Econ 160: Introduction to Statistics

Last updated: 31st of August, 2009

Introduction

This course is designed for a wide range of students, not just those with a background in economics. It is aimed at those majoring in business, those who are planning graduate work in economics, and finally those who love statistics. No matter what field you are in, though, you should be confident that by the time you leave this course, you will understand that 'the application of statistics to the study of economics,' while perhaps different from what you have seen before, is in fact feasible. Also, I believe that a basic understanding of statistics can substantially expand your job opportunities, particularly if you're planning to graduate and enter the job market in the relatively near future. To illustrate the essentials of what we will be doing throughout the course, consider that most statistics are constructed by just taking averages of numbers! Actually, this is something you all already do, whenever you add up your exam and assignment grades in a course, and come up with your total points, or average points, for example. This is all we're going to do in this course, but we're going to learn how to do it well!!

“I shall never believe that God plays dice with the world”

Albert Einstein (1879-1955)

Please Note: If you have a problem with any of the “PDF” files on this homepage, save them to your disk (right click on the link, then select “save file as”) and view them (and print them) using Adobe Reader.

Course Syllabus

Economics 160 Course Syllabus, Fall 2009. PDF Version.

Tentative Dates Of Interest

Assignments

All assignments are due back at the beginning of class.

Project: Data Selection Due 8th of September

Assignment 2 Due back 15th of September

Assignment 3 Due back 2nd of October

Assignment 4 Due back 13th of October

Datasets that can be used for Assignments/Project

Economic Datasets that can be used for a project.

Economic Time Series Datasets

NBER Datasets

Datasets sorted by topics, statistical methods, etc. A good place to start.

A site that leads to sites with Datasets The most comprehensive site (it includes links to some of the sites above).

Final Project

The final project is due in class on the 4th of December. The project should be typed, and at least 10 pages in length. Please do not include computer printouts, programs, log files, etc. Rather, summarize your findings in prose, with simple equations, and relevant statistical analysis.

I would like each person to complete a econometric and statistical analysis of an dataset which you have constructed, or which you have chosen from among the various data series that you find in links on this website. In order to complete the project, each project is expected to draw on (1) computational tools learned in this class; (2) basic econometrics and statistics learned in this class, (3) your knowledge of the basic theory and models that you are testing, be it an economic, business, finance, psychology, etc., theory.

The basis of any statistical project is one or more questions which are relevant to your particular dataset. Mention why the issue(s) you've raised is relevant, in the context of, for example, government policy, social welfare, assessing the rationality of economic agents, constructing "good" forecasting models, etc. If it's not obvious what you'd like to do, you may want to pick up a basic macro text, say, and look for simple theories which link two or more economic variables together. However, for the project it suffices to pick a group of variables and simply give me an intuitive explanation of why you might expect the variables to be related in a regression context. Alternatively, you may want to consider constructing competing forecasting models and comparing them. (Note: Unless you are developing a Forecasting Model, avoid data series that involve time (Time Series), instead select data that relates to one point in time but varies over countries, individuals, etc. The reason being that data that has a dynamic component are difficult to analyse (this type of data analysis is the subject matter of Econ 273, Economic Forecasting). On the other hand, if you do choose to simply posit the relationship between some group of variables, remember to pay close attention to explaining your expectations concerning the signs of the coefficients in your regression model, etc.

The individual parts of your project will be incorporated into assignments and completed over the semester (so that by the end of the semester all that you should have to do is combine each of the parts into one project, this obviously depends on the grade that you get for each part Ð if you get a poor grade on any of the parts you will be asked to redo that part). The individual parts can be summarized as: Select A Dataset (this part is the crucial part, when you select a dataset you should have in mind some questions about the relationship between the individual variables in your dataset), Perform a Univariate Analysis, Perform a Multivariate Analysis (this will be broken into two parts in the assignments)), and Evaluate the Multivariate Analysis.

When combining each of the individual components into a complete project, I would like you to discuss your approach to answering these questions given your particular dataset. In particular, discuss your expectations concerning estimated economic relationships, signs of coefficients, slopes of graphs, evolution of your series across individual, etc.

Finally, report to me your "best" findings in the form of a project, being careful to discuss why you think those findings are "best."

Please don't hesitate to contact myself or your TA if you have any questions.

Datasets that can be used for Assignments/Project

Economic Datasets that can be used for a project.
NBER Datasets
Datasets sorted by topics, statistical methods, etc. A good place to start.
Datasets from UCLA researchers
Links to sites with medical data
A site that leads to sites with Datasets The most comprehensive site (it includes links to some of the sites above).

Course Grades

Changes to the Regular Class Schedule

Software and Software Guides
Simple software guides that I wrote while teaching advanced econometrics at PennState University and the University of Virginia.
If you are going to use these I suggest learning each program in the order given below. Learning the basics of the programs should take no more than half an hour for each.
An overview of programming using Eviews and Matlab as a starting point: Guide to Programs

EVIEWS (Econometric Views): (Old) Eviews Guide
University of Berlin Eviews Guide
MATLAB: MATLAB Guide ,
1. A sample MATLAB program - Basic Commands (Note: Right click on this link, then select "save as"), and the (Mon1.dat) dataset to go with the sample.
2. Another guide

Easyreg: Free Download and Easyreg Guide
Gauss: Gauss Guide and Sample Program

SAS: SAS Guide and a sample SAS program (Note: Right click on this link, then select "save as")

Additional Sas Commands

An excellent site for beginners
SAS homepage

Datasets On The Internet

An invaluable guide to all things economic
Links to a HUGE number of data sources (from the site above)
Economic Datasets that can be used for a project.