading assignments before each meeting to prepare questions and comments about the assignments and to contribute to discussions The class will generally meet in Bryan 211 which is a computer classroom The school prohibits food and drink from the computer classrooms Students are expected to follow the classroom discussion and exercises and to refrain from other activities such as web surfing emailing and game playing during class The primary responsibilities of students in this class will be to attend and participate in class 10 percent of the grade complete weekly homework assignments 60 percent of the grade and complete one large programming assignment 30 percent of the grade The large programming assignment will be made in the sixth week of the class with the assignment being due Monday October 28 2008 Please note that assignments must be turned in when they are due Late assignments will not receive any credit unless prior arrangements have been made with the instructor In addition to these responsibilities students are expected to conform to the University s Student Code of Conduct http studentconduct uncg edu The instructor and students will also conform to the Bryan School s Faculty and Student Guidelines http www uncg edu bae faculty student guidelines sp07 pdf Research Integrity Students are expected to be familiar with and abide by the University s Academic Integrity policy see http academicintegrity uncg edu In particular students are expected to work independently on homework assignments Students may discuss general data and programming approaches among themselves However they should not discuss specifics of their programs Assistance will be available from the instructor and teaching assistant Software The primary software package for this class will be SAS SAS is installed in the UNCG computer labs SAS licenses for personal computers are available for UNCG students through ITS To begin the license process connect to https web uncg edu researchaccess secure sas sas asp Tentative schedule BASICS Aug 26 Sources of Data in Economics Students will obtain copies of the SAS software Aug 28 Introduction to the Panel Study of Income Dynamics PSID BASE SAS TOOLS Sept 2 Introduction to SAS on the PC Sept 4 Lab Homework 1 assigned Sept 9 Reading and storing data Sept 11 Preliminary discussion of ECO 726 projects Homework 2 assigned Sept 16 Creating tables and graphs Sept 18 Cleaning and manipulating data Homework 3 assigned Sept 23 Complex file and data structures Sept 25 Complex file and data structures continued Homework 4 assigned MULTIVARIATE ANALYSIS TOOLS Sept 30 An introduction to multivariate procedures Oct 2 Working with procedure output Homework 5 assigned Large programming project assigned ADVANCED TOPICS Oct 7 Missing data Oct 9 Artificial data Homework 6 assigned Oct 14 Macros Oct 16 Other data handling procedures Oct 28 Large programming assignment due