Philosophical Foundations Lecture 4

Organization of this lecture Philosophical Foundations: Positivism Normativism Pragmatism Blending the Philosophies Empiricism in Research The Scientific Approach

These philosophies stress confirmation rather than discovery. Different philosophies of research are introduced to illustrate how they contribute to economic research. “One’s philosophical beliefs affect one’s choice of ‘legitimate questions’ … as well as one’s choice of research methods” (George Ladd) Each philosophical position has advantages, yet each has problems. In practice, researchers tend to use a combination, stressing different positions for different problems. These philosophies stress confirmation rather than discovery.

Positivism Contends that only “factual” knowledge from observation (the senses) is trustworthy. Stresses measurement. Logical positivism expands this to include reasoning and theory as valid means to achieve reliable knowledge. While never a dominant philosophy in economics, it became influential in the mid-20th century, with proponents such as Wassily Leontief, Milton Friedman, and Harry Johnson. John Maynard Keynes’s father (John Neville Keynes) was an early proponent in the 1890s

Logical positivists do not believe in the scientific validity of prescriptive or descriptive knowledge about values. Only things which can be directly observed or measured are considered by positivists as valid for scientific attention. Positivistic knowledge is also culturally dependent since culture can affect interpretation of observations

Logical positivism holds that theoretical concepts are only valid if theory can be quantified. (too extreme a position for most economists). Both facts and theories are seen as sources of hypotheses – economists embrace this component of positivism. But a problem with positivism is that many things that are not visible or “concrete” are still real. eg. demand relationships can’t be “seen” but are very real – their characteristics can be estimated.

Logical positivism is not accepted by many economists, but has had a profound effect on economic thinking and research. It has served to place more emphasis on measurement and quantification in economics. eg. new methods in statistics and econometrics Also more attention has been focused on values as being positivistic knowledge, when they are quantifiable or demonstrable. eg. What things people value, or how much they are valued.

Positivism has also highlighted the importance of objectivity. In emphasizing the importance of providing evidence, personal judgments and perceptions are not accepted as “scientific” information. In summary, positivism has had important and lasting effects on science and economic research. But it is too limiting a philosophy to be the dominant philosophy of science.

Normativism A collection of philosophies – emphasizes that knowledge of the goodness or badness of conditions, situations, and actions is necessary to produce prescriptive knowledge (what “ought “ to be done). Normativistic knowledge in economic research emphasizes people’s values – efficiency, welfare, income, standard of living, quality of life. Intrinsic values (good and bad) are considered knowable.

However, normativism in economics is not concerned with moral questions of right and wrong (but rather good or bad, which is different). Economic choices (the “right choice”) may entail selecting between several “bad” or unfavorable alternatives. Personal or private values should not be considered, but rather public knowledge of values. Emphasis is on objectivity

Objective Normativism refers to the position that the desirability of a result or outcome can be known, based on experience or logic. Objective normativism accepts that value knowledge is sometimes essential for statements about what should be done to accomplish specific goals or objectives. eg. “The people of the world are better off with free trade than with restricted trade”. Any discipline that deals with public policy must use normative value judgements

Pragmatism Mainly focused on prescriptive knowledge (what ought to be) and emphasize problem solving. Believes that positivistic value-free knowledge and normativistic value knowledge to be interdependent. “Workability” (appropriateness for the problem at hand) is the central pragmatic criterion for judgment.

Pragmatism became a prominent philosophical force in economics research in the 1920s. Institutional economics (ie of society’s institutions) pragmatically focuses on problem solving. Test of Workability is the primary test for reliability of prescriptive knowledge. ie. Is the problem solved? Clarity – if solution is not ambiguous or vague Coherence – if prescription works Correspondence – if consistent with what we already know.

Pragmatism plays the greatest role in problem-solving research, less in subject-matter research and the least in disciplinary research. U.S educational and political systems are dominated by the philosophy of pragmatism, which stress problem-solving and workability (achieving results).

How the Philosophies Blend Most disciplines have adopted the philosophies of logical positivism, objective normativism and pragmatism in some combination. Economics is a problem-solving, decision-oriented discipline by nature. Many different kinds of problems are addressed, ranging from simple everyday activities to complex theoretical problems of cause-effect relationships.

The three philosophies – positivism, normativism, and pragmatism – may all be more or less important depending on the type of research. Disciplinary (and basic theoretical) research focuses on logical positivism and objective normativism. Subject-matter research involves all three philosophies. The focus is on understanding outcomes of proposed actions, which leads to guidelines and decisions. Problem-solving research that addresses particular management of policy questions for a decision-maker can be both positivistic (eg. estimating parameters) and normativistic ( eg. estimating consumer surpluses)

All types of research are needed – all are relevant (in different cases) However, some contend that too much emphasis has been place on disciplinary journal publishing. This fosters a situation where economists only communicate with other economists. And only about theoretical issues. On the other hand, most noneconomist users of economic research want the results to be intuitively obvious – without understanding of complexities. This is unrealistic!

Empiricism in Research Methodology The influence of logical positivism fostered interest in measurement or quantification, as applied to economics. Empiricism goes beyond this in subjecting measurement results to testing. Collecting of social and economic data led to statistical methods of analysis, including estimation techniques. The integration of mathematics with economic theory led to the development of econometrics.

Econometrics originated in the early 1900’s and was augmented tremendously by the advent of electronic computers. It is now considered essential analytical training for all economists. Since it emphasizes empirical data and measurements it is both positivistic and pragmatic. Some leading economists (eg. Leontief) argue for more empiricism in economics – more measurement, reliance on data (objective observation) and quantitative analysis to improve scientific respectability of economics.

The Scientific Approach The central scientific methodology (not a single “scientific method”) has the following general steps: Identify the problem/issue/question Define research objectives Develop approaches for achieving objectives (including hypotheses of expected outcomes) Conduct the analysis (testing the hypothesis) Interpret the results and draw conclusions These steps are common to all disciplines

Problem identification is affected by individual as well as group perceptions – ie. what we perceive as a problem. Objectives, the identified set of specific goals, are inherently normative, ie. related to our values and perceptions Both problem identification and objective specification may have a pragmatic orientation.

Laboratory and field sciences tend to see their research process as producing reliable data, devoting attention to proper experimental design to generate statistically valid numbers . Social sciences see their process more in terms of using data to understand relationships and to address problems requiring decisions. Physical and social science disciplines tend to differ in the last step of interpreting the data. Economists maintain that normative interpretation of data is often necessary with complex social science research.

Deduction and Induction in the Scientific Approach Usually the approach in economics consists of the “ongoing interfacing” of deduction and induction. Deduction is involved in developing theory and induction is used in validating or evaluating the applicability of the theory through empirical testing. Here we are concerned with how deduction and induction are used, rather than their relative merits as forms of logic.

Deductive reasoning starts with premises – assumptions . If the individual premises are true and complete and the reasoning is correct, the conclusion is reliable.

The most direct application of deductive reasoning in the scientific approach is in Step 3, developing hypotheses. 1 2 3 4 5

Theoretical reasoning can include: Disciplinary research often involves developing or modifying theories, leading to hypothesized outcomes. Theoretical reasoning can include: Newly developed theories New conceptual elements added to theories Modification of existing theories In applied research, the reasoning involves the application of existing theory and evaluation of expected outcomes.

Induction is an empirical process of arriving at new generalities from observations and does not depend on previous knowledge (ie theories). The testing of hypotheses is largely inductive. Statistical induction is the process of testing estimates of parameters or the amount of variation explained in variables describing relationships.

Induction cannot provide proof of a proposition because we cannot examine all possible evidence. We can only describe the probability of the outcome. We cannot say that an outcome or relationship will always hold – the underlying cause of the outcome or relationship could change over time. But outcomes based on evidence can have a specified probability

Interpretation of results (step 5) is largely inductive Interpretation of results (step 5) is largely inductive. In examining implications, we often extrapolate from the specific analysis to more general applications. eg. A representative firm can be used to reason through the expected behavior of an industry. The outcome for the industry can be estimated to be the outcome for the firm times the number of firms.

Deduction provides the necessary implications of premises, which may be general (laws, axioms, principles) or specific (factual); induction examines the validity or applicability of the premises Deductive reasoning can organize knowledge and deduce new relationships but is not sufficient as a source of new knowledge. Inductive reasoning fails to use prior knowledge, and is therefore inefficient. Both deduction and induction are necessary.