Department of Economics, McMaster University

ECONOMICS 3F03: Methods of Inquiry in Economics Fall 2002
Thomas Crossley

LECTURE #1

Readings:

“Statistics and Logic”, Chapter 1 from Lucy Horowitz and Lou Ferleger, Statistics for Social Change, Black Rose Books, 1988

“The structure of Scientific Explanation”, Chapter 1 from F. Neal and R. Shone, Economic Model Building, Macmillan, 1976.

Topic

What is:

Inquiry?
Research?
Science? (economics is a social science)

Important Caveats

No clear answers to these questions (contrasting views in the philosophy of science)
Adequate discussion would take all term (philosophy of science, methodology of economics are big topics)

Goals

Familiarity with some basic ideas (deductive and inductive reasoning, the difference between association and causation……)
Motivate interest in experiments

A. Deductive Logic

A syllogism or argument is made up of statements
The statements include premises and a conclusion
Statements can be true or false; arguments may be (deductively valid or invalid)
The truth of the conclusion rests on the validity of the argument AND on the truth of the premises.

Example 1:

If A then B

Therefore B.

“If A then B” and “A” are the premises. “Therefore B” is the conclusion.
Premises of the form “If A then B” can be divided into the antecedent (“If A” ) and the consequent (“then B”).
This in an example of affirming the antecedent, and it is a valid form of argument.

Example 2:

All men are mortal.

John is a man.

John is mortal.

This is another example of affirming the antecedent (a valid argument).
Note that the first premise could be equivalently rewritten: “If John is a man then John is Mortal.” The flexibility of the English language may sometimes “hide” the structure of an argument.

Example 3:

All men are immortal.

John is a man.

John is immortal.

This a valid argument that leads to a false conclusion (because one of the premises is false)

Example 4:

If John is a man, John is mortal.

John is mortal.

John is a man.

This is an example of affirming the consequent, which is an invalid form of argument.

Example 5:

All men are mortal.

John is not mortal.

John is not a man.

This is an example of denying the consequent, a valid form of argument.

Obviously, what we can learn about the world with deductive logic alone is limited because the truth of conclusions rests not only on the validity of the argument but also on the truth of the premises. We need a way to assess the validity of our premises.

Observation plays an important role in Science.

Considerations of Deductive Logic lead to one philosophy of science known as “Falsificationism”. Falsificationism is associated with the philosopher Karl Popper.

The key idea in Falsificationism is that empirical evidence can refute (falsify) a theory or hypothesis, but cannot confirm a theory. This is because using empirical evidence to confirm a theory would be “affirming the consequent” – which is not a valid form of deduction.

Example 6:

If all crows are black, observed crows will be black.

Observed crows are black.

Therefore, all crows are black

Contrast this with the next example:

Example 7:

If all crows are black, observed crows will be black.

A white crow has been observed.

Therefore, not all crows are black

Falsificationism has problems, and many modern philosophers of science have rejected it. For example, a strict version implies that nothing is learned from experiments or observations that are consistent with theories or hypotheses. In practice, scientists tend to give quite a bit more credence to theories or hypotheses that have withstood many tests.

Even if falsification is not a good model for science, the idea that a good scientific theory should be testable (make predictions that could be falsified) is still important.

C. Inductive Logic

· Inductive logic seeks generalizations

· The strength of inductive arguments in not 0/1 (valid/invalid). Inductive arguments are stronger or weaker than other inductive arguments.

· In principal, 1 counter example discredits an inductive argument. An inductive argument can never be “proved”. (See the discussion of Falsificationism above).

· In practice, a single falsification rarely leads to the rejection of a hypothesis. One reason for this is that hypothesis can never be tested in isolation. For example, to test a hypothesis is physics usually involves a whole series of auxiliary hypothesis about how the measuring equipment works and so on. A negative result might mean that hypothesis under consideration is false, or it might mean that one of the auxiliary hypothesis is false. This ambiguity means that central hypothesis or theories are usually only abandoned when a weight of evidence against them has accumulate.

· One well known philosopher of science who has written about the process by which theories or hypotheses are discarded or replaced after evidence has accumulated is Thomas Kuhn. His name is associated with the idea of “paradigm” shifts and his work is an example of how modern philosophy of science has moved from being a normative exercise to being more positive.

· Remember from your principles class: normative if “how it should be”, positive is “how it is”. Modern philosophers of science have focused more on how science is actually done, and less on deriving rules (from logic) as to how it should be done. For example, Falsificationism (discussed above) is a normative philosophy of science that has between criticized in part for its failure as a positive theory.

D. Inductive Fallacies

· Deductive and Inductive arguments suffer from false premises and invalid (in the case deduction) or weak (in the case of induction) arguments.

· Some common problems (fallacies) with inductive arguments (that is, characteristics of weak inductive arguments) are:

o Over-generalization (selected or non-representative samples)

o Insufficient evidence (arguing from anecdote, for example)

o Causal fallacies

· Avoiding causal fallacies is an important theme of this course

· A causal fallacy is interpreting association as causation

· If variable (or event, or phenomena) A is observed to be associated with (correlated with, occur together with) variable (or event, or phenomena) B, there are several possibilities:

o A causes B

o B causes A

o Another factor, C, causes both A and B

Example 8: poverty and high birth rates

Example 9: university education and wages

Example 10: smoking and lung cancer

Example 11: “gateway” drugs

· How can we distinguish causation? One common idea is that if A always precedes B (in time) then A causes B. Does a retail shopping boom cause Christmas?

· What exactly do we mean by causation? Its closely related to the notion of a counter-factual statement. A counter-factual statement tells us what would happen if circumstances were different: If A had occurred, B would have resulted. A causes B. There is also a sense of necessity: If A occurs, B must occur.

· Counterfactual or causal statements is a characteristic that distinguishes scientific explanation from mere description.

E. Looking Ahead

· In the next few weeks we will discuss how good experiments can help us to build strong inductive arguments (inductive arguments that do not suffer from causal fallacies).

· We will discuss the characteristics of convincing experiments, including manipulation of the treatment, control groups and randomization.

· We will discuss the limits to (and possibilities for) experimentation in the human sciences (including economics).

· We will discuss how circumstances that approximate experiments (and hence can form the basis of a strong inductive argument) sometimes arise naturally, or by accident. These are sometimes called “Natural experiments.”

Example 12: The Mariel Boatlift

F. Some Other Issues to Think About

· What are the roles of theory and observation? A very old view of science was that the scientific method based all theory on observation – observation proceeded theory. However, without theory, how would we know what to observe? Thus there is an inter-play between theory and observation. Theories and hypotheses guide our observation, and observation leads us to modify, update, and even reject our theories and hypotheses.

· What are the characteristics of Science? What is pseudo science? Some suggestions: Science has a theoretical foundation, and makes counterfactual and causal statements. These distinguish it from simple description. Good scientific theories are accessible and testable (or falsifiable).

· What are scientific laws, hypothesis, theories and models? What distinguishes each from the others.

· Does it matter if the assumptions (premises) of a theory are correct? What if a theory based on false assumptions makes useful predictions? (The “instrumentalism” of Friedman).