Economics 201
Economic
Professor Lawlor
Syllabus (Spring, 2008)
1. About this course
Economics 201 is a required course for economics majors and has Economics 150, Introductory Economics, as its prerequisite.
The purpose of this course is to provide students with basic skills relating to finding, downloading, displaying, graphing and analysis of economic data. The course presumes no prior computer skill; we will provide instruction in all the software that we use. The software we will cover and use will be: Excel, and GRETL, an econometrics package written by Professor Cottrell that you can download to your computer (downloading site and instructions listed on the course webpage).
All other readings can be downloaded from the course website, or will be handed out in class.
Economics at its best is a discipline that attempts to explain the reality of the multitude of social behaviors which constitute the subjects of micro- and macroeconomics. Economists interact with this reality in many ways, including the study and development of theoretical models, the study of history, politics and current events relating to economic behavior and institutions, and the analysis of economic data. This course is focused on this last aspect.
Data may be of interest to economists at three levels. First data may provide initial background information about phenomena under study – the health insurance market or the level of consumer spending in the economy as a whole, for example. From such knowledge (and more casual observation as well as personal intuition, experience and prior knowledge of past economic analysis), the interrelations between various concepts or behaviors will suggest themselves. This is the first stage of theory construction. Theory construction, though more or less constrained by such pre-theoretical knowledge, is a creative process, which proceeds in a somewhat independent fashion. During this stage, logic, mathematics and other tools are brought to bear. Economic “models” and “theory” subsequently arise. It is a mistake, reinforced by textbook learning, to think of these theories as sacrosanct and done with, once they are written down and published. Theoretical hypotheses, to be useful, need to be “tested” against the reality they purport to describe. From time to time this will result in the theory being questioned, perhaps modified or even abandoned in light of the result of such tests.
The testing of theory against data can be done in a number of ways, ranging from casual investigation of simple data all the way up to sophisticated econometric analysis (econometrics is the formal application of statistical method in economics). The basis of such testing lies in the ability to either collect or find from publicly available sources, numbers that measure the variables suggested as important in the theory. This is what we mean by economic data. Economic data are formal series of numbers that more or less perfectly measure some economic phenomenon. Such data are more often the result of observation rather than experiment, given the limits of experimentation in economics (though that experimentation is growing). Furthermore, most economists are not themselves producers of data; statistics are difficult and expensive to collect and maintain.
Thus after the first stage of gathering informal background knowledge, and the second stage of formulating concrete theoretical hypotheses from imaginative linking of economic data, the third stage in the use of economic data is to test the validity of those hypotheses against as wide a variety of actual data as can be found. Ideally, this is how economics progresses to a greater (or perhaps just evolving) understanding of the economy.
It is the first stage (data exploration) and, in a beginning way, the third stage (hypothesis testing) that will most concern us in this course. Hopefully this will prepare you to become more comfortable and familiar with data sources and the techniques of using them. Reading the economics literature for future classes should become easier after this. We also hope our class will contribute to the sophistication of future papers you write for classes in the major. Lastly, the required statistical class for all majors, Math 109, should gain greater relevance and context, in respect of its usefulness for economics, from this course.
For students with an interest in the formal aspects of theory testing the department offers Economics 215, Econometrics.
2. Grading
An essential element of your learning in this course is your faithful and timely attendance to all classes and assignments. We will be exploring software, data sets and various forms of data manipulation and display in class. If you miss class this material cannot be repeated and no easy substitutes will be found. Likewise the assignments are all very tightly scheduled and designed to give students a cumulatively increasing insight into economic data, thus missing assignments is a serious hindrance to your learning. Also, since we will be going over assignments on the day they are due, it will not be possible to turn things in late (except in medical emergencies).
Thus as a check of, and a reward for, regular attendance and reading we will be conducting regular 5 minute quizzes at the start of some class periods. Unless otherwise noted on the course schedule below, any other day is fair game to have a quiz. The fair subjects for these very brief quizzes will be the readings and focus questions assigned for that day. Quizzes missed because of absence will count as a zero. One quiz grade will be thrown out and an average grade computed at the end of the semester. Also, sometimes (as in section 4 below) there will be homework assignments that are averaged into your quiz grade.
Quizzes will be graded quickly and returned and are not expected to be detailed in either the question or the answer. In most cases the grade is 95, 85 or 50. If knowledge of the reading is obvious and the question is answered correctly, a 95 is earned. If knowledge of the reading is apparent and the question is answered incorrectly, an 85 is earned. If there are obvious problems with both the general knowledge of the reading and the answer, the quiz earns a 75. If the student shows clear evidence of not having read the reading, the quiz earns a 50. If the student is absent without a written excuse, the quiz earns a 0. Thus, note that even if you have not done the reading there is still an incentive to attend class.
Students are encouraged to save all returned quizzes for a verifiable record of your quiz average at the end of the semester.
The quiz grades are designed with three reasons in mind. One, they are designed to reward conscientious students with a sure guaranty of at least a B level (or higher) contribution to your grade from just doing the readings ahead of time and coming to class. Two, they are designed to help learn a major point or two from the day’s material. Three, they provide feedback on a daily basis to the instructor on how the class is doing in digesting the material. Overall, these points should be nothing but beneficial to students. Only students that don’t treat the course seriously will find that the quizzes are a penalty. They should be a gift for the conscientious student.
This quiz grade will be worth 10% of your grade. In addition we will make a more subjective evaluation of your efforts to prepare for and to participate in class discussions; this is also worth 10%. This latter participation grade usually follows your quiz grade very closely. When it diverges, it is usually due to a student missing class excessively or not participating at all.
There will also be two data assignments (one due on February 14, and the other the first day of finals week, March 7), worth 40% each. Thus the total grading scheme is:
Quiz grade: 10%
Participation: 10%
Data project
Data project
3. The Data Projects
The two data
projects will focus on economic applications of publicly available data and will
give students a chance to practice software skills, the analysis and display of
data and the presentation of the results in a final report. Both assignments
are detailed and should be followed precisely. The final reports when turned in
will include specific tables, graphs and answers to specific questions about
the area under study. Students try to make this final hard copy presentation as
clear, neat and presentable as possible. All work should be done alone for
maximum learning potential. The first data project will deal with
cross-sectional data on the health systems of the OECD countries. The second
concerns macro data from the
4. Required Text, Website and
There is no textbook for the course. All of the readings and other assignments and all of the data for the projects will be available on the course website. Students should familiarize themselves with this website: http://ricardo.ecn.wfu.edu/~lawlor/ecn201/
Most of the other readings and assignments are found in the course schedule below, linked to our class website or in the "docs" directory of the website. Students should print the articles out and bring them to class on the dates indicated. (Regular consultation with the web site is encouraged as more things are often added to the linked documents as the course develops.)
5. Contact Information
Michael Lawlor, Office Hours: T and Th.:
3-4 and by appointment. (You are free to drop by any other times, but might
call ahead first.)
Office: 108 Carswell
Contact: 758-5564,
6. Course Schedule
Introduction, Housekeeping, (#1, January 22)
Go over syllabus, having mailed it to students for prior reading.
In class reading and quiz: What are Data?
1. Introduction to the Philosophy of Science and the Theory of Data Analysis (#2, Jan. 24)
Topics covered: The nature of empirical science, the problem of induction, deductive testing of theories, demarcation of science, “verifiability" and “falsifiability” of theories, scientific objectivity.
Come to class having read the Popper article and prepared answers to the focus questions. Both of these can be found at the website.
For students unclear about the references in Popper to Hume and induction, here is a short (2 page excerpt from Hume.) This is also available on the website
3. Exploring Cross Sectional Data: The Comparative Health and Health Spending of Nations (# 3, January 29-31, February 7-February 14)
Topics Covered: Assembling cross sectional data series, the OECD Health Database, means, bar graphs, line graphs, scatter plots, regression lines, interpretation of data, the relationships of health spending to GDP and of health spending and health workforce to health status.
BRING COMPUTERS TO CLASS
First two Days of this section (Jan. 29, 31, No Quizzes given these days): Exploring The OECD Health Database and setting up Gretl on your computer.
Preparation for Class: Install GRETL software package on computers. Downloading instructions available on the website.
Interim
Day (#5, February 5): Required Meeting, Attendance Taken. Library Resources and Databases. Meet in Library 476. Session taught by Ms. Mary Scanlon,
Reference Librarian.)
Third
and Fourth Day of Section (#6 & #7, February 7 and 12): A Wider Interpretation of Health Spending in the OECD
Countries.
Print the article and bring your copy to class so we can look at the data tables together.
(#8, February14: NO CLASS Turn in Project 1. I
will accept projects as on time if turned in by 5PM on February 15. After that
the grade declines by one letter each day it is late. No exceptions without
letter from an M.D.)
4. Variance in Data: How to Measure It, Use It, and Display It (#9 & #10, February 19,21)
Topics Covered. Hypothesis testing, variance, the area under the standard normal curve, differences in means, t-statistics and the use of Excel spreadsheets.
First Day of Section (# 9, February 19):
The Basics of Variance
Preparation for class:
i. Read the assignment and bring it to class
ii. Print out the document, "Analysis of Variance Homework," which will be due February 26. The material needed to complete this homework includes the reading assignment on cholesterol (above), today's discussion of it, your computer Excel program and a document we have created, "Some Basic Statistical Formulas," containing all the necessary formulas.
iii. .BRING COMPUTERS TO CLASS
Second Day of this section (# 10, February 21). Continue discussion of variance and hypothesis testing, including how to calculate variance on Excel. No quizzes will be set this period.
BRING
COMPUTERS TO CLASS
.
Third Day of this section (#11, February 26).
"Analysis of Variance Homework" due.
Bring Answers to turn in during class and discuss. Will count as two quiz
grades.
Topics covered: nature of time series data, macro
relationships, the theory of the consumption function, the data of the national
accounts, real versus nominal values, percentage change, and regression. The
software packages utilized will be GRETL and Excel. We will be starting with a
reading from Keynes's General Theory,
the origin of the idea of the consumption function. As listed below, we have
posted a reader's guide to this text.
In order to explore Keynes's ideas from a data standpoint we will be utilizing
data from the Federal Reserve Bank of St. Louis database and the GRETL
econometrics software. The assignment listed below as "Macroeconomic Time
Series: The Consumption Function" will be our initial foray into this
area. Print it out and bring it to class, where it will form the basis of our
class discussions.
Finally, we have created a data project, titled "Consumption Function
Assignment." This is the final project of the course and will be due on
Thursday, March 6. In completing it, you will utilize your knowledge of GRETL
and Excel, as well as of the theoretical interpretation of the consumption
function. In presenting your analysis, you should also use the insights into
the visual display of data that you learned from our discussion of graphing and
your experience in the course. .
First Day of this section (#11, February 26).
Print out these readings, read them and come to class prepared to discuss them.
A handout will be passed out prior to today. In class today we will discuss it. Bring the document passed out prior to this day to class. “The Consumption Function in the Great Depression.” This is a document I created for illustrating Keynes’s ideas from the 1930’s
with data,
Second
Day of this section (#12, February 28)
Readings: "Macroeconomic Time Series: The Consumption Function," continued.
Today’s class
assignment is contained in the document on the website titled: “Macroeconomic
Time Series: The Consumption Function.” This is a document that contains
a discussion of the Keynes reading and a GRETL assignment with data to estimate
a realistic consumption function. We will discuss both of these in class.
Your final
project is contained in the file: "Consumption
Function Assignment". You
can get stated on it early, now, if you like. Print out this document, read it
and bring it to class the rest of the semester. Complete it by March 6.
Third Day of this section (#13, March 4)
Extra
Interest