Lecture 2: Models, Data, and the Scientific Method in Microeconomics

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Models and Data

Introduction to Economic Models

Economic models are essential tools used by economists to simplify and represent complex real-world phenomena. By focusing on key relationships and variables, models help economists analyze and predict economic behavior.

Model: A simplified description of reality, often using mathematical or graphical representations.
Data: Empirical evidence used to evaluate the accuracy of models and understand how the world works.
Correlation vs. Causality: Correlation refers to a statistical relationship between two variables, but does not necessarily mean that one causes the other.
Experiments: Controlled or natural experiments help economists measure cause and effect.

Evidence-Based Economics

Opportunity Cost of College

Economists use data to assess the value of education by considering both direct costs and opportunity costs.

Direct Costs: Tuition and fees (e.g., Toronto Metropolitan University 2023-2024: Domestic $7,236–$13,288; International $35,072–$40,485).
Opportunity Cost: The value of the next best alternative forgone, such as potential earnings from working instead of attending college. For example, at a minimum wage of $17.60/hour, working 50 hours/week for 28 weeks yields $24,640/year (before tax).

The Scientific Method in Economics

Steps of the Scientific Method

The scientific method, also known as empiricism, is a systematic approach to understanding economic phenomena.

Developing Models: Construct models that explain some part of the world.
Testing Models: Use data to test how closely the model matches actual observations.

Role of Models

Models are not exact; they are simplifications.
They generate predictions that can be tested with data.
Average outcomes can mask individual variation.

Example: The Wright Brothers

The Wright brothers succeeded in building a functional airplane by first constructing models and testing them in a wind tunnel, rather than building full-scale planes that often crashed. This illustrates the importance of modeling and experimentation in scientific progress.

Returns to Education: An Evidence-Based Example

Modeling Wage Increases from Education

Economists often model the returns to education by assuming that each additional year of education increases future earnings by a fixed percentage.

Assumption: One more year of education results in a 10% increase in future earnings.
Example Calculation:

First Year: $15 × 1.10 = $16.50
Second Year: $16.50 × 1.10 = $15.00 × (1.1) × (1.1) = $18.15
Third Year: $18.15 × 1.10 = $15.00 × (1.1)3 = $19.965
Fourth Year: $19.965 × 1.10 = $15.00 × (1.1)4 = $21.9615
n-th Year: $15.00 × (1.1)n

Formula:

Hypothesis Testing

Getting a college degree (years 13–16) increases wages from $15 to $21.9615, or 46.41%.
Calculation:
Alternatively:

Variation in Returns

Not everyone will see their wages increase by 10% with every additional year of education.
The average can mask variation among individuals.

Empirical Data: Canadian Wages by Education Level

Average Canadian wage, ages 30–34, in 2016:

Education Level	Average Wage ($)
No certificate, diploma or degree	31,778
Secondary (high) school diploma or equivalency certificate	39,152
Apprenticeship or trades certificate or diploma	48,785
College, CEGEP and other non-university certificate or diploma	44,535
University certificate or diploma below bachelor level	43,496
University certificate or degree at bachelor level or above	56,182

Comparison: College vs. High School Graduates

College graduate average wage: $56,182
High school graduate average wage: $39,152
Percentage difference: (43.5% higher)
Model predicted 46% higher; empirical data shows 43.5% higher, which is reasonably close.

Limitations and Signals

Not all college graduates earn the average wage.
Does finishing university increase earnings by more than 10% over the last year, or does it act as a signal of ability, work ethic, or perseverance?

Additional info: In economics, signaling refers to the idea that completing a degree may indicate certain qualities to employers, beyond the direct skills learned.