1. Lecture 2: Positivism, its variants and its impact on Economics
Research Methods
Lecture 2: Positivism, its variants and its impact on Economics

2. Why study Positivism?
Hughes & Sharrock (1997: 24): positivism was ≈ orthodoxy in social science
No longer believed? (Williams, 1976)
Yet economics still heavily influenced
Authors defined in terms of positivism
Positivist tools (e.g. survey) still dominate
Must try to give it a fair hearing!

3. Roots of positivism
Renaissance/Enlightenment thought of 16th/17th Centuries
Philosophy divided into empiricism/ rationalism: foundation of knowledge experience/reason; Bacon/Descartes
Saint-Simon: liberate people from dominant ideas; French Revolution
Get past illusions to “social facts” (Durkheim)

4. Comte’s positivism Influenced by Hume’s attacks on metaphysics
Two bona-fide forms of knowledge: empirical and logical, but empirical emphasised
Precision, clarity and certainty
View world as machine (reflects Descartes)
World comprises deterministic laws, regularities; waiting to be discovered by the scientist

5. Positivism: basics Laws: whenever A, then B (plus CP)
Causality: constant conjunctions of events (Hume)
Single cause leads to single effect (Durkheim)
Mill’s tendency statements, Hume’s caution both too weak for modern positivists

6. Scientistic naturalism
Social science should imitate natural sciences (although why? Never stated!)
Aim for “unity of method”
Differences acknowledged between subject matters
Science proceeds via observation, modelling, to get to laws

7. Observation
“Brute facts” (not affected by any judgement): mimic natural sciences (e.g. atom, velocity)
Observation is preconception free (Durkheim) and Value-free (positive analysis)
Correspondence theory of truth
Variables; measuring properties present in entities
Quantification: counting frequency of some property present in some entity
Operationalism: object defined in terms of the means of measuring/checking it (Hausman: 14)

8. Theory development Individualism; reductionism Modelling
Testing predictions of models
Verification
H-D model tries to solve problem of induction

9. Logical positivism
Carnap, Mach (Vienna Circle), Ayer, Russell: trying to make positivism more logical
Meaningful (True) statements must be verifiable
But now analytic statements can be true by virtue of the logical rules by which they are deduced
Yet LP questioned ‘ideal types’

10. Popper’s intervention
Karl Popper: capturing spirit of positivism in many ways but opposite in others
Sceptic: verification impossible
No theory proven; yet to be falsified
“Scientific” theories are testable
Theories set up bold conjectures to be tested
Test theories by their predictions

11. Popper’s intervention
Falsification from a single counterexample
Learning by trial and error
Idealised view of science
Kuhn, Lakatos: Popper underestimated tenacity with which “failed” theories are retained
Kuhn: sciences proceed irrationally; normal vs. revolutionary science

12. Friedman (1953) Highly influential essay
Can be interpreted as combining elements of positivism with Popper
“positive economics”
Purpose of theory = prediction
Good theories predict well
Simplicity and precision also good

13. Friedman Assumptions of theories not important
Assumptions are always simplifications - cannot be “realistic” - cannot assess theory via “realisticness”
Assumptions are shorthand for conditions, etc. under which theory works
Model works “as if” assumptions are correct: e.g. mobile leaves; profit maximisation

14. Conclusions
Positivism has had several highly significant effects on economics:
Mimic natural sciences
“Value-free” analysis
Causal laws: “if X then Y” type
Quantification
Tools used
Emphasis on deductive logic

15. Conclusions H-D model Friedman also very influential
Assertions about “positive” economics, the role of assumptions, prediction and falsification (echoing Popper) adopted strongly (at least “officially”)
Both subject to considerable criticism
Next two lectures will engage criticisms of positivism and its variants