Economics 201
Economic
Professor Lawlor
Syllabus (Fall, 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.
2. Detailed Subject Discussion
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 economic research involves formulating concrete theoretical hypotheses from imaginative linking of economic data. This generally means applying some aspect of economic theory to a situation. Thus a second stage of economic research of observed economic behavior is theory building, either formal or informal.
A third stage in the use of economic data in economic research 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.
To restate and summarize, consider the following schematic description of economic research:
Stage One – Data Exploration
Stage Two – Theoretical Statement of Economic Behavior
- at the least informal and implicitly
- at the most formal, by explicit and falsifiable hypothesis statements
Stage Three - A Formal statistical test of these statements
- Hypothesis testing
It is the first stage (data exploration) and, in a beginning way, the third stages (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.
We don’t wish to exclude other research in economics that may not fulfill, any, or all of these stages, or to suggest that nothing is written that does not fit in this description is unworthy economic research. But this is the idealized view of economics that appeals to most researchers in the profession when they reflect on what they are doing. Some research is sometimes focused on only one of these steps. Some economic theory is impossible to test because it is stated in such a way that it must always be true, given its assumptions. For other problems there may be no available data that would be sufficient to test every economic hypothesis we would like. Also, it is always the case that the lure of ideology can creep-in to influence our view of any situation. Is an attitude of animosity toward government’s role in economic behavior an outcome of the observation of empirical results, or a bias generated by the implicit conservatism of the manner in which much of economic theory is stated?
At any rate, much of the skill of empirical economics consists of imaginative and creative ways to either state problems or use new sources of data. Economic theory is useful in the suggestions it may offer to state problems from an economic point of view. But economic theory should only be seen by serious students of a particular problem as intermediate stage. The full usefulness of looking at a problem from an economic point of view must rest on whether an economic explanation is insightful and is consistent with believable empirical evidence – data.
For students with an interest in the formal aspects of theory testing the department offers Economics 215, Econometrics.
3. 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 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 9 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, with the exceptions of the assigned homework. For the in-class quizzes, in most cases the grade will be 95, 85 or 50. In rare case it will be 75. 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 and homework for a verifiable record of your quiz average at the end of the semester. If you later think your grade was computed incorrectly, this proof of your grades will be essential in convincing me that we need to change a grade.
The quiz grades are designed with a number of reasons in mind. One, they are designed to reward conscientious students with a sure guaranty on 20% of your grade at least a B level (or higher) 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.
Additionally, since students are naturally uncomfortable with not feeling secure with how they are being evaluated, this device is a vehicle by which you can guarantee high grades on at least part of your work.
Lastly, since the class is only for ½ of a semester, and since we are trying to convey a “skill” that all economists should enjoy and find useful, mastery of data analysis can be difficult to assess. Most of you will get very high marks and the few that do badly will really only have themselves to blame. Bad grades can usually be traced to some form of not taking the course seriously enough – by either not coming to class, by not reading the assignments ahead of time, or by trying to complete a project the night before it is due. Getting good at data analysis requires skills and practice. The various components of this course are designed to provide you those opportunities.
This quiz grade directly 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.
In addition, there will also be two data projects assigned (one due on Sept. 18, and the other on Oct. 9), worth 40% each. Obviously these will form a major component of your grade. The assignments instructions are posted on the web-page. If you have any trouble identifying them, or about them, be sure to ask me, hopefully in class so others can benefit. Please start the projects early, They each are extensive, and the in the various parts they vary greatly as to the difficulty and skill that they require. Also please make your final reports as neat and presentable as is commensurate with the grade you think they deserve. I will strive to evaluate them fairly and objectively. .
Thus the total grading scheme is:
Quiz grade: 10%
Participation: 10%
Data project
Data project
3. Another word on 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.
As already
stated, students should try to make the final hard copy presentation as clear,
neat and presentable as is consistent with the grade you think they deserve.
All work should be done alone. This allows for maximum learning potential, as
well as assures the instructor that each student is graded exclusively for his
or her own work and understanding. 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://www.wfu.edu/~lawlor/eco201.html
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.:
4:30-5:00 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
1. Introduction, Housekeeping, (#1, Aug. 28)
Go over syllabus. Students should read in its entirety
In class reading and quiz: “What are Data?”
2. Introduction to GRETL (#2, Sept.
2)
Topics Covered: Assembling cross sectional data series, 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
Preparation for Class: Install GRETL software package on computers. Downloading instructions available on the website.
3. The Basics of Regression Analysis (# 3, Sept. 4)
Topics Covered: The rationale for regression analysis.
Detailed discussion of the mechanics and meaning of regression using Gretl
4. The Comparative Heath Spending of the OECD
Nations (#4, Sept. 9)
Topics Covered: The O.E.C.D. Health Data base. The relationship between health spending, GPD and other variables.
5. Comparative Health Spending in the OECD,
continued. (#5, Sept 11)
Topics Covered: How and Why does
6. Interim Day (#6, Sept. 16) Meet in Library 476. Session taught by Ms. Mary Scanlon, Reference Librarian. The morning section of ECN201
will meet in room 204 while the afternoon section of ECN201
will meet in room 476.
7. (#, 7, Sept. 18): NO CLASS.
Project 1 Due. Turn in Project 1 in a box designated for your section in 117 Carswell. I will accept projects as on time if turned in by
4PM on Sept. 19, when Mrs. Van Sice goes home and closes the office. After that
the grade declines by one letter each day it is late. No exceptions without
letter from an M.D.)
Variance in Data: How to Measure It, Use It, and Display It.
8. First Day of Section (# 8, Sept. 23): The Basics of
Variance
Topics Covered. Hypothesis testing, variance, the area under the standard normal curve, differences in means, t-statistics and the use of Excel spreadsheets and computer.
9. Variance, Second Day (#9, Sept. 25) An example and a Homework Assignment (to be
graded, and worth two quiz grades.) The example
will involve measuring variance among a sample of readings of cholesterol
levels, and testing for differences. The homework assignment asks you to do the
same for samples of infant birthweights.
10. Exploring Times Series Data and Testing Economic Theory: Day 1: The Consumption Function (#10, Sept. 29)
Due in class:
"Analysis of Variance Homework" due. Bring Answers
to turn in during class and discuss. The H.W. will count as two quiz
grades. Same late policy as Project # 1 applies.
Topics covered: nature of time series data, macro relationships, 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.
At this stage if will also be useful to see an estimate of the Consumption function for the 1930’s. The document “The Consumption function and the Great Depression” will serve this purpose.
Please download, read and bring to class both of these documents.
11. Exploring Times Series Data and Testing Economic Theory: Day 2: Exploring
the data and modern form of the consumption function. (#11, Oct. 2)
Topics covered: In order to explore Keynes's
ideas from a data standpoint we will be utilizing data from the Federal Reserve
Bank of
Reading: The assignment listed
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.
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.
Project: Finally, we have created a
data project, titled "Consumption Function Assignment." This is the
final project of the course and will be due on Oct. 9. 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 strive
to show your reader courtesy as much as possible in your final report.
Remember, such courtesy and neatness conveys how important you think the material
is. 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 Oct. 9
.
12. Exploring Times Series Data and Testing Economic Theory:
Day 3: The Consumption Function: Consumption and saving in the 1990s and early
21st century. (#12, Oct. 7)
Topics covered: Nature of the “Wealth Effect” in theory and in data, multi-variable regression. Included will be some discussion of the
role of “housing wealth” and
by Danielle DiMartino and John Duca