Chapter One. 15

Economics: Scarcity and Choice. 15

 

Economic Models

 

 

Watches as Models of Time  16

Donald Elliott

Southern Illinois University-Edwardsville

Realism in Airplane Models  16

Regan Whitworth

American University of Armenia

What is an Abstraction or Model?  16

Herbert M. Bernstein

Drexel University

Models of Prospective Spouses  17

Joe A. Garwood

Valencia Community College

Economic Models and Paper Planes  17

Rose M. Rubin

University of North Texas

Logical Fallacies

 

 

Illustrating the Fallacy of Composition  21

Steven T. Call

Metropolitan State College of Denver

Common Logical Fallacies  22

Ralph Byrns

University of North Carolina-Chapel Hill

Logical Errors in Rain Dancing  22

Gary M. Galles

Pepperdine University and UCLA

Correlation vs. Causality  23

Bienvenido S. Cortes

Pittsburg State University

Graphics

 

 

Graphical Literacy  24

Michael Kuehlwein

Pomona College

Graphs and the Distribution of Grades  25

Ralph Byrns

University of North Carolina-Chapel Hill

Positive vs. Normative

 

 

Are You Positive that’s not Normative?  27

Brian Eggleston

Augustana College

Distinguishing Positive from Normative. 28

Stephen Teney

The Franciscan University of the Prairies

Ideology and Economic Analysis. 29

Robert D. Simonson

Minnesota State University-Mankato

All Economic Goals are 30Normative

Ralph Byrns

University of North Carolina-Chapel Hill

Microeconomics and Macroeconomics

 

 

Using a Watch to Distinguish Micro/Macro. 31

Jerry McElroy

Saint Mary's College‑Notre Dame

Distinguishing Macro from Micro. 31

Ralph Byrns

University of North Carolina-Chapel Hill

Scarcity and Choice

 

 

Rational Decision Making and Economics. 32

Eric K. Steger

East Central University

Scarcity and Immortality. 32

R. Michael Brown

Metropolitan State College of Denver

A Date with Scarcity and Choice. 33

Don C. Jackson

Abilene Christian University

Scarcity and the Speed of Light 33

Seymour Patterson

Truman State University, Missouri

Resources

 

 

Economic Capital vs. Financial Capital 34

Marvin L. Larson

Southwest Missouri State University

An Alternative Taxonomy of Resources. 34

Ralph Byrns

University of North Carolina-Chapel Hill

Opportunity Costs

 

 

What is an `A' Worth?. 35

Dennis C. McCornac

Kalamazoo College

Valuing Lives. 35

William L. Weber

Southeast Missouri State University

What Makes Something a Free Good?. 36

Carole E. Scott

State University of West Georgia

Does Everything Have a Price?. 36

Ralph Byrns

University of North Carolina-Chapel Hill

Economic Efficiency

 

 

Efficient Inefficiency. 37

Gary Galles

Pepperdine University and UCLA

Productive versus Allocative Efficiency. 38

John W. Reifel

Grand Valley State University

Engineering versus Economic Efficiency. 39

Carole E. Scott

State University of West Georgia

Inefficiency. 39

Ralph Byrns

University of North Carolina-Chapel Hill

Rationing in a Prisoner of War Camp. 40

Mark Evans

California State University-Bakersfield

 

 

 

 

Chapter One

 

Economics: Scarcity and Choice


 

Economic Models

Watches as Models of Time

Donald Elliott, Southern Illinois University-Edwardsville

How to introduce the concept of a "model"‑‑its purpose and evaluation. Hold up your watch. Ask: (a) Is a watch a model? (Yes) (b) Of what? (The passage of time.) (c) Must the watch duplicate the actual process of the passage of time? (Of course not; it simplifies this complex process by providing an acceptable representation of the process.) (d) Is there a unique model? (No; consider the many different mechanisms used in watches to stimulate this process‑‑springs and balance wheels, tuning forks, quartz crystals, etc.) (e) How can one evaluate the relative performance of different models? (If the models (watches) yield different predictions (times) over some period of observation, they can be evaluated relative to some benchmark which is considered to represent reality.)

Realism in Airplane Models

Regan Whitworth, American University of Armenia

Bring to class in separate boxes an elaborate plastic model airplane and a balsa glider. Display the plastic model to the class, pointing out all the "realistic" features of the model: its color, rivets, visible seams between plates, markings, etc. Then point out that it's really NOT realistic: it's made of plastic, not metal; has no seats; is not big enough to get into; and moreover, it won't do the one thing which airplanes must do: FLY!!! Remove the balsa model from its box. Point out that this model, which many people would regard as much less realistic, will fly. A demonstration is sometimes a useful diversion.

It can then be pointed out that no model is realistic, in the sense that it can't do everything the original does, or it wouldn't be a model. The kind of model one chooses depends on what one is trying to find out. Both models have their uses, but neither is "realistic" if put to the wrong use.

What Is an Abstraction or Model?

Herbert M. Bernstein, Drexel University

To emphasize the need for abstracting or constructing a simplified model when explaining economic relationships, I draw a crude face on the board.

I ask what the drawing is, and students respond that it is a face. I ask them to describe this face, and if they have ever met anyone who looks like this caricature. The point is made that they do not need a Rembrandt depiction to ascertain certain information and that relevance, rather than realism, is the essence of theorizing.

Figure 1-1

Models of Prospective Spouses

Joe A. Garwood, Valencia Community College

Early in the Principles course we all usually deal with the concept of abstracting and its importance to economics. We need to do this to show why it's necessary to abstract, and to allay student apprehensions about our simplified examples and heavy use of models, theories, principles, etc.

I ask a student whom I know to be single whether or not he or she ever intends to marry. If the answer is yes, I point out that there are roughly three billion people of the opposite sex to choose from and that finding "Mr. or Ms. Right" could be quite a chore. I then ask how the student intends to go about finding the ideal mate. In response, the student will indicate that certain criteria are used to reduce the sample to manageable proportions, e.g., appearance, education, location, personality, religion, or special interests.

After going through this process I point out that the student has been abstracting and emphasize how necessary it is to the final outcome. I also point out that the criteria used represent theories about what will make the ideal mate for that student. Conclusion ‑ abstractions and theories are absolutely essential if we are to make any sense out of the real world. This is a real interest grabber and it develops an appreciation for the need to abstract.

Economic Models and Paper Planes

Rose M. Rubin, University of North Texas

Students often have difficulty initially grasping the concepts of modeling and of economic models as representations of theory. I find that this idea can be presented in a readily comprehensible way by using what is probably the most instantly recognized "model" a paper airplane.

I follow a standard discussion of "What is Economics?," by discussing the methodology of economics. As I proceed, I very ostentatiously pick up a large piece of paper (preferably colored, which is easily visible to the entire class) and start folding what the students quickly recognize to be a simple paper airplane. At the proper point in the discussion to introduce the concept of a "model," I hold it up and ask, "What is this?" Someone in the class inevitably responds, "A paper airplane," so that I can then ask, "How do you know it is an airplane?" The usual response is in terms of, "It looks like an airplane." or "It has wings." (Sometimes, a member of the class will come up with the word "model"). Then, I introduce the idea that there are certain, specific variables or factors which indicate that this is a "model" of a plane. While it is clearly a "plane," it does not include all the details of an actual plane, i.e. no motor, no propeller or jets, no wheels, etc. Nonetheless, it has been clearly recognized as a paper airplane or model of an airplane.

Then I draw the analogy between the "plane" and economic models or theories as abstractions from reality, which are nonetheless representations and which describe the entire economy (macro) or specific areas of the economy, such as markets (micro). Further, these abstractions may contain only key variables, (give examples) and still represent a complex economy, just as the paper airplane is recognizable by its wings.

The second stage of this demonstration is to ask, "Will it fly?" Of course, the students know that it potentially will and usually respond, "Try it" or "Test it." This leads into a discussion of the use and usefulness of models not only for initial description of the economy, but also to show that change in the variables permits analysis of resulting changes which occur in the system. At this point, add ailerons on the wings or a paper-clip ballast to the paper airplane and see what happens to the direction of flight to demonstrate changing or adding variables to the system.

Logical Fallacies

Illustrating the Fallacy of Composition

Steven T. Call, Metropolitan State College of Denver

Failure to avoid the fallacy of composition accounts for many errors in economic analysis, both by professional economists and by laymen. I use variants of the following two examples to illustrate the fallacy. They are particularly effective in large classes.

(a)    Place your class notes where they are difficult to see from the rear of the room. Ask a student somewhere near the middle or rear of the class if he can see your notes. If done properly, the student will say no. Ask him to stand. He should now be able to see the notes. Since the class is simply the sum of individual students, it should follow that if everyone stands up, everyone should be able to see your notes better. Ask the class to rise. In large classes, no one can see anything. This is a powerful demonstration.

(b)   Ask a student to quietly drop his or her desk top (where feasible). This can be done with very little disturbance to the class. Again, since any one student can do it, and since the class is just the sum of students, everyone should be able to lower their desk tops simultaneously without disturbance. In a large class, the sound is deafening and very effective. This technique sets up the class for a wide variety of policy and theoretical issues where aggregation and externalities are important.

Common Logical Fallacies

Ralph Byrns, University of North Carolina at Chapel Hill

One way to enrich a discussion of scientific methods and the process of theorizing is to discuss some of the more common logical fallacies. Among these are:

(a)    Appeals to authority, or ad hominem arguments. Albert Einstein (or the Bible, or the president, or my Mother) said that "...". Therefore, it must be true that "...". Alternatively, communists (or the devil) believe that "...". Therefore, "..." is obviously wrong. Or, Keynes was a communist and therefore, his suggestion that "..." must be wrong. Such appeals are, of course, not compatible with logical or scientific approaches to solving problems.

(b)   Post hoc ergo propter hoc. Precedence does not imply causation. To make this point, suggest that if the idea that anything that follows another is necessarily caused by the first, then roosters would be justified in believing that early morning crowing causes the sun to rise. Similarly, union wage hikes or big government deficits, or growth in the money supply do not necessarily cause price inflation simply because they precede it. Nor does victory by the National Football Conference team in the Super Bowl necessarily portend an increase in the Dow Jones index, etc. These are simply statistical artifacts until more scientific causal explanations are developed and tested.

(c)    Composition and Decomposition. The whole may be either greater than (synergy) or less than the sum of its parts. If you buy all of a cow's components at your local butcher shop, you will still be unable to assemble a cow. Similarly, a crowd of people may behave very differently than any of the individuals that comprise it would alone (e.g., a lynch mob). A basketball player who tries to play against a five member team is unlikely to score one‑fifth as many points as any team composed of five individuals, even if they are less talented on average. Nor would two teams of 50 players each be likely to score 10 times as many baskets as two standard 5‑member teams.

Logical Errors in Rain Dancing

Gary M. Galles, Pepperdine University and University of California, Los Angeles

It is often difficult to impress students with the necessity to consistently apply the logic of opportunity cost thinking to reach correct conclusions. To drive this point home, I ask how accurate the results of a string of implications AàBà...-->Z would be if an error were made somewhere in the chain. They see that the conclusion can be way off, and farther off the earlier in the chain the error comes (even if all the other links are logically correct), which I use to emphasize the special importance of examining the beginning assumptions of a chain of logic as well as each implication step. I then illustrate the point with the example of rain dancing.

I ask the students why rain dancing could arise and persist for over a century when it does not affect whether rain falls. All it takes is a view of God as one who needs appeasement and a post hoc, ergo propter hoc fallacy. Once I get the idea of dancing to appease the rain god (whose anger is shown by the fact that it hasn't rained when it should have), and it rains after such a dance, the post hoc ergo propter hoc conclusion that the dancing caused the rain could easily be reached. Once this is established as a theory, there is no natural tendency to correct the error. If the tribe dances long enough, it will rain; if it doesn't rain, they didn't dance well enough, or long enough, or their hearts weren't in it or it wasn't enough like the ancestors did it. Further steps in logic are taken, starting from the error rather than examining the initial error.

Correlation vs. Causality

Bienvenido S. Cortes, Pittsburg State University, Kansas

Much has been said about the common fallacy in economic methodology that association is causation. Simply because two variables are found to be statistically correlated does not necessarily imply that they are causally related. A high correlation may reflect a spurious or nonsensical relationship. Some classic examples include the "Super Bowl Predictor" (Stovall, 1988) which contends that when the NFC team wins the Super Bowl, the stock market goes up, and Jevons' theory that sunspots cause the business cycle. In beginning principles and more so in advanced economics courses which require students to formulate and test cause-and-effect relationships, it is also very important to emphasize the causality must be based on sound economic theory. Even if the movements of tow variables are causally related, the direction of causation may be altogether different from what was expected. It is possible that the direction of causality may be reverse or even two-way. With or without getting into a discussion of Granger (1969) causality tests, the instructor will be able to demonstrate the significance as well as the difficulty of inferring causal relationship by asking the class:

What variable causes what? (Or alternatively, which one comes first?)

(a)    advertising and consumption?

(b)   government spending and income?

(c)    sunspots and economic activity?

(d)   the chicken and the egg

Possible answers:

(a)    consumption causes advertising (Ashley, et al, 1980)

(b)   government spending causes national income (Holmes & Hutton, 1990)

(c)    economic activity causes sunspots (Sheehan & Grieves, 1982)

(d)   the egg causes the chicken (Thurman & Fisher, 1988)

Graphics

Graphical Literacy<