Economic Methodology – Final Notes
Chapter 1: The Received View
Historical Context and Background
Logical Positivism, also known as the Received View of science, emerged in Vienna and Berlin during
the 1920s to 1950s.
Influential groups included the Wiener Kreis (Vienna Circle) and the Berliner Kreis (Berlin Circle)
- It formed as a reaction to metaphysical approaches
o Emphasized observable phenomena and rejected unverifiable metaphysical claims
- The movement aimed for purity and clarity, focusing solely on surface phenomena observable
and measurable in science
Key contributors are Moritz Schlick, Rudolf Carnap, Otto Neurath.
Core Concepts of Logical Positivism
Empiricism and Logical Analysis
- Empirical verification through observation and measurement
- Logical consistency ensures that theoretical frameworks align with empirical findings
Demarcation Criterion
Distinguishes scientific statements from non-scientific ones
- Scientific Statements:
o Analytic (true by logic or definition, e.g., “Circles are round”)
o Synthetic a posteriori (verifiable by observation, e.g., “The Earth revolves around the Sun”)
- Non-scientific Statements:
o Synthetic a priori (e.g., “Time is linear”) lack verifiability
Operationalization
It defines how theoretical concepts are linked to measurable, observable categories
- Example: Unemployment defined and measured by correspondence rules (e.g., survey criteria)
Verification and Explanation
Two-Step Verification Process:
1. Empirical verifiability of a statement
2. Confirmation through repeated observation and logical consistency
,Deductive-Nomological Model (Carl Hempel)
It consists of
- Explanans: Lawlike propositions (unrestricted, true synthetic a posteriori) + Initial conditions
(observable and verified)
- Explanandum: The phenomenon being explained
à Symmetry Thesis: Explanation and prediction use the same laws and conditions.
Scientific Laws (or Lawlike Propositions)
Characteristics:
- Verified and unrestricted generalizations (not limited to a finite space, time, or group)
- Identify causally relevant factors
Challenges:
- Subjectivity in defining scientific laws
- The problem of induction (Hume): Limited observations cannot guarantee universal
generalizations
Responses to the Problem of Scientific Laws
1. Instrumentalism (Schlick):
o Treats scientific laws as usable and instrumental guidelines or hypotheses
o Not necessarily true (so, not meaningful) but practically useful
2. Confirmationism (Carnap):
o Probabilistic approach: Laws are confirmed with degrees of probability rather than absolute
certainty
Decline of Logical Positivism
The inability to fully operationalize certain theoretical terms (e.g., “utility” or “atoms” pre-electron
microscope).
By the 1960s, logical positivism faced significant critique:
- John Passmore: Declared it “dead as a philosophical movement”
- A.J. Ayer: Concluded it was ultimately “false”
Key Takeaways on Logical Positivism
- Science: Meaningful, verifiable statements (analytic or synthetic a posteriori)
- Non-Science: Includes unverifiable synthetic a priori propositions (e.g., “The subconscious is
the origin of the world”)
, Operationalization and Measurement
Correspondence rules bridge theoretical concepts and observable categories
- Example: Defining unemployment using legal and survey criteria ensures empirical grounding
- However, different operationalizations may lead to varied interpretations of the same concept
Instrumentalism and Confirmationism
- Laws serve as practical tools or probabilistic regularities rather than absolute truths
- This flexibility acknowledges the inherent uncertainties in scientific theories
The Legacy of Logical Positivism
Although it “failed”, logical positivism remains foundational, with modern philosophy of science
evolving in reaction to its principles.
Chapter 2: Methodologies of Positive Economics
Foundations of Econometrics
The Econometric Society was founded in 1931 to advance economic theory through its integration with
statistics and mathematics. It emphasized a unified approach to solving economic problems, grounded
in the rigorous methodologies characteristic of natural sciences
- Econometrics seeks to build a bridge between theory and empirical observation, allowing
theoretical models to be tested and refined through statistical tools
Steps in Econometrics
1. Model Specification: Models are expressed in explicit functional forms, often linear, to describe
relationships between variables
a. Example: A linear regression model to predict economic output based on input factors like
labor and capital
2. Data Definition and Assembly: Relevant data series for the variables are identified and
operationalized. Operationalization ensures theoretical concepts are measurable using
correspondence rules
a. Example: Unemployment rate defined through specific survey criteria
3. Theoretical Validation: Statistical methods test the validity of the theoretical model by
analyzing its consistency with the data
a. Example: Hypothesis testing to verify causal relationships between economic variables
Chapter 1: The Received View
Historical Context and Background
Logical Positivism, also known as the Received View of science, emerged in Vienna and Berlin during
the 1920s to 1950s.
Influential groups included the Wiener Kreis (Vienna Circle) and the Berliner Kreis (Berlin Circle)
- It formed as a reaction to metaphysical approaches
o Emphasized observable phenomena and rejected unverifiable metaphysical claims
- The movement aimed for purity and clarity, focusing solely on surface phenomena observable
and measurable in science
Key contributors are Moritz Schlick, Rudolf Carnap, Otto Neurath.
Core Concepts of Logical Positivism
Empiricism and Logical Analysis
- Empirical verification through observation and measurement
- Logical consistency ensures that theoretical frameworks align with empirical findings
Demarcation Criterion
Distinguishes scientific statements from non-scientific ones
- Scientific Statements:
o Analytic (true by logic or definition, e.g., “Circles are round”)
o Synthetic a posteriori (verifiable by observation, e.g., “The Earth revolves around the Sun”)
- Non-scientific Statements:
o Synthetic a priori (e.g., “Time is linear”) lack verifiability
Operationalization
It defines how theoretical concepts are linked to measurable, observable categories
- Example: Unemployment defined and measured by correspondence rules (e.g., survey criteria)
Verification and Explanation
Two-Step Verification Process:
1. Empirical verifiability of a statement
2. Confirmation through repeated observation and logical consistency
,Deductive-Nomological Model (Carl Hempel)
It consists of
- Explanans: Lawlike propositions (unrestricted, true synthetic a posteriori) + Initial conditions
(observable and verified)
- Explanandum: The phenomenon being explained
à Symmetry Thesis: Explanation and prediction use the same laws and conditions.
Scientific Laws (or Lawlike Propositions)
Characteristics:
- Verified and unrestricted generalizations (not limited to a finite space, time, or group)
- Identify causally relevant factors
Challenges:
- Subjectivity in defining scientific laws
- The problem of induction (Hume): Limited observations cannot guarantee universal
generalizations
Responses to the Problem of Scientific Laws
1. Instrumentalism (Schlick):
o Treats scientific laws as usable and instrumental guidelines or hypotheses
o Not necessarily true (so, not meaningful) but practically useful
2. Confirmationism (Carnap):
o Probabilistic approach: Laws are confirmed with degrees of probability rather than absolute
certainty
Decline of Logical Positivism
The inability to fully operationalize certain theoretical terms (e.g., “utility” or “atoms” pre-electron
microscope).
By the 1960s, logical positivism faced significant critique:
- John Passmore: Declared it “dead as a philosophical movement”
- A.J. Ayer: Concluded it was ultimately “false”
Key Takeaways on Logical Positivism
- Science: Meaningful, verifiable statements (analytic or synthetic a posteriori)
- Non-Science: Includes unverifiable synthetic a priori propositions (e.g., “The subconscious is
the origin of the world”)
, Operationalization and Measurement
Correspondence rules bridge theoretical concepts and observable categories
- Example: Defining unemployment using legal and survey criteria ensures empirical grounding
- However, different operationalizations may lead to varied interpretations of the same concept
Instrumentalism and Confirmationism
- Laws serve as practical tools or probabilistic regularities rather than absolute truths
- This flexibility acknowledges the inherent uncertainties in scientific theories
The Legacy of Logical Positivism
Although it “failed”, logical positivism remains foundational, with modern philosophy of science
evolving in reaction to its principles.
Chapter 2: Methodologies of Positive Economics
Foundations of Econometrics
The Econometric Society was founded in 1931 to advance economic theory through its integration with
statistics and mathematics. It emphasized a unified approach to solving economic problems, grounded
in the rigorous methodologies characteristic of natural sciences
- Econometrics seeks to build a bridge between theory and empirical observation, allowing
theoretical models to be tested and refined through statistical tools
Steps in Econometrics
1. Model Specification: Models are expressed in explicit functional forms, often linear, to describe
relationships between variables
a. Example: A linear regression model to predict economic output based on input factors like
labor and capital
2. Data Definition and Assembly: Relevant data series for the variables are identified and
operationalized. Operationalization ensures theoretical concepts are measurable using
correspondence rules
a. Example: Unemployment rate defined through specific survey criteria
3. Theoretical Validation: Statistical methods test the validity of the theoretical model by
analyzing its consistency with the data
a. Example: Hypothesis testing to verify causal relationships between economic variables
